I bought a Fairphone3. I was hoping to quickly receive a Fairphone-supported Android again, which is Google-free. You know ? so there is not this giant cooperation getting to keep tabs on where I am at all times and who I talk/write to. Plus, it doesn't really feel like my phone, if the Google account is "connected" on there.

Anyway, Fairphone didn't actually want to go to the same trouble again as they did with the Fairphone2, so I had to wait. And now, for the first time, I actually "rooted" my phone. It's now mine again!

I used the /e/ foundation's version of LineageOS, which has a great mission (an actual Google-free phone[1]), a good tutorial for my phone, a nice roadmap and they support my exact phone model.

After two weeks of using the new OS and apps, I can say I am quite happy!

How I'm using it

Here are some points to make on what the /e/+LineageOS approach is and how I'm using it:

• You don't need an /e/ account. It's only a service they offer, should some peple like to backup mails and contacts between phones or computers. I have Nextcloud for that.
• The /e/ foundation added the MagicEarth app, so there is some decent Navigation based on OpenStreetMaps data. I have to say it works quite well!
• /e/ comes with their own app store, which I like. It has apks from popular non-free apps, should you want/need them, like Whatsapp or Netflix. The source for these apk files is cleanapks.org. That is still a hot topic in the free software world. You can install other stores of course, like FDroid (completely free) or Aurora (niche apps from Play Store). Updating apps works well in all of those.
• They don't give you too much control over what's on your home screen (app launchers, widgets). You can't delete the standard ones, so you have less space for the ones you care about. The solution is pretty cool, once you know it: You can install a different Launcher. I used Launcher<3. Now I have space for the two widgets I love: AgendaWidget (installable from the app store) and TaskWidget (comes with openTasks).
• The old gang for supporting my Nextcloud integration on Android is working better each time I set up a phone: Nextcloud app + DAVx5 + ICSx5 + OpenTasks
• Other notable base necesseties, while we're at it: AnySoftKey, KeepassXC, WebTube

What is the future for /e/? Apparently, they're working on creating a more aligned Look&Feel, so that standard apps they offer look more alike. I'd like that. For example, the Mail app is a fork of K-9, but got a clean modern look. However, the version of the fork is rather outdated, I hope they catch up.
 

Drawbacks

I don't want to leave the impression that not going with the mainstream is all roses. It is actually a small sacrifice - next to doing your own OS installation (which is actually not really hard but it will take you at least an hour, and then you start with installing and configuring apps).

Here is a list of annoyances I have so far:

• Typing with auto- correction is okay but I know it's a bit worse than cutting edge. More mistakes slip in.

• Webtube's full-screen mode is not full screen.

• MicroG keeps crashing and I don't know what that means for my OS functionality

• My phone would like to connect to my ChromeCast but it can't.

• Text-to-speech is a while away but somebody's working on it.

Actually, all or most of these issues are being worked on. It's a matter of time.

Living somewhat free of giant corporations means you'll be living in the slight past. Maybe two or three years beind. It's really not that bad, but I can see that not everyone feels like they can do it.

Trust

A big issue in this whole story, and also a complex one, is trust ? we are here because we don't trust Google or Apple to be good stewards of all our data for all time. But we can't do it alone. We have to trust the makers of our alternative tooling to some degree, as well. In this situation, I am putting various levels of trust in the makers of LineageOS, the /e/ foundation and (by extension) cleanapk.org. But I'm also trusting app makers like the guys at KeepassXC. Some of the trust here is easier to maintain with the monopolists ? we're trusting Google and Apple (at the moment) to have a good eye on the security aspect of their app store.

It's complicated.

[1]  /e/ uses MicroG as a free and open-source replacement for Google Play Services, and Mozilla Location Service for geolocation. One of their goals is to support beign Google-free for non-technical users. They even offer smartphones (like the FP3) pre-installed for sale.

Software is a peculiar thing. It is made by engineers, but how to estimate costs and how to understand the end product is very different from other engineering sectors. This difference comes from the level of complexity that comes with even reasonably-sized software. The digital age just began. It might be a while until we can estimate and understand software projects, if ever.

This paragraph above is true and well-understood in the software industry by everyone who is paying attention. I refer you to two recently-published and very well-written articles about this. Every layman should be able to read them. They look at this problem from two different angles - the estimation of what reasonable costs and the expected stability of delivered software should be, and the understandability of software, especially when data science and machine learning are being used.

The Age Of Invisible Disasters:

Nobody dies on a failing CRM project. At least not so far as I know. So why should you care? Everyone still gets paid. You should care because within government, the only sector where failure gets any real coverage, I count £20b in failed IT projects over the last decade alone. Because within publicly quoted companies such failures are a bonfire of shareholder value. Because the ability to deliver technology projects will become the determining survival factor for many companies. Finally, you should care because if there is a skills shortage (or as I prefer to say, a talent shortage) and talent is tied-up with moribund IT projects, the lost opportunity cost to business is vast.

The terrifying, hidden reality of Ridiculously Complicated Algorithms:

If, as Jure suspects, machine judgement will become measurably better than human judgement for important decisions, the argument for using it will only grow stronger. And somewhere in that gap between inputs and outputs – the actual decision making part of the process itself – is something that can shape our lives in meaningful ways yet has become less and less understandable.

So - both estimations and understandability of software are currently really poor. That makes this a weird time to be involved in the software sector. It makes it exciting to predict the near future. But also, it makes it highly costly for businesses to do any software development. It isn't, however, stopping the digital advancement. Information is power, and who gets it right, can thrive.

Are you getting this angle from the software developers or software companies you talk to? I'm guessing the answer is no. I'm guessing they are telling you that your software project will certainly succeed, that maintenance will be no big deal, and so on. I get it, as framing the planning of software projects like I and the two articles above did, might not be the best marketing approach. This is business, after all.

But if you want to know if your software developer actually understands the situation, ask them about software complexity. Put the finger where it hurts. They either should somewhat admit to this weird state of their sector, and maybe tell you how they try to keep complexity at bay, or they are overselling and you should politely decline their services.

Fairphone is making more steps to its goal of modular phones which are used longer (instead of, for instance, buying a new phone because the camera is a bit outdated). I have a (almost) two-year old Fairphone2, and making photos and videos is one of its most important functions. Thus, I bought the new camera module.

The new module upgrades from 8 to 12 megapixels, but there is much more to a camera than the pixel count.

Here I'll show a few before and after pictures for any Fairphone 2 owners who are interested. I'll show original first, then the new camera.

First picture: Objects in fall afternoon sunlight, no special instructions

The original camera did make some odd choices when making the picture, especially with lightning. The new module got it much better. This is also a reminder that a camera is hardware, but it needs software making good decisions.

Second picture: Objects in fall afternoon sunlight, focus on the sunflower

When I focused on the sunflower, the original camera made a better picture. The new camera, however, gets more out of the scene. The table isn't as dark, and the colours are generally more natural.

Third picture: Freezer magnets on slightly reflective surface

It's less obvious, but I think the new camera gets details like natural colours and reflections noticably better.

I also made a comparison picture in a quite dark setting, and both cameras made really different choices. The old one caught too much light, the new one slightly too little. I installed OpenCam to see what difference another camera app made, and that result was much better.

I recommend getting the new camera if photos are important to you (e.g. you make 90% of the family pictures with your Fairphone2 and you believe 45 EUR are worth catching scenes slightly more naturally) and also to not underestimate what a different app could do, as well.

I was inspired by a call to write members of the European Parliament about upcoming legislation. Christian Engström writes in this post that self-written emails have the greatest effect, so I picked the two topics still being discussed and wrote about those.

Here is the text of my email:

Dear delegate of the JURI committee,

I am writing to you from The Netherlands as a citizen who is very concerned about internet legislation. As a computer programmer and father of two, I am following the current debate about the future of copyright with great interest.

I want to focus on two articles which I find so troubling that I am writing you today. These are the topic I discuss among my peers and which I raise awareness of: Article 3 (copyright exception for the modern research method Text and Data Mining) Article 13 (Automatic upload filtering).

Article 3:

I urge you to not only give the right to mine data to "researchers".

* We need journalists to have this opportunity, as well. In "big data" the important revelations can be found which we direly need.

* Also, big companies will find their data troves or already made their own. It stifles innovation if small, young companies are not allowed to find value in large amounts of data.

Article 13:

I urge you not to mandate that we hand over to machines to decide what can be uploaded or not. Machines cannot do this task, because they do not understand the context (e.g. satire) and uses covered by exceptions. But even more, this is

1) a censorship-like scenario, in which companies will rather block too much than being accused of not blocking forceful enough.

2) working towards centralisation of publishers, since implementation of such blocking behaviour is expensive and thus favoures the bug players. It will create even more of an oligopoly than we already have now.

Sincerely,

Nicolas Höning

In which I show my solution for listening to audio and watching videos at home in the digital way, with an acceptable quality (for most people), but for a very little costs and almost no hassle getting it to work.

Here's the short rundown on requirements I had and maybe you also agree on (which in turn means you might want to read on):

• All digital (sound and video files & streaming services)
• hassle-free setup - this is for the bulk of people who like me, are not in for weeks of research or tooling
• very low costs
• no vendor lock-in & use of standards where possible
• acceptable (not necessarily the world's greatest) audio quality
• remote control for everything (by mobile phone or actual remote controls)

And here is what what I actually use:



PlayOn Harddisk Media player                     40 EUR
Google Chromecast                                        39 EUR
Raspberry PI as music box                          ~70 EUR
Envaya Bluetooth Audio Player                   140 EUR
--------------------------------------------------------------------------
                                                                        289 EUR
 

Why? - So here's the problem

Listening to music and watching videos at home. Everyone (in a modern household) wants to do this, of course. These days, however, the number of choices how to do it is vast, to the extent that researching what to buy can take forever. You can also built and configure a lot of things yourself, for instance using a raspberry pi and a custom-made luxurious soundcard. I understand that there were tough choices to make 30 years ago, as well, like how large the TV should be and if gold cables are really needed to get everything out of your audio signal.

I believe that today the number of sources for media has increased (and I'm only counting the digital cases for me anymore, really), because next to playing sound and video files from your hard drive there are now a number of relevant streaming services you might want to use.

On the hardware side, a lot of devices are on the market now, which all do something to play audio to you, in varying locations and quality. In fact, it's a young market with a lot of companies trying to develop exactly what we need. It's exhausting to do research there!

A lot of these new solutions are designed to lock you in and to upsell, something Apple is really good at. They want you to buy something wireless for every room in your house and also for on-the-go and what started at 200 EUR ends up at 1300 EUR and you need to keep using this system from now on.


The (my) solution

So I decided to lower my expectations with respect to audio experience, otherwise I would never install something modern. Otherwise, I believe I got pretty close to my requirements. Let's list what I bought:

Harddisk Media player

This little device plays almost any movie file you give it and it comes with a remote control (not pictured). I like USB sticks, which I can place there, but you could also connect a computer network cable and read files from some place in your LAN. I bought this a few years ago for around 90 EUR I believe (it's out of stock now), but nowadays the devices all seem to cost around 40 EUR. Connect to your TV via HDMI and it works.

Chromecast

Google makes this nifty little device which connects to your Wifi and then lets you show most of the content your phone screen would show, but streamed fromt he Wifi via the Chromecast to a connected screen, i.e. your TV. Your phone becomes a remote control. For streaming a few things which are well-supported (Youtube almost all of the time to be honest), this works really well. You have to help ot find your Wifi but that is very nicely done. Its usability breaks down though if you are streaming content via an app that is not supporting it or if you do not want the whole Google app stack on your phone (like I'm trying to these days), so I'm eagerly awaiting more innovation in this gadget area.

Envaya Bluetooth Audio Player 

The audio speaker is the area where one can lose the most time and money. I settled for a bluetooth speaker I can put anywhere I want, has decent reviews about its sound (not great, but reviews from people with better ears than me -audiophiles- are tiring), good bass, an AUX in and can even charge your phone. You could pay less money here, but it is something you'll use a lot. Using the AUX in, it can even give your TV watching experience a boost. This works out of the box.

Raspberry PI as music box

Streaming music to the speaker from the phone or laptop has its limits. It really occupies your phone for example, and if you want to play files from a hard drive you cannot reach that from your phone. So one might want to use a music server, which can be controlled from laptop and phone. Enter Pi Musicbox, a ready-to-use open source software package which can run a RaspberryPi for this purpose. Basically, it runs Mopidy, an open source music server oftwear, but neatly wraps it for perfect fit on RaspberryPi. The nice thing about Mopidy is that there a many mobile apps written for it, so you can control the Pi Musicbox nicely from a mobile device. Pi Musicbox plays files but also streams web radio stations and gives access to streaming services (though I cannot vouch for the Spotify support yet, still trying to get the most out of it - however, I still can use my phone here). By the way, the 70 EUR I listed above roughly cover the Raspberry PI (about 40 EUR) plus necessary extra things like an SD card, a case, power supply and a 32GB USB stick.
    This gadget is the only one requiring a little work, but not much, as you can see:
    1. put the Pi Musicbox image on a SD card
    2. edit the config file so it finds your Wifi when it boots
    3. put in the USB with your music
    4. boot
 

Algorithms should be made open ("transparent") to the public. I doubt, however, that we will live in a world where you can demand an explanation of what an algorithm did to you.

So, algorithms are a hot topic now. They change our world! You might remember how Facebook has an algorithm which manages user's news feeds, but it performed very poorly and kept trending fake news. Sad! Or the current discussions about self-driving vehicles being a danger to our safety - or even a danger to social peace because millions of driver jobs are endangered.

Let me make the side-note here that in both of these cases mentioned above, and many others which are similar, the awareness might be new, but the fact that algorithms do crucial work in our newsfeeds and our car safety systems is actually not that new actually. As a good example for this take banks, who have been using data mining algorithms to decide who should get a mortgage decades ago.

Lots of demands, but few incentives

However - the conversation is starting on what we should demand from entities (companies, governments) who employ algorithms w.r.t. the accountability and transparency of automated decision-making. The conversation is being led by many stakeholders:
 

• Think Tanks: For example, Pew research just published a report, in which expert opinions around this question where gathered: "Experts worry [algorithms] can (...) put too much control in the hands of corporations and governments, perpetuate bias, create filter bubbles, cut choices, creativity and serendipity, and could result in greater unemployment.".
• NGOs: With Algorithm Watch we now have the first NGO that dedicates itself to "evaluate and shed light on algorithmic decision making processes that have a social relevance".
• Governments: The EU General Data Protection Regulation (GDPR, enters into law 2018) has a section about citizens having "the right to question and fight decisions that affect them that have been made on a purely algorithmic basis".

There are many things being said, and I find this discussion more vague the longer I listen, but maybe the one specific demand all these stakeholders would get behind is this: Explain how the algorithm affects my life.

So it seems like a lot might be happening in this direction, but I believe very little will happen. Why?
 

1. It is very costly to develop this feature (of explainable algorithms). I'll discuss why that is in more detail below. In fact, this feature is so costly, making it mandatory might actually drive smaller software development shops out of the market, as only the big players have enough manpower to pull it off.
2. Customers will not demand it in everyday products, no matter what think tanks say. Open source software is not demanded by customers - it is being used because engineers love it.
3. It will only become the norm in a specific type of algorithmic software if the product actually needs it. Consider a medical diagnosis software - the doctor needs to explain this diagnosis to the patient. Or the mortgage decision example where I believe lawmakers could step in and make banks tell you exactly why they will not give you a loan.
    

Explanations: decisions versus design

Algorithms should be "explainable", they say. However, there is no consensus to what that actually means.

In the light of complexity, I believe that what is explainable is not well-defined - while many people talk about explaining individual decisions, all we can really hope for in most cases is explaining the general design - which is much less helpful if our goal is to help people who have been wronged in specific situations. There can and should be transparency, but it might be less satisfying than many people hope for.

A new paper by Wachter et al (2017) makes a good point here that I agree with. They say that many stakeholders to the EU General Data Protection Regulation (see above), have claimed that "a right to explanation of decisions" should be legally mandated, but is not (yet). Rather, what the law includes as of now is a "right to be informed about the logic involved, as well as the significance and the envisaged consequences of automated decision-making systems". They also make a distinction between explanations for "specific decisions" versus "system functionality", and they state that the former is probably not "technically feasible", citing a book explaining how Machine Learning algorithms are not easy to understand.

I agree with their doubts here. Let me shortly dive into the feasability problems with explaining specific decisions and also broaden the scope a bit. To me, it comes down to complexity which is inherent to many IT systems that are being built these days:
 

1. Complex data: Let's look at the Facebook news feed example: There is a lot of data going into this algorithm. The algorithm makes thousands of decisions for you while you surf and to fully explain one of them at a later time, you'd need a complete snapshot of Facebooks database at the very second the decision was made. That is unrealistic.
2. Complex algorithms: Many algorithms are hard to understand for humans. Maybe the prime example here are machine learning algorithms. These algorithms are shown real-world data, so they can build a model of the real world. They use this model they built to make decisions in real-world situations. The model often is intelligible to human onlookers. For instance, a neural network (which is for instance used in Deep Learning) reaches a decision in a way that the engineers who "created" it cannot explain to you because the algorithm propagates information through this network many times over because it links back from its end to its beginning (so-called "back propagation").
3. Complex systems: Finally, many algorithms might actually not live inside one computer. You might interact with a system of networked computers, which interact and all contribute their own part to what is happening to you. My favourite example here is a modern traffic control system that interacts with you while you travel through it, and at each intersection you encounter a different computer. I actually argued in a paper I published in 2010 that decentralised autonomic computing systems tend not to be "comprehensible".

So I believe (and agree with Wachter et al) that the demand to explain for any given situation how exactly the algorithm made a decision, is hard to hold. What can be explained is the design of the algorithm, the data that went into its creation and its decision-making and so on. This is a general explanation, which might be useful to explain to the public why an algorithm is treating problems in a certain way. Or it might be useful in a class action law suit. But it cannot be used to give any particular person the satisfaction of understading what happened to them. That is the new reality which probably already exists, but it has to sink in.

The notion of complex, almost incomprehensible algorithms has been brought up previously by the way. I want to mention Dr. Phoebe Senger, who noted that software agents tend to become incomprehensible in their behaviour as they grow more complex ("Schizophrenia and Narrative in Artifcial Agents", 2002), and of course the great Isaac Asimov who invented the profession of "robot psychologist".
 

I dragged it with me after my contract ended in 2014, but I actually made a finished product out of my dissertation after all and defended it at the TU Delft this past May.

It was a pretty formal procedure as you can see, but quite a meaningful end to , and actually a fun day in the end.

The dissertation itself is available here officially, but also hosted by me. I'll post the propositions here:

1. Both the need for low computational complexity of bidding and for effective capabilities of planning-ahead can be addressed in a market mechanism for electricity, that combines the trade of binding commitments as well as reserve capacity into one bid [this thesis, chapter 3].

2. In settings where a uniform price changes dynamically over time and where these dynamics are influenced significantly by consumer behaviour, the ability of a consumer to comprehend price patterns increases if a large part of the other consumers reacts to price dynamics in a manner similar to how he himself reacts to them [this thesis, chapter 4].

3. Dynamic pricing for electricity can effectively reduce consumption peaks, also under the two conditions that the retailer promises an upper limit on prices and designs his pricing strategy for profit maximisation [this thesis, chapter 5].

4. A heuristic control strategy for a battery which is limited in capacity can be designed such that it has the following three advantages: it reacts fast, it can reduce overheating of a connected low-voltage cable significantly and (if prices are dynamic) it can partly earn back the acquisition cost of the battery by performing revenue management [this thesis, chapter 6].

5. There is not one silver bullet to the problem of how to manage a smart grid in the most efficient way. Each setting has its own requirements, given by its own set of stakeholders and design objectives.

6. To have a healthy and happy toddler is not to a small degree a matter of luck.

7. For the foreseeable future, concerns about privacy need to focus on computers and mobile phones, which directly expose political views and social contacts of their owner, rather than smart meters, which expose less meaningful data.

8. If users do not comprehend the reason why a novel technology interacts with them in the way it does, it will not be adopted, even if it is useful and resource-friendly.

9. Electricity grids are the largest man-made synchronous machines, and economies are the most complex man-made systems. To combine them leads to much more complexity than is commonly assumed, and the resulting systems will therefore never be completely understood.

10. In a referral network, where agents base their opinion about the performance of a service on those of other agents, it is beneficial for users if the agents forget old information at a comparable rate. [N. Höning: "Discounting Experience in Referral Networks", Master thesis, Vrije Universiteit (2009)]

I also was asked to write a very short summary, which might be useful here:

New developments require us to reconsider how electricity is distributed and paid for. Some important reasons are renewable energy, electric vehicles, liberated energy markets and the increasing number of smart devices. How we deal with these dynamics will affect important aspects of the upcoming decades, for example transportation, home automation, heating/cooling & climate change.

In order to keep the security of supply high and price fluctuations within acceptable ranges, we need to continuously make the decisions who will supply or consume electricity, at what price and at what time. The resulting complexity should not grow too high for small participants, otherwise novel technology might not be adopted. This dissertation contributes market mechanisms and dynamic pricing strategies which can deal with this challenge and reach acceptable outcomes in four relevant problem settings (mostly situated in lower levels of the electricity grid).

The most critical problem to address are intervals with very high power flow, or with high differences between demand and supply which need to be evened out. Such “peaks” can result in steep price movements and even infrastructure problems. We study decision problems that will arise in expected scenarios where peaks reduction becomes important. In order to arrive at an efficient and usable system, this research specifically looks into

1. Encouraging short-term adaptations as well as enabling planning ahead (of generation and consumption) within the same mechanism.

2. Ensuring that small and/or non-sophisticated participants can still take part in mechanisms.

3. Letting smart storage devices contribute to network protection.

We develop agent-based models to represent expected settings and propose novel solutions. We evaluate the solutions using stochastic computational simulations in parameterised scenarios.

A similarly high-level overview was given by me in a short presentation before the defense.

Last week I attended DockerCon Europe 2014 which luckily happened in Amsterdam this year. I got my finger on the pulse of important developments in the ongoing evolution of the internet and a just-healthy dose of tech-optimism from current Silicon Valley prodigies. I thought I'd share my five favourite slides with a little comment on each.

The internet is still a technological Wild West. So many talented people. So much change and progress in technology each year. So many things you need to know to deliver something that doesn't break for some reason. So much still to achieve. Docker provides a usable (fast and well-documented) way to bundle into a container some things that you know are working, then upload this container on any server and expect this functionality to be up and running and simply work as you expect. It wasn't a DockerCon talk, but I like this short breakdown of what holds us back and why containers can help a lot (9 slides). At Softwear, we are using Docker both in the CI workflow and partly in production (by the way, let me know if you want to do influential UX or QA engineering work for us). The slide above shows the way of thinking going forward - build stacks from things you know will work and will also work together. Like Lego. Then make these light-weight stacks (your actual web applications) work together in creative ways. The current term for a picture like this is "Microservices". This slide from Adrian Cockcroft (who spent six years at Netflix) makes the point how useful Docker will be in more detail. Adrians presentation (all slides) probably generated the most food for thought. My favourite line (slide 26) is:

DevOps is a Re-Org!

meaning that software developers are taking over system operator/admin - tasks in any company which does not actually run data centers (which is becoming a very concentrated business nowadays).

Next, we get to some Silicon Valley - style notion of how suspected technology breakthroughs will change society. Docker Inc. CEO is asking here:

What happens when you separate the art of creation from concerns about production & distribution?

Subtly, there is a picture of the printing press. He wants to say that creators of web applications soon might need to worry less about how they will deploy their app such that it will work, as the "container revolution" will make this trivial. Of course, the web 1.0 kind of already did that for content. However, I can see how lowering a crucial technological barrier for inventing useful web applications can really be significant to innovation. We have a lot of content and ways to get it out there, now let us see what cool applications can be built to assist people everywhere in the world. And although we at this conference were a bunch of rich white males, poor people are hopefully getting access to cheap smart phones soon (Africa is a good example). I, too, find these times exciting. But I was glad to return to my normal life, and to cool down a bit.

This slide gives an indication of the scale of change we are seeing in the software world. Henk Kolk from ING told us how this large bank sees itself as a technology company now and removed everyone from their large IT team who can not program at least something. Being a programmer means being in demand right now but as his slide says as well, speed is key from now on. If you don't get on board with this new way of having tight control over your stacks, together with being totally flexible towards switching technologies, all you will be doing is to jump from one sinking ship to the next. I got both excited and chilled, actually.

An interesting take away of the current weeks is how Open Source currently works. Big money has gotten in on it, because in the software world, you have to invest in widespread and sustainable technology while also having a modern stack. This only works when an open source community carries the technology. Even Microsoft is coming around in major ways. Companies are actually employing the best open source programmers directly to stay on top of things. The industry is a bit different than other industries in this regard (hopefully actually leading the way). On the slide above, Docker Inc. CTO Solomon Hykes is giving us his current set of the rules that he thinks make a technology successful these days. As a consequence, Docker got some interesting new functionality (announced on the first conference day), but it was kept out of the core code - "Batteries included, but replacable".

But it is also not all agreement and happy collaborative coding. No, sir. The latest trend is that a company or a startup guides an open source technology. This makes progress faster and stable, but it can easily break if you annoy the comunity. Node was just forked, AngularJS is having a community crisis. The Docker community is also weary of the Docker startup Docker Inc. In fact, Solomon Hykes spent a lot of his time on stage at DockerCon Europe 2014 to discuss how he wants to succeed as a steward of the Docker technology, using a process he calls "Open Design" (see all slides here). There is an Open Design API through which all feature requests have to go, thus separating people acting on behalf of Docker Inc. from people acting on behalf of the Docker Open Source project - no matter which company pays them at the moment. They are creating and updating their own constitution which deals with this construct as we speak (of course in structured text files, so if you suggest a change, you submit a pull request). So the message of this slide above is simple and compelling:

The real value of Docker is not technology. It's getting people to agree on something.

Replacing "Docker" with any standard, this is something you could also have said during any time of rapid development and change. Interesting times.

P.S. There were some really smart people at this conference, building amazing companies and systems. We can expect to see a lot, e.g. from the Apache Mesos project. I could have chosen more technical slides for this list, but it would have taken me longer to explain why I fancy them. A lot of them were also quite intimidating, actually.

Today, I gave a talk at CWI on how to become more efficient with complex computations in our scientific work. I discussed how I have approached the need for distributed computation (to scale up towards larger and more complex problems) and the problem of organising the scientific workflow when doing experimental work.

I promised listeners that they would get

• hands-on information on getting results from large-scale, "embarrassingly parallel" computations,
•  ... without actual parallel programming,
•  ... little ssh effort
•  ... and using the programming language of your choice.
•  Plus, some tools to keep track of experiments and data.

where I would (not exclusively) mention the tools I have written, StoSim and FJD. I was happy to have a turnout of 16 people and I think we spent an interesting hour.

Here are the slides (direct link to PDF):

I'm quite happy with how the visits to this website of mine have developed over the last year. Here are the monthly numbers:

Btw, since March 2013 I use Piwik for my visitor analytics and am very happy. You should also be happy about that, because I don't store your metadata on Google's servers, only on mine.

An average week looks like this:

You can tell that people mainly come to my site on workdays, weekends are rather quiet. Why is that?

Well, in 2007 or so, I wanted to have javascript tooltips, or "popups" to display context to links when you hover them. I wanted to style them like I wanted. So I wrote a small script. It is very simple but the page explaining it creates almost all trafic to this website. Look at this example of page view numbers ("page views" are the amount of loaded web pages, where "visits" consist of one IP address performing one or more page views in one session) from (I think) one week:

The trend is clear. Around 300 people come to that page about the little javascript thingy every day, and not much else I write gets attention. And as you can tell from the long list of comments there, many people use this javascript thingy in the websites they build. I actually get some satisfaction in making them happy, so I answer many of their questions and actually improve the codebase once in a while.

But here is the problem: There are many other similar scripts for this out there, and I never get mentioned when experts list libraries for such a feature (I have been mentioned in two or three forums, I think). Why do people keep finding this? I think the dirty little secret is that I called it a "popup", while the technically more correct term is "tooltip". Look at search queries that people used when they came to this page:

There you go. Me and a significant amount of people use the slightly wrong term, and that's what drives traffic here. Accidental linguistic match-making in cyperspace. Positive things come from this. The traffic probably improves my Google ranking a lot. Our interactions help my users get something done and make me feel some fulfilment. It's a weird world.

Speaking of the world, here is where my visitors are from Mostly english-speaking countries where a lot of web development happens:

The European Commission just announced a new indicator to measure innovation in its economy. I think it shows how the bureaucrats favour big companies, want to make it easy for themselves and hold a simplistic view of how innovation leads to positive net effects for the economy.

To quote, here are their new ingredients to the indicator:

• Technological innovation as measured by patents.

• Employment in knowledge-intensive activities as a percentage of total employment.

• Competitiveness of knowledge-intensive goods and services. This is based on both the contribution of the trade balance of high-tech and medium-tech products to the total trade balance, and knowledge-intensive services as a share of the total services exports.

• Employment in fast-growing firms of innovative sectors.

1. First, the view that patents are important favours big established companies over small innovative ones. Small innovative software companies are often better off to just move on and not waste their time trying to get a patent. And don't forget that (luckily) in Europe it is difficult to patent software. So comparing to the rest of the world here is even more questionable. Patents are also often used by companies for no other purpose than to block out other companies, which is maybe good for Europe (only if a European company bocks out a non-European one), but it is hardly helping substantial innovation in the economy to form. Another point: I think the EU has the view that innovation has this standard way to lead to positive impacts for everyone: Someone (a big company, see above) invents something, then they patent it and then hire people to develop the invention. As they start producing, they will hire other companies as subcontractors, and so the positive effect trickles down from the inventors to the others. I think that this sometimes happens, but only for big companies. This view is neglecting large parts of the economy. Innovation often happens in non-formal open spaces and/or in collaboration.
2. And about the second ingredient - simply hiring people in "knowledge-intensive activities" gives you points, no matter their actual effects on innovation. That makes it easy to count, but what are we measuring? Are we measuring that these employees are doing something useful with their knowledge-intensive work or are we simply celebrating that people are getting paid to think? For example, I'm sure the banking and lawyer industry has lots of jobs that would count as knowledge-intensive. A reason to celebrate them? Also, government spending on research gives a country points here, no matter what is actually researched.
3. The third ingredient is the only one that makes at least some direct sense to me. One can compare the contribution of high-tech and high-knowledge activities to other services and get some information out of it (albeit my point about the second indicator holds here, as well).
4. The fourth ingredient is based on the assumption that fast-growing companies must be more innovative than other ones. Might sometimes be true, but often probably not. Growth != innovation. A dangerous way of thinking in my opinion. Most often, rapid growth is merely the ability to attract capital - capital that is interested in rapid returns. The substance below the company is indirectly related to the jope on rapid returns, but often not necessary for this capital attraction effect (as the last couple bubbles should have tought us). If your concept of innovation is to enable turnover, it has not been formulated in society's best interest.

I think that behind this formalism there is a dangerous fan-boy attitude toward big companies/big finance and telling the story that they like to tell - an effect of lobbyism. What about small companies? They'll have an even harder time being "sexy" to EU bureaucrats now.

There is so much more happening in an economy, which is one of the most complex systems on earth. One example that comes to mind: what about innovation that isn't directly making money but enabling others to make money? For instance, what if people create an intelligent new way of doing things, but don't directly sell this new way? Maybe they open-source their powerful idea and run a successful little consultancy based on their newly-found reputation. With their help, a part of the European economy considerably improves, in more than just one way (they provde direct services and they shared their knowledge to enable many others), but without the bureaucrats taking notice - their innovation is flying completely under the EU radar.

I know it is difficult to "measure innovation", and that is why I have not yet come up with a better way to measure it. However, it seems to me that to not measure would have been better than to measure like this. A counter-question: why do we actually need this number? It's as if the numbers we have (like GDP) aren't already alchimistic and misleading enough.

I think we live in times where both governments and citizens of western democracies are searching for a new role in their relationship. My point today is only this: the court systems are still working to some degree, and they seem to me a valuable battling field in this search. Citizens should actually pay attention and support causes fought in their name.

First, what do I mean with this "search" for new roles? It is not as easy as some pundits had described, who after 1990 simply awaited the state to take a step back. After some years of perceived openness, where capitalism had supposedly "won" and everyone could relax and enjoy, I think we now rather see the state taking a stronger stand. One reason might be that governments feel threatened by globalization and the internet, creating too much openness and feedback loops for them to feel in control. Another might be rising tension due to the resource front, as energy supply gets tight and climate change restricts what we might want to do with resources we still can get our hands on. Or, more general, this is just the usual dance between governers and governed, a step forth and a step back, and we will only see what it all meant after this song ends.

Anyhow, we are beginning to discuss what "freedom" should mean, again. And when I say discuss, I mostly mean "battling out". Emotions are running high and claims are bold and strong. Governments simply create new facts of what is legally possible, while the Chinese lean back and rub their hands.

Some citizens are being taken to court, others decide to let their quarrel with the government escalate to court. In most of these government vs. someone trials, important definitions are being made, and, as far as the court is still functioning, the outcome of these battles are important for (re)defining freedom, more important than, say, a general opinion piece in The New York Times.

What is also new today is that it is dead simple to support the legal funds of people whose cases you find interesting, via the internet. I believe if you are interested in funding societal change, investing in the legal defense of someone is (to use the lingo of our time) a sound investment. The amounts I gave are by no means to brag about, but I have begun to give to such individuals, and I think I should increase this activity. Here is a short list of who I remember supporting:

• Tim DeChristopher
• Lothar König
• Julian Assange*
• Ladar Levison

There are heroes out there fighting for you right now and it is easy to help them.

* Actually, I only gave some monetary support to Wikileaks as an organisation, after the Collateral Damage video. Criminal investigations into Assange started afterwards and only then it became clear that most of the financial funds of Wikileaks seem to have gone towards his legal defense.

On the way to the offices I work in, the bike path layout had a flaw: To reach Science Park (coming from Amsterdam center), one had to take a little detour. In the situation shown on the picture below, you had to follow the path on the left for about 200 meters and then turn right, in order to continue on the street in the background (here is the view from above). The more direct way, right down the hill, has been an emerging bike path for the better part of a year. It is now becoming an official bike path, as the picture shows (I took it only a couple of days ago).

While it was emerging, the path was muddy, and (especially on rainy days) quite difficult to manage, both down- and upwards. I spoke to some of my colleagues and everyone wanted to take this route, but until now only the young males felt confident enough on their bikes to do it.

Why did everyone feel strongly about taking this route instead of the slightly longer one? There is an emotional cost to pay for being forced to take a longer route, even if it is only slightly longer. Does this emotional cost justify the effort of building this new bike path? I'm not sure, but I sure can say that the city of Amsterdam has a bike path management that pays attention.

A rather famous example (at least in the scientific research community on emergent human patterns) of such an expression by users that their intent differs strongly from the planners' design is this (from an article by Helbig et al from 1997):

I'm not sure if the University of Stuttgart reacted to this, though, back in 1997. I tried to find that place on satellite images, but with no success. They probably redesigned it completely. Just as our emergent bike path, this one is, admittedly, not pretty to look at. However, the response from system planners can be quite different, apparently.

Sometimes you can tell that technological progress is blending into a known science fiction scenario. I think right about now is a time to spot several of those - this year is like those special days when you see a lot of shooting stars. 

So, there is the obvious similarity of governments watching (well, storing and monitoring) more and more of everyone's steps to the famous book "1984".

However, there is more. I recently reviewed "Manna", where a complete automation of societey begins not by replacing low-wage humans, but by algorithms taking over middle management to make fast food stores more efficient (by organising the work of the low-wage humans as efficient as it can be). Recently, reports came out how Amazon's warehouses are actually like that: 

Amazon’s software calculates the most efficient walking route to collect all the items to fill a trolley, and then simply directs the worker from one shelf space to the next via instructions on the screen of the handheld satnav device.

Most of the article is about how bad they treat workers, but their fate is not my point here. And anyway, Amazon puts their warehouses in regions which have very few economic options. Consider that locals in the article are sad because they can't work in a mine anymore. My point is that even mines had middle management. Amazon warehouses are optimally efficient with very few middle management positions (mostly, what is left to be done is to ask the system who was the least efficient and fire and replace them). 

Next to be replaced are the workers themselves. Well... that depends. I'm not sure there will be a business case within th next 50 years for robots doing simple tasks in a warehouse over humans doing it. It's not decided yet if that is going to happen. However - the business case of doing simple middle management tasks has been decided in favour of computers. They are much better in making the most of employee time. 

I'll close ba admitting that the speed and the consequences of automation in our society are discussed by people with more insight and time for this than me, so I think I'm not qualified to say whether this development is negative or positive*. It is negative in Manna, but Manna is just a story. 

* However, Amazon is a monopolist, so there might be a different reason not to use them that much.

To test if a given string is indeed a valid email address is an unsolved problem in programming. The internet is full of endless threads of which regular expression would let all valid addresses pass and forbid all invalid ones. The only agreement is that there is no agreement.

So I welcomed the inspiration of my colleague Jim (at Vokomokum) to implement something straightforward: Check everything before @ to be a valid name (consisting of letters, digits and a couple other characters). Then use some library to check if everything after @ is a mail host currently known on the internet.

I was sold. That seems like a really nice trade-off between quick implementation and effectiveness. It is mostly the host name that is hard to check, so let's simply see if it exists. Mail hosts don't disappear and reappear, so it's pretty safe to ask for the DNS system to know about them at any time. The only drawback here is that you need an internet connection to run this test.

Anyway, here is an example implementation of this in Python:

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    def validate_email(address):
        ''' check email '''
        # check general form: a valid local name + @ + some host
        if not re.match('[A-Za-z0-9\-\_\.\+\$\%\#\&\*\/\=\?\{\}\|\~]+@[^@]+',
                        address): 
            raise('The email address does not '\
                  'seem to be valid.')
        # check host
        host = re.findall('[^@]+', address)[1]
        try:
            # dns.resolver throws an exception when it can't find a mail (MX)
            # host. The point at the end makes it not try to append domains
            _ = dns.resolver.query('{}.'.format(host), 'MX')
        except:
            raise('The host {} is not known in the DNS'\
                  ' system as a mail server.'\
                  ' Is it spelled correctly?'.format(host))

The dns.resolve module has to be installed, as it is not in the Standard Library. It is in the pythondns package, so you could do

pip install pythondns

At this time of writing, Posterous is an elegant, easy way to keep a blog. In 2011, I set up a simple blog to post articles I came across that had some angle on the interconnectedness of energy systems. I loved how I could simply send an email to <blog-name>@posterous.com and the article was posted.

However, Twitter bought Posterous as a modern way to hire their staff and then decided to shut Posterous down. All content will die end of April 2013. This is another hint that if you make something that lives online and there is a possibility you want to keep it, own the domain and be aware that you or someone you can ask for help needs to be able to curate the content over time (I started that blog just posting links, but then also wrote a summary or an opinion here or there - sometimes you don't know you'll want to keep something around for longer when you just started it).

Anyway - so I had to export the content from Posterous and import it into the MySQL database which currently underlines this website. Widely-used blogging software like Wordpress offers an importing tool, but everyone else is probably thinking how to get their Posterous data into their web publishing software.

Posterous offers an export in XML form, but it could have made it easier to deal with it. For instance,  it is hardly parsable XML, and the creation date is in a format used in emails. It took me a bit to get a simple Python script working, and I thought I'd share it here for anyone who needs to do something similar:

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#!/usr/bin/python

from datetime import datetime
import re
import os
from bs4 import BeautifulSoup
from email.utils import parsedate_tz


def san(unicode_str):
    '''
    for sanitizing strings:
     - getting rid of all non-utf8 things
     - escape single quotations
    '''
    s = unicode_str.encode('utf-8', 'ignore')
    s = s.replace("\\'", "'") # first unescape escaped ones
    s = re.sub('''(['"])''', r'\\\1', s) # now we escape all
    return s


psql = open('posterous-import.sql', 'w')

xmls = [xf for xf in os.listdir('posts') if xf.endswith('.xml')]
for xf in xmls[:-2]:
    xfp = open('posts/{}'.format(xf), 'r')
    soup = BeautifulSoup(xfp.read())
    
    title = soup.find('title').text
    tt = parsedate_tz(soup.find('pubdate').text)
    tdt = datetime(tt[0], tt[1], tt[2], tt[3], tt[4], tt[5])
    sql_date = tdt.strftime('%Y-%m-%d %H-%M-%S')
    content = soup.find('content:encoded').text
    
    psql.write("INSERT INTO my_table \
                (title, content, inputdate) VALUES \
                ('{t}', '{c}', '{ed}');\n\n"\
               .format(t=san(title), c=san(content),
                ed=sql_date))

psql.close()

Well, it seemed to work for the contents of my Posterous blog, at least. I only cared about title, content and creation date of each post. 

Place the script above (download) into the folder you get from exporting your Posterous data (mine is called "space-3179959-energy-systems-ticker-0e4cc18feed3e8982ddae1ef4537b529") under the name of import.py (or whatever you like) and then call it via

python import.py

Then, you should find a file called posterous-import.sql which you can use to populate your Posterous posts into your own (MySQL) database. I used BeautifulSoup to be able to parse the XML, so you'll have to install that python library first, e.g. by

pip install beautifulsoup4

Also, you probably first would edit the INSERT statement in line 35 to match your specific table structure which you're importing to.

I recently commented on the idea to reward users if they in return offer flexibility to the management of the system they use. For instance, a congested road could pay people not to ride to work during peak hours. Or in energy management, consumers can offer that they use less energy than they originally planned or a generator offers to supply more.

The general idea is of course not new, but in the IT-congested world we live in now, it becomes possible to negotiate compensations with users in advance and identify them while they actually use the system. This new timing of such approaches makes it necessary to think about novel mechanisms (e.g. what negotation procedure makes sense, which compensation scheme will probably work for both sides).

This approach is not applicable everywhere, for good reasons. In some systems, like the road example, it is hard to track people and probably overall not a good idea. Common approaches like car-polling and toll houses (or simply taxing fuel) can also work to some extent. In other systems, like the energy example, it is not a new idea per se, but how to implement such mechanisms (such that they are usable and serve the existing infrastructure in the best way) is still under heated discussion.

Anyway, there are now two recent examples of this idea being brought to existence in novel circumstances. No idea if these experiments will be deemed a success, though. Time will tell.

• The Dutch railway company wants to pay people if they don't use the train during peak times. This is feasible because the whole system is being switched over to digital passes, so it actually becomes technically possible to track if a specific customers is using the train during peak hours. They are in a trial period. Having to pull a wagon less can make a significant difference to operation costs, I assume.
• Amazon will pay people (with vouchers) if they are willing to wait longer for their package. This might actually stick, since Amazon has the capabilites (technical and organisational) to actually make this an integral part of their strategy. Personally, I think that Amazon becomes a bit too big, but I must admit that they seem to be where they are because they do the things they do pretty well, much like Google.

A conference I'll soon be attending asked participants for the questions they find most important for A.I. I didn't submit any, but from the list of ~150 questions, they now asked us to vote for some (up to ten) that we find most important. Here are my picks (I did it really quickly):

• Q12. DWIM - Do What I Mean problems. Can computers do what I think or intend or say?
• Q15. Can machines and the people think together?
• Q35. The computer processing power is increasing with the invention of new hardware devices, does this mean that the computation processing power is infinite and are humans able to achieve it?
• Q54. Can computers exhibit the dynamics of the financial market , rather can we a) Model the financial market b) Make the computers to exhibit the same
• Q78. Does a system become always smarter by integrating smart sub-systems or smart components together? If no, in what cases it becomes smarter, and in what cases it becomes not smarter even stupid? How to make a system smarter when integrating smart elements?
• Q127. What is the difference between Turing test and Socratic method?

I was a bit disappointed by reading the list of questions. I could not find ten questions to agree with (but I might have missed one or two). Most of them were not only written badly, but clearly simply asked for what the researcher is currently working on (i.e. how can A.I. make use of mobile technology?/how can social networking improve our lives?) or what has been a question in AI already 50 years ago (i.e. what is thinking, really?).  

I am currently not that fanatic about being called an A.I. researcher, and this (to some extent) showed me why. The concepts are too fuzzy for me, everything goes under this A.I.  hat. Too few people care about topics that deeply influence how we will manage in the upcoming decades.

One of the themes I miss is complexity - only questions 54 and 78 really touch upon that (while I'm not sure question 54 has the intention that I hope it has). The complexity of interactions in our interrelated decision systems becomes less and less understandable and controllable. And, while we head towards a future of scarce resource, the complexity of our economic system increases as well, with no signs that the financial sector actually added any value in the way. 

A.I. researchers should decide why they do things. If you built robots, is that really what humankind needs? And if so, is it likely that we can afford a robot for everyone in 15 years? Do we need smarter decisions for future actions or rather better explanations of why systems actually fail? If you study complexity, is Facebook really where our fate is decided?

Pythons collections framework has some nice classes that can be very helpful. I just used the formidable Counter class to check if I got a probability distribution conversion right.

I wanted to generate a random integer in the range of 4 to 8, given an existing value from a uniform distribution between 0 and 1. I came up with a simple way of doing that, but wanted to do a quick test if it actually does what I thought it would do. So I used the Counter class to do a quick test:

Looks like it does the job :)

I am a big believer in subscribing to websites via RSS. This may be one of those things which sounds like 'get off my lawn' to those who think 'news' is brought by social networks. However, I stand firm: It's a core idea of a modern internet that you make a choice what your news sources are going to be and automatically fetch them.

 I just spent a weekend in Paris, to attend the fourth European Scientific Python conference.

• A very nice and talented crowd of roughly 160 people. It was very well-organised, many thanks to the team who made it happen.
• Python has come a long way. I learned that Python detected the latest, scientifically sensational, Supernova explosion and will command an on-board camera in a robot on Mars in 2016.
• "Mr. ipython", Fernando Perez, gave an insightful keynote talk. He showcased a new kernel-clients model in the upcoming ipython 0.1.1. Not only can several clients work on the same ipython process, a client can now be anything ipython users ever dreamed of (or didn't even know they should be).  First, Fernando showed a console emulation window written in QT. It had nice syntax highlighting, tex support, actually working multi-line editing and inline plots. Pretty neat. Then he showed a broser implementation, merged last tuesday, which they call the ipython notebook. Basically, the ipython session becomes a document, which is editable inline and at all times and can contain many content types (he easily inserted images, videos, math and javascript). The whole book can be saved as json. Fernando closes with the sad fact that less than 30 people do 80% of the work in many python scientific computing libraries (scipy, matplotlib, numpy, etc).
• I presented my simulation framework Nicessa on a poster and decided to give a short lightning talk about this vision of independent layers which seem to evolve in this community (Nicessa can be the middle layer):
• On the train ride back, I happened to sit next to Ralf Gommers, one of the few major SciPy contributors, by coincidence. Pretty interesting, not only because I actually started using SciPy in a research project very recently.

I am sick today so I had time to watch two talks on why the interpretation of what humans (want to) thrive for is outdated and needs to change. Both are about 50 Minutes long, but have speakers of different age and background. Both can help in understanding this new idea of how mankind is interoperating, but both are also not a final answer  - they are descriptions of what is in the beginnings and may turn out to happen in this or a similar way. They are also not the only people who think about this theme, of course.

Hans-Peter Dürr (interview is in German) is an accomplished quantum physicist and explains how from that point of view, "Wirklichkeit" is a much better term than "reality". He then talks about how he fought in World War II, worked with Edward Teller and Werner Heisenberg and met Hannah Arendt, leading him to later engagements for peace, more sustainable communities and economies.

Jeremy Rifkin (talk is in english, with convenient subtitles), one generation younger, is someone who runs think tanks, advises the EU on energy planning and sells books. His latest theme is the "empathic civilisation", and here he is invited at Google to explain it and the challenge it faces during the coming energy crisis. He uses the occasion to tell Google what role he thinks they should be playing. He introduces the empathy-entropy paradox we need to break: As mankind has widened the circle of empathy, the energy footprint became worse and worse.

When we use a common good, we cause the most expense and anger when we all use it at the same time. An idea that is now being tested in several places is to convince a small percentage of people to deviate their usage of the good from this popular time points. It is generally agreed that in many cases,  a change in the behaviour of very few people can already relieve a system of much pressure.

The current consensus seems to be that the system operator should pay people for that. If someone actually has the flexibility to deviate, the opportunity to earn or save money might make him actually identify and use it.

I see this in electricity markets, where demand peaks can maybe avoided by convincing a couple of devices to stop operating for a while and also in traffic management: The city of Utrecht plans to pay a commuter €4 per workday if he doesn't use the highway A2. They will have to devise some solutions where they film the numberplates of passing cars, but building new streets might be much more expensive (not to mention how much trafic jams hurt the economy and the mental wellbeing of commuters).

This can be a very effective way towards more efficient usage of common goods - but there are hurdles like the increasing hunger for usage data that comes along with it. Not many people will like that and we will need to talk about this. The good news is that if the mathematicians are correct, not everyones flexibility is needed.

Update: The Netherlands now plan to tax highway usage for everyone via satellite by 2012 (like the Germans already do for trucks). This system is more flexible, but also harder to accept.

I have been making the optimisation of systems, based on local information, one of my specialities. Such systems are optimised in a decentralised manner (which says that control happens on local levels and decisions about that are made also locally, according to local information). As such they are resilient against the shortcomings and the failure of a central planning node. That's good for users of the system. It also sounds nice. But is it really nice, in daily perception? Let's look at two examples:

On dutch motorways, the control system sometimes imposes tempolimits (say, 70 km/h or 50 km/h) on parts of the roads in order to prevent traffic jams further down the road. So the system knows about congestion problems in the vicinity of you, and might slow you down so you do not make a traffic jam out of it.

Recently some scientists modelled the problematic public transit system in Mexico city. Though buses run according to a plan, they sometimes stay in the stations longer (e.g. when a lot of people have to get in) and so they built up irregularities over a day, which ends up in a lot of buses being in one place and none in most others (this problem even has a name: "platooning"). They concluded that buses should just leave after a short time and not let all attending passengers board. Those passengers left out should take the next bus and overall, in the long run, everyone is better off because the whole system will run smoothly.

All this is true, but from the local viewpoint of the user of such a system, it feels wrong. I cursed when I rode on the dutch motorways and had to slow down for no reason that I could immediately apprehend. And it will definitely suck when a bus driver just leaves with you still standing right in front of the bus stop. We would hate those bus drivers.

I can tell from my own experience in understanding such systems (while researching them) that it would be hard to make everyone understand the situation. On the one hand, it's based on a lot of information and that information is decentralised - it is not all in the same place as a local observer. On the other hand, our brains are also bad at processing such abstract stuff like the platooning problem.

What to do? Would humans be happier with problematic systems, simply because they would feel more in control? Or can we evolve a system thinking in our culture that appreciates such complex, decentralised solutions? Maybe it would help to put out as much information as possible about how these systems work so that everyone can look it up herself. Maybe we'll need to go the extra mile and also visualise them really well. We should have graphically appealing real-time overviews of traffic situations (already in the making), public transports, elevators, electricity grid congestion and so on - for everyone to see and to discuss.

But I also think that in the end, not every optimisation procedure can actually be accepted - it needs at least to be understandable to stand a chance.

Yesterday I was lucky enough to take part in the Seminar of Collective Decision-Making at the Hanse-Wissenschaftskolleg Delmenhorst. Interesting talks about current research, all of them involved socio-economic experiments with human subjects who got real money based on their behaviour. I'll try to briefly summarize all three talks here:


Manfred Milinski

A look at cooperation towards a common good and a stab at representational democracies. Subjects played the "climate game": Everyone has to invest in a common good, or all are at risk to lose all they have. Players start with 40 Euro, and can for 10 rounds invest 0, 2 or 4 Euros. If after 10 rounds less than 120 Euros have been invested in the common good, they all are at risk (here they tried 10%, 50% and 90%) to lose all they have left. I was late to this talk, but I heard that often the players didn't make it to invest 120 Euros, even in the 90% risk case (all of the rules were obvious to everyone).
In another scenario, 18 players formed 6 "countries" a 3 players. Each country elected a representative, based on the strategy (s)he proposed (via chat). This setting was played three times, so that countries held several elections. It turned out that this worked even worse. Representatives who worked towards the common good left their countries with less Euros left, so they were not re-elected. In the next round, representatives all paid too little towards the common good. Sad.
Afterwards, there was a lively discussion about the transferability of this experiment to the real world (someone called the discussion a "snake pit").


Bernhard Kittel
"Coordination and communication in multiparty elections with costly voting"

This research started with modeling a problem in voting theory, but ended with a look under the hood of collective decision making in human groups. In some elections with three candidates, the winner is not preferred by most voters, but the ones who oppose him just split their votes on the two other candidates (think Bush vs Gore and Nader in 2000). Those voters should have been more strategic. In addition, lots of voters don't show up.
In the experiment, voters (the subjects) were assigned payoffs for each candidate, modeling that they all had different preferences. All voters wanted either candidate A or B while they all despised candidate C. In addition, there were costs assigned to actually voting, so that some voters would decide to abstain.
Voters knew what the preference distribution was. The researchers added communication among the voters via a chat before they actually voted. This enabled the voters to coordinate their behaviours in a way that candidate C got elected less often and the voters maximised their individual payoffs.
What then is really interesting is that the chat logs contain the "black box of group decisions". The researchers plan to analyse them in order to find out more about the coordination process of humans. Results are to be expected in a couple of months, but they can already say that
  * the voters who organised most of the coordination got less personal payoff in the end
  * ca. 50% of the people simply stick to their candidate in all rounds, no matter what is being discussed
  * communication among all voters is needed for an optimal outcome
Very interesting. I think that if these chat logs are really a "black box of group decisions", then this data set should be opened for other researchers.


Judith Avrahami / Yaakov Kareev
"Do the weak stand a chance?"

These experiments concern situations were one player clearly has less resources than his opponent. What happens in terms of strategies?
In the "pebbles game", each player has 8 boxes. Player A and player B have 12 and 24 pebbles, respectively, which they can distribute among their 8 boxes. Then, one box of each player gets randomly chosen and who had more pebbles in his box wins. Player A, clearly being weaker, should leave some boxes empty so that he at least has some boxes with a good chance of winning. Expecting this, player B should also make his distribution of pebbles uneven (rather than putting 3 in each).
In essence, inequality in player strengths introduces variability into the strategy space on both sides.
The researchers than got further into the role of the evaluator: what difference does it make that only one box gets evaluated, rather than all? The hypothesis would be that adaptive agents are pushed into trying harder when they know that only some of their work will be evaluated but don't know which in advance. They ran an experiment in which subjects solved addition problems on 6 pages. When the knew that they would only be evaluated according to one page, performance rose.
This managing style got invented to save lazy evaluators time, but it might actually raise performance. I wonder then, if subjects who knew that they were weak in adding numbers also left some pages out to concentrate on the others.

When I run computer simulations, I have to have a solution for the same set of technical tasks each time:

• How to combine variable settings in experiments
• How to store log files nicely
• How to plot nice graphs from those log files
• How to run these expensive computations on remote servers (e.g. university servers)

Now I have one solution for all of this and I am very happy with it:


The above bundle of tasks is universal to a lot of scientists that need to to run computational experiments. I myself will run into this over and over again.

It is a natural reflex of a software developer to build a good tool for this over time and this is what I did. While working on several projects during my Masters, the latest of which is my thesis, I developed scripts for all of these tasks and bundled them together so that you could now call it an application: Combex (Combinatorial Experimentor).

It has turned out to be very useful to me lately and I would like to share this tool with anyone who is interested (this is its home). There are a lot of things that could be even nicer (I already maintain a ticket list), so I welcome contributions.

Note that Combex lets you program whatever you want in whatever language you want, all it wants is that you write log files.

I will let the (sparse) documentation speak for itself and just throw in another screenshot which shows how it all nicely comes together: A (dummy) experiment gets chopped into several tasks and those are shipped to remote servers. I can nicely check if they are done. If so, I have Combex get the data and generate nice plots.

P.S. To talk about our process and find general, reproducible solutions seems to be a general trend in science, see e.g. myexperiment.org.

P.P.S. I am unaware of any other software that offers this task bundle, even if its commercial. Anyone knows software like that? I only found quite specialised approaches, but what I like about Combex is that it doesn't care what the hell your code is doing as long as you configure variables and log data. It is more of a very simple workflow with nice tools along the way. In principle, a lot of other software (say, statistical processing) could be hooked into this as needed.

P.P.S. I am still open to be convinced by a better name for this.

P.P.P.S. It has now changed name (it also evolved a lot) and lives here.

I recently accepted a new job. From October 2009 on, I'll be a junior researcher at the CWI (Centrum Wiskunde en Informatica), a national research center here in Amsterdam. I'm very happy to be working with Prof. Han La Poutre.

I will actually be a Phd student but do research in a predefined context - nowadays, a lot of Phd positions in the exact sciences are a mixture of research work and research exploration. An exciting part about this project is that it is about a very real challenge and there are many stakeholders involved whose views on the problem are important. I will do fundamental research on dynamic and adaptive multi-agent systems, but I will also be busy wearing the hats of different stakeholders and try to bring their view into the model.

[image via http://www.usgbc-centraltexas.org]

The project I'll be working on is called IDeaNed (Intelligent en Decentraal Management van Netwerken en Data, only dutch description so far). It deals with one of the big challenges we face in the next years - a redesign of our energy distribution networks.

As we begin to exit the age of fossil energy, energy will soon become a problem for us, not a cheap and abundant catalysator for progress. Now, as an AI researcher, I can't help out where it is most important - say, actually invent an effective renewable energy source or useful, longlasting batteries. But what we need for sure is a new energy infrastructure. There is already a term for this - the "Smart Grid"*.

Our existing energy networks are of an old, centralised design which is not suitable for the way we need to look at interconnected things. As the report "Grid 2.0" (PDF) puts it:

"It is hard to make the link between flicking a switch and the distant power station that made it possible to turn the light on.
(...)
Partly as a result of this lack of a feedback mechanism, and partly because of technological constraints, Grid 1.0 is surprisingly inefficient. Only around 40 per cent of primary energy input (coal or gas) used in power stations is converted into usable electricity, the rest is wasted heat. A further nine per cent is lost as the power moves through the transmission and distribution system. Then a further third is lost in our homes and offices because they are poorly insulated, not designed with energy in mind, and inhabited by people who do not see themselves as players in the energy game."

We need a network that is decentralised (can work with input from several local sources, not only big central plants, can communicate locally about sharing loads) and avoids efficieny problems in peak times. Such a net needs real-time price mechanisms and needs to accomodate a lot of players: customers want to use effectively, producers want to sell efficiently, governments want to distribute evenly **. Meanwhile, there is a real, non-abstract component: the network. Voltage capacities at different parts of different sub-networks dictate what is possible and what is expensive to do. A lot of these things change all the time. This can get very complex very fast.

What we'll be doing is modeling Multi-Agent systems in order to learn what good price mechanisms are and what good automisationable strategies of the local players could be. We will get input from another Phd student from Eindhoven supplying technical findings about the infrastructure and we'll work with companies in the dutch energy market (big players and consultancy agencies that  develop energy network simulation software). This highly integrated approach of designing scientific projects is a unique dutch approach and I am quite excited about it.

This topic is not only being picked up in the Netherlands. Big companies like GE or IBM are already promoting their competence in this topic which isn't even entirely understood yet.

They smell money in creating a market better targeted at our actual energy usage and in savings due to efficiency. This might be one of the rare cases where what they want and what society needs have a significant overlap. For instance, I recently learned that energy efficiency on the last mile is multiple times more effective than energy efficiency at creation time (due to all the energy losses by conversion or distance that already accumulate until the last mile). And it is easier to do.


* There might even emerge a bubble with all the money being thrown at this topic right now by governments, but I hope that in 4.5 years, when I finish this project, things will have come to terms, the crooks took their money and left or were thrown out and we know where to go.

** Especially when there is not enough. In a post-fossil world there may be "bad weeks" with few energy available. Or, in more grim scenarios, we'll have few energy at all times and almost none in "bad weeks". Making sure distribution can be fair is crucial and not as easy as it first sounds.

I am reading reddit.com for the interesting links, but also for interesting conversations in the comments (I still have to learn to skim over the trolls, though). A special kind of conversations came up recently. People would claim that they are interesting or different in some way and invite peoples questions.

I remember that it started with a guy saying he is hetero, but works at a gay sex phone line to support his studies. If anyone wanted to know anything about it? People wanted. Some girls said she has epilepsy. Any questions? Sure.

Then, someone had the idea to make an own subreddit for these kinds of conversations (a reddit-style forum). It's called I am a .... Currently, it's pretty lively. Some people can be asked about being french or from Afghanistan, others have strange jobs like Lobbyists or are illegal Immigrants.

Every scientist needs to have a collection of papers (s)he reads and might use for reference. For the last research projects, I used a desktop program called JabRef that was decent. Now, I switched to something really promising.

Mendeley is a startup that wants to do with research papers what last.fm does with music: Make it easy and fun to find some that you don't know yet but would probably like. This goal is really, really mouth-watering, since the amount of papers out there seems to grow exponentially. Today, there is no other way of knowing if someone else already did what you want to do by following references from papers and maybe keyword search on Google Scholar. It's a growing concern for researchers.

They want scientists to have a profile on their site and fill a giant pool of data by citing their research interests, uploading and tagging a lot of papers and maybe build social connections. Then, recommendation becomes possible.

Of course, they'd have the hen-and-egg problem every social community project has. Value can only be created when people are there in big numbers, and people only come when value is already there. This is why the Mendeley people decided to start with solving some other problems scientists have, so that users have a reason to come:

• They built a really slick desktop client to organize papers. It runs on every OS, does full-text search and extracts meta data from PDF automatically if you want. I think it's already better than JabRef.
• The client also syncs automatically with your web portfolio. You can have your library with you wherever you want.
• You can open a research project and share papers only within that research group.
• You can always import and export your library (for instance to Bibtex).

They said recently that users have uploaded one million papers already. That's a lot of potential for data mining right there. And did I mention that they have a Last.fm investor on their board?

I just watched the first part of "The Trap: What Happened to Our Dream of Freedom?" by Adam Curtis. He claims that our basic notion of human behaviour has been crooked ever since the cold war, leading to inhumane psychology and selfish politics.

His main starting point is that in the cold war, the two big military forces faced the double contingency problem of how the other party might think of what they were thinking of them themselves (and so on) - all in the realm of nuclear destruction. The USA threw a lot of scientists at the problem and they invented Game Theory. This concept, in which people are regarded as only selfish and numbers can be put on behaviour, got picked up by psychologists, economists and politicians, slowly taking over the way society looks at human nature.

I don't disagree fundamentally with the basic historical notion here: In the 50s and 60s, Game Theory still had a rather simplistic view on human behaviour, portraying humans as only self-interested. Later, western societies went through a lot of change but left the discussion what constitutes freedom in the realm of rationalism. I hope we're making some progress to develop this idea of what makes us happy and free, but this discussion has been stuck for some years now. In the meantime, societies changed a lot, sometimes built on a much too strong view of humans as being rational. It makes sense to discuss what went wrong because of this.
I agree with that, but I think, Curtis overshoots with this movie. Here are some points of criticism:

No History context
For starters, Curtis bends history so that it fits his story. Game Theory wasn't invented during the cold war, but already in the 1930s. The view that humans are rational beings is also much older.
More on context: Curtis recognizes that western societies needed to change in the 50s, 60s and 70s. Psychology until then was really, really inhumane, Families were often little dictatorships and government bureaucracies (in his movie the British) desperately needed reform. Curtis never addresses the view on human behaviour that was in place until then (I think it was close to the view that you can make people do whatever you tell them to).

But any new concept should be explained in the light of the concepts it was made to replace. What was the general idea that the rational model replaced? Were there other good solutions on the table at the time than to try to view people as rational? Maybe it wasn't only scientists who placed this concept in the mind of society. Maybe it was time to look at people that way and maybe this was already much better than the view before.

Crazy Scientists
Curtis portaits proclaimers of Game Theory ideas (in which people are only selfish) as crazy and old. That is necessary, because today, everyone younger than 70 who works Game Theory wouldn't look at things in this one-headed way. For instance, when using the Prisoners Dilemma, the only modern models I have seen ask the question: In what settings does cooperation emerge? (Axelrod first made this new notion public 29 years ago). It's always some crazy scientists misleading everyone else. For example: Buchanan, an economist, is guilty for Thatchers politics because she invited him to talk once.

I understand that you can't show all context when you shoot a documentary, but Curtis is destined to blame a dozen people for all that went wrong regardless of what was there before, and that smells of conspiracy nut.

Causality
He claims causal links that I can't follow. For instance, here is the gist of 10 minutes of the movie: The psychologist Laing critized old-school Psychology in America  (somehow, hew was of course inspired by Game Theory in the beginning of his work). As a consequence, American Psychology turned to using automated, oversimplistic questionaires and tested a lot of people for mental problems. Then, it turned out that every second American has some history of mental problems. As a consequence, Americans were oversensitive for the idea of what "normal" is and since then ask their Analysts to turn them into this new strange notion of normality. That is one hell of a causal chain, proving that Americans running to Analysts is also a consequence of Game Theory.

Here is my theory: Society is a complicated organism. Sadly, things take time. Good ideas take decades to develop into mature concepts that everyone has understood.  And it seems to be a pattern that they  cause a lot of damage when people carry early versions of them into the real world. See Game Theory or also the influence on early physics ideas on economics. That doesn't mean you can't make the theories better, like it happened to Physics and I believe, also Game Theory. Of course, if certain people already are happy with the dangerously simple ideas and cause damage, we sometimes have to wait until they are somehow out of power. They say that old ideas are only gone when all of their proponents are dead.

But enough of that - back to Curtis. Sometimes, I got the feeling that he really agitates against using numbers for anything that could describe human behaviour. Fine, that is something to discuss, but then he made the wrong movie.

P.S. This critique makes some of the points I made more clearly.

I am currently reading The Origin Of Wealth - a book which tries to explain in what deep explanatory troubles classical equilibrium economics have gotten into during the last two decades.

One of the main messages is that economic systems are no closed systems that could theoretically reach an equilibrium - they are highly dynamic and interactions are so complex that they will only -suddenly- reach an equilibrium when all involved players are dead.

This simple drawing I made should resemble some of the most basic physical classification of systems and where economic systems belong. The author says that classical economics would want to place an economy in the right branch and therefore never have a model close to reality.

After economics borrowed the notion of an equilibrium from physics (roughly 100 years ago), physics moved on and discovered entropy and the second law of thermodynamics. Chaos and Complexity have now been discussed fundamentally by almost all basic sciences, but seldom in economics.

Later on, the book discusses that in an open system like an economy, the creation of (temporary) order is what we call "wealth creation" and that this happens by evolution-like processes (the best system/solution/product replaces others):

I am interested to see how the author defines a "complex adaptive system" (which is his own term) later on...

My last post concerning cooperation  was not about any research that I would personally do, but highlighted the best and most useful results concerning the old question why there is cooperation that I have come across. I am studying Artificial Intelligence (AI). Today, I want to put on the shoes of an AI researcher trying to tell other researchers why research in cooperation is a good idea.

Cooperation as an AI topic
A natural question is: Why should someone in AI spent precious research money on cooperation? After all, to explain why there is cooperation is generally a domain of the sociologists and biologists, maybe economists. AI is based on Computer Science and while it surely should try out inspirations from other disciplines, its main purpose is still to build things that work in a new way (initial goals of building something entirely new have been refined). More and more (due to a lot of fruitless approaches and now also due to the economy), I hear the question why any approach would be useful to pay for. What can the new thing do or show that lets people do things better (for instance more efficient) than before?

I think that cooperation is a fruitful theme in this context and want to explain why.

Autonomous agents
An important goal for the future are intelligent agents that do tasks on behalf of us. We don't want to tell them too exactly what to do (it's work and we might give bad instructions) and want them to interact with each other in the world. This is why they need to act autonomous. They also need to be reactive in an unpredictable environment which for them mostly consists of the actions of other agents.
My simple point is that the notion of cooperation is a good tool to model this. First, actions of other agents can mean a lot of things to me. But if I was pressed to put it into really simple terms, I could label those actions as being good (cooperative) or bad (defective) for me. It's a simplification of the world, sure. But we have to start somehow*. With a modeling tool like the Prisoners Dilemma I can already model that agents are autonomous and depend on what other agents are doing. That's already some modeling effort covered, even in a way that researchers agreed upon long ago to be a standard method. I can still play around with some settings though, like the utility values or the number of involved agents per interaction.


Efficient Systems
When I say said I model cooperation, I mostly get looks that imply I'm being labeled a "Hippie". But in reality, cooperation means efficiency. Cooperation makes sense if the outcome of it is superadditive. This means that the utility produced together is more than just the sum of the utilities the agents would have produced alone **. It is also safe to assume that when one agent defects the other, he takes home a lot more utility, but the overall utility is still less than if both had cooperated. So for the system performance, it would be great if agents decided to cooperate often. This should be sold as a hard fact more often: Cooperation makes systems of autonomous agents efficient. It makes sense to do research with this goal in mind.
One thing about complexity and superadditivity: Not all interactions are superadditive, of course. But I think that when the behaviours of agents become more advanced and complex, their interactions in multiagent systems will be superadditive more often (since superadditivy often arises when noone is an expert for everything).


Multiagent architecture - Cooperation built-in?
Researchers come up with design guidelines for multiagent systems quite often. That cooperation is an essential design guideline for decentral systems with autonomous agents is sometimes already part of this. Take for instance the AMAS architecture. There is a subheadline called "Self-organisation by co-operation". They assume that each agent always tries coopreation and thus the system becomes efficient. I think that is a little simple. Take humans - for us cooperation is natural and feels right. But we don't have to cooperate. In fact, we often don't. If there are agents in the system that defect, then let that happen. Work around them, if you can. Defect them back if you deal with them or maybe see if they change behaviour.
Multiagent systems can - like nature - be heterogeneous and then it doesn't make sense to assume some behaviour for all agents.

Outlook
Cooperation is one way to start modeling complex interactions. There are simple models to use that everybody understand and we can agree that cooperation makes systems efficient. However, it is important to note how we mostly talk about the question if an agent wants to cooperate with another. Much more complicated is the how later on.
How do two agents cooperate once they both try? Can we make any general models for this at all? There is so much context involved and so much circular dependencies, so much source for uncertainty. I hope we can find a simple model for this that can be as usable as the Prisoners Dilemma.

* And we have to talk about it. To communicate about science is really important and to use simple and accepted models helps big time in this.
** You can nicely model such a situation with the Prisoners Dilemma.

I got my new MacBook some days ago and am very happy. Especially having a built-in webcam feels very much like finally being in 2009. Visiting my friend Marcel in Osnabrück, I tried out Photobooth, a nice app to make pics with the webcam. It's great fun, not only for kids:

Here are our best shots :)

I have not found time to develop my approach to a next-generation CAPTCHA any further (here is my original outline of the idea from last year). I still think that a collaborative process of creating and solving interesting and/or creative riddles is a really good idea, so I want to at least put this idea out there. Here is the presentation I developed for it together with Kathrin:

Also, I had started a website for this project before I ran out of time. Here are some blog posts.

Update 10.03.09: The editors at slideshare.net featured this presentation on their start page. Thanks! Btw, this list of featured presentations is a great place to shop around for interesting  and well-digestible concepts.

Here is a result from the group project.

To summarize shortly, the job description was to take an emergent system (where the exact outcome can't be controlled for in advance) and inject some agents that prevent some behaviour from happening. This could for instance be an effect you as a system designer don't want while you still want to allow the system to freely find other solutions.

In this little animation you can see the first proof of concept in a Particle Swarm Optimization. In the middle is a local optimum (darker background is optimal) and the grey agents try to coordinate in luring normal (red) agents to the hard-to-find global optimum in the upper left corner. Everything still happens decentralised.

It was fun to put it together in roughly two days, but now the tricky parts would begin:

• This example with only two control agents worked well, but it all depends on the settings: What are good parameters to adjust the control agents (e.g. the ratio of control agents vs normal agents, what is k in the k-nearest neighbour approach, why do sometimes equilibria exist that seem hard to explain right now?)
• In what direction should research in controlling emergence generally go? Martin Middendorfs initial approach [1] is interesting, but also just playing with the idea.

Update: Jeff Vail has some thoughts on "Guided Emergence" in Biology, the War on Terrorism and the Military.

[1] D. Merkle, M. Middendorf, A. Scheidler. Swarm Controlled Emergence - Designing an Anti-Clustering Ant System. Proc. IEEE Swarm Intelligence Symposium, 8 pp

I'll do a three-piece blog series about cooperation - well, at least about some basic terms I've been thinking about, in order to clarify them for myself. This first piece will deal with cooperation as a research objective. Later, I will argue why I think cooperation is a formidable objective for Artificial Intelligence research and why it's a good idea to study network structures along with it.

Basic Definition
To cooperate basically means to do something together. The research I deal with is especially interested in situations where altruism is needed for cooperation, i.e. you have some initial costs if you cooperate. Then, the question the cooperator can ask himself is "Will I be repaid?".

The Dilemma
In many situations in life, you will be repaid. But if you want to be rational about it, there is always some uncertainty. Moreover, cooperation may or may not have some overall benefit for you after you've been repaid, but if you cooperate and get screwed over (not cooperating is called "defecting"), you may lose your whole investment.  So there is unbalanced risk, favoring defection. The uncertainty about this is higher if you know less about the situation you're in.
The dilemma is as follows: If you don't plan ahead (maybe due to uncertainty), defecting is always the best option. If at all, cooperation only repays in the long run and if you don't get defected too often.

We all know that cooperation happens every day, even with big uncertainty, in humans as well as in almost every other life form imaginable. It has been proven that humans are even hardwired to cooperate, for instance via the oxytocin hormone (see for instance this book by Joachim Bauer) *. The question is how it came to be.

The Prisoner Dilemma
A really nice way of putting this dilemma into numbers is the Prisoners Dilemma. I'm not going to reiterate the basic "prisoner" setup (which was just a story to make the dilemma clear). If you look at the payoff matrix below for a while, you'll notice how the numbers express the dilemma: to defect will not hurt, but might payoff big time - cooperating will not yield that much, but may hurt dramatically.

Why is it nice to have this dilemma formalized so simple? Now you can setup different worlds, simulate them or prove mathematically that a certain setup is good for cooperation or not. It's a great tool. I'll talk more about this in the next post on Cooperation in AI research.

To finish this, I want to highlight some approaches to explain why systems have cooperation. It's amazing how long it takes to come to reasonable theories for this:

Survival of the fittest (Spencer, 1864)
The survival of the fittest is a dangerously extreme notion of individual success. This notion would only opt for the short-term notion of the cooperation dilemma (saying that defection is your best option, always), and is therefore stupid. It has been attached to Darwins ideas of evolution for a long time and to explain cooperation it is often changed to somewhat more meaningful concepts:
 

• Kinship selection - A very popular concept among scientists is that you're more likely to cooperate the more related you are to your opponent genetically. This notion is carried by the belief that genes have been favoured in evolution that make their carrier do beneficial stuff for similar copies of them (i.e. for related carriers), where you are related 1/2 to each parent, 1/4 to a sibling and so on. They even try to get these numbers to show up in psychological results (it gets problematic right there).
• Group Selection - For cooperation outside of kinship, people just bend the survival-of-the-fittest metaphor to several levels and say that there is selection pressure on whole groups and if only its members cooperate, the group is stronger than other groups. You can find proponents for this from Kropotkin to Hitler.

Both of these subtheories make some sense in specific situations. If I ever happen to die in a fight to the death, then certainly the survival-of-the-fittest approach would be suited best to explain why I didn't survive. But none of these approaches is in any way general. There is certainly cooperation without kinship (called "reciprocal altruism"), and when everyone is connected to everyone, how do you define a group?

Systemic approach
There is a need for approaches that approach conditions for cooperation more systematically. For instance, one very important property of a cooperative system is that altruistic acts are superadditive (meaning that such an act generates more utility than if the two participants had just acted alone - the utility can still be shared unequally). When you look at cooperation in systems, you are more interested in the behaviours of agents than their interiors. You care more for the dynamics of all interaction patterns than if A would beat B in a duel. This is an approach we need while we realize how complex all our networks are.

I found a promising model by Fletcher and Doebeli (2006) [1], who connect Hamilton's rule with results from D.C. Queller (which are from 1985!!). While Hamilton's rule explains in simple terms that cooperation works well if the cooperators are related on the genotype, the rule can be generalized to the relation among phentotypes. In other words, systems that have some properties that support cooperation, will have cooperation. It matters that altruists benefit each other. I quote from Fletcher and Doebelis conclusion:
 
"What this rule requires is that those carrying the altruistic genotype receive direct benefits from the phenotype (behaviors) of others (adjusted by any nonadditive effects) that on average exceed the direct costs of their own behaviors. Kinship interactions or conditional iterated behaviors are merely two of many possible ways of satisfying this fundamental condition for altruism to evolve."

I hope I have motivated how research generally deals with cooperation, or at least what tools I think are appropriate. The next post in this short series places cooperation in the context of AI research, which mostly should answer the question why anyone would want to build cooperative systems (until now, I was talking about explaining them).


[1] J.A. Fletcher & M. Doebeli, Unifying the theories of inclusive fitness and reciprocal altruism, The American Naturalist, 2006

* Of course, too few cooperation also happens. The Tragedy Of The Commons models situations in which agents use up a depletable common good (for instance a water well), thinking only in short terms.

During the talk of Giovanna Di Marzo Serugendo I learned a new term: Stigmergy.

It stems from biology (from 1959, actually) and describes self-organizing systems in which the next actions are determined by the state of the environment. This way, agents don't even need to have a memory or communicate. They leave their environment in some state, and whoever wants to do further work there knows how to go on.

There are to ways to do this:

1. Leave a marker, for example the pheromone traces of ants carrying information on where to go.
2. Leave the work in a state. The wasps, for example, build hives in hexagons. Whatever the actual state of the hive is, it is obviously defined by some simple rules which every wasp knows where to build the next hexagon.

Systems like this have a property that I think I remember from autopoietic systems: The single actors are not needed for the system to survive (since their memory or their communication holds no existential information).

I noticed in a discussion with Gabriel yesterday that this is a vision of professional programmer teams:

In programming, the number of hidden assumtions rises all the time and code that isn't reviewed to be readable most likely does what it should, but it becomes more and more unclear for other humans what the code intends to do as it grows. The current mantra is top let the code be so clean, documented and self-describing that any developer can quit the team without taking the whole project down with him. This 'clean-code' mentality requires a lot of discipline by developers and adherence to standards.

These standards develop during discussions in the programming community. The tendency to demanding stable systems makes the individual programmer less important. And they help making this possible by themselves. Fascinating.

Anders Johansson gave a great talk here at Decoi 2009 about the work Dirk Helbig directs (he is currently in Zürich - here is a 3Sat video of a german interview) concerning the simulation of pedestrian crowds. This research has over some years evolved to a rich set of tools and he was able to entertain us with nice 3D-videos of their simulations. I will shortly highlight the main topics he addressed.

The social force model
Their model is based on a swarm algorithm: Agents (the pedestrians) follow their own goal, but are influenced by others (others can be other agents or walls). They want to be close to others, but not too close (this is called "repulsion"). Then, they added to this proven local algorithm what they found useful. For instance, agents have individual traits like acceleration (how fast they can be and how fast they reach this best tempo).
You can also describe the external forces influencing an agent as physical (strong, but short-lived) and social (not so strong, but affect the agent longer).
By illustrating each step in the model building with a small 3D video of people approaching each other, we really could watch the model becoming quite realistic.

Real-world data
A lot of the work has been done in extracting real-worlf behavior from videos. They filmed people moving through metro stations and shopping malls. It is a quite demanding task to extract all individual pathways from the video, but they have a good algorithm now to do it. Then, they can replace one agent in the extracted data with one simulated agent (who works according to their model) and find out how good the model predicts what a real human does. Do this a lot for many combinations of people and adjust your parameters a lot, and you can make your model better.
It should be noted that of course the video can't tell which intentions humans had - if someone remembered he forgot something, he'll turn around. Also, the real humans had a high variation in their behaviour.

Evolution
Some work has been done to evolve an agent strategy via a 'blind' evolution algorithm that just tried to evolve a model that predicts human behavior very well (you notive that this is a bidy of scientific work spanning years).

Macro Level
Now, when you look at groups of pedestrians from a macro level, you can describe crowds in several ways:

• when groups of people have contradicting targets, they tend to form lanes (at least this happens in Europe). If the streams of people hit each other diagonally, the form stripes (this looks fascinating).
• When the space which pedestrians move through gets more crowded, the mass of people  moves through different stages: First it tends to progress in Stop-And-Go Movements. When it gets even more crowded, turbulences occur in which most people just get pushed around slowly in random directions. Interestingly, some simple models had predicted that crowds at some point will just stop moving, but that actually never happens.

Real stampedes
The research group also studied real mass accidents that happen in night clubs or football stadiums around the world. In fact, Anders just arrived from Saudi-Arabia, where Scientists study the mass accidents that regularly happen during the Hajj in Mekka. We got introduced to the terrain and special problems of this occasion (for instance every single of this 3 million people needs to do the exact same thing at the exact same place). We saw some stunning videos from 2006, when they started to film the crowds (luckily, we didn't saw the big accident of 2006 itself). for the next Hajj, the organisators took several measures like defining routs in which to go (slowing down traffic and leaving areas free for emergency support), building important bottlenecks over several stories and simply registering a considerable amount of visitors to be able to spread them over the week.

Accident prediction
A nice feature of a model would now be to predict an accident from such a video. They found that a measure called "gas-kinetic" works best for them. This indicates the crowd density and the variation in velocity. When both are high, an accident becomes more likely. However, they are hard to predict. In almost well-known examples, something innocent triggered the mass panic (like a fight between two women in a Chicago night club or the rumor about a suicide bomber in Karbala, Iran).

I am currently attending the DECOI 2009 workshop (Third International School of Design of Collective Intelligence) in Leiden. It has very interesting speakers (I hope I manage to summarize some things later) and attending people.

My work group will play around with the idea of controlling emergence (meaning that you might be able to change the mix of your system design on-the-fly in order to prevent certain behaviours of the system that you do not want to happen).

My first positive impression is the location: the Lorentz Center in Leiden is an institution solely in place to let scientists organize efficient and rewarding meetings like this. It's government-funded and professionally run. Attendants get keys to offices (we're 5 in one office) and the coffee machines grind the beans freshly while you wait. There is free Wi-Fi and food.

There is no way to measure directly if this government money is well spent. We don't publish anything here. But any scientist will tell you that exchange of ideas among scientists is one of the most important tasks on science. Organizing such meetings, though, is hard work and keeps scientists from doing actual science. Kudos to the dutch government for addressing this problem. Good policy.

[from here]

1. A man ("TN") suffers two strokes and says he's blind. Standard tests confirm it.
2. He still reacts to someone smiling at him. Researchers are thrilled to find out that his emotional processing center -the amygdala- seems to receive information.
3. Researchers build him an obstacle parcours to walk through. He is able to do it. He sees, but only subconscious parts of his brain still process the visual information.
4. They are excited because now they will be able to study how far our subconscious processing goes, in isolation. At least for vision, that is.

I am having a rough semester, group-wise. I think that group work at universities is still pretty immature.

Here at the Vrije Universiteit (like in many universities these days), group work is an important concept. To put students in groups saves the lecturer the hassle of evaluating 30 projects. Instead, (s)he evaluates 10 projects. Then, projects can be more ambiguous. Of course, group work also prepares students for the complex work life, where nowadays collaboration is an important ... and so on.

My point today is that group work also introduces new problems, problems that are not properly dealt with. Most of the times, a group is assembled and you have to work together with some guys you never met before. Yes, this is where the soft skills get developed. But what if one or more group members are clueless and/or lazy? The last thing is often worse and it happened to me in almost all courses this semester. I worked really hard, while others profited and got the mediocre grades that I almost single-handedly achieved. Meanwhile, I couldn't focus on other stuff like exams and also got mediocre grades there. I am pissed, mostly because people can behave like dicks right in front of me and get away with it.

Of course, this also happens in the real world. In fact, I know that it happens all the time. But in the real world, there is often something you can do. You can leave and add your work force to a better group. You can fire someone. People can get different payments because their contribution to the project is different. In the real world, there are potential drawbacks for slackers. Currently, in most courses at universities, there is none. You have to stay in your group. Everyone gets the same grade.

What I am saying is: if you create group work, fine. But if you let the work of individuals be invisible, you create incentives to cheat. If you grade everyone the same, you show that underperforming pays off. If you don't allow people to regroup, you are a Stalinist.

A group needs to be able to react to conflicts in a way that matters.

There are so many tools out there that make online collaboration trackeable. Tell students to use them and monitor them in case of conflicts. Make conflicts visible. Introduce a sensible rating among group members and act if there are disparities. Make it possible for members to leave a group. There is so much to do that would raise the quality of work and the motivation of students that are not trying to get through on the back of others.

Update 12.01.09: In one of the project, one that still goes on, I decided to talk to the supervisors. One normally doesn't want to do this, because it feels like telling on your colleagues. But by this time, I had become so angry *, that I didn't consider my group members colleagues anymore. I have to say that when the supervisors are really monitoring group work (in this case by group meetings and presentations), then they can and sometimes will react properly. In this case, they had also suspected what I was describing. After they questioned the rest of my group about their subject knowledge, they decided to split the group. Maybe that is better for everyone. The supervisors really took time to resolve this and had indeed prior knowledge, albeit coarse, about individual work. If they do good work like this, I do think that supervisors should take a minute at the beginning of a course to mention that they will also keep an eye on individual performance (and there might very well be differing grades) and will react to problems in groups (and not just the "Hippie-way"). This helps the incentive.

By the way, this was in a group of three (where they normally preferred a size of two). Group size is also very important. A group shouldn't be too big. I had one course this semester in a group of five and that just spells disaster in this setting.

* I was angry when I wrote this rant, in fact - so I now reformulated two or three adjectives in the text.

In recent years, mind-doping has moved from science fiction to commonplace, at least that's what they tell us about US universities. Here is a recent article from the german "Die Zeit" and it is also a scenario discussed in the book "Radical Evolution". Students take cognitive-enhancing drugs like Ritalin (there are many more, it is a hot market) to get ahead of competition during exams. US researchers are now demanding to talk openly about it, and are provocatively proposing to give all students access to such drugs, for equality. Neuro-enhancement will come, the only question is when, how and of course the price.

This is scary, not just because it feels not right to a lot of people. It also says that there will be a more direct mean to turn money into success. If you are rich, you can afford the best drugs to make you more able to perform, to concentrate on only one thing, and so on.

But maybe, hopefully, this is not the only road this can go down. Paul Graham recently talked about why he thinks a successful society relies less on short-term evaluations like exams and more on actual, long-term successes like finishing a project at work or founding a startup. A society should define its success in keeping direct influence from money to success down. He sees a difference in the US a couple decades ago to the US now - money hogs like elite universities and big corporations have become a little less relevant (meaning: they don't hold the monopoly on the road to success anymore) *.

There are some drugs that might translate into medium-term success - for instance, Provigil lets you depend less on sleep and is taken by military pilots. But for these things I see a reasonable middle ground. People who overdose will not have long-term success. It's just like workaholics tend to break down after some time.

I hope that the trend Paul describes is real and will hold. Like all effects we have on the world should be valued more by their sustainability, we also need to regard human work success under the view of sustainability. I don't see a drug at the horizon that not just makes you a better performer, but more "intelligent". For me, intelligence is a long-term concept.

* Of course Paul promotes startups as the new thing in the rest of this article. He is advertising his startup seed company. But let's not bash him for that right now. I like to think of "startup" as a broad term, and be less enthusiastic about them how they are today and then Paul actually sounds reasonable most of the time.

Spoiler: nasty programming problem ahead.

I am currently developing on a Plone3 website. Plone and its base, Zope, have a lot of concepts from the programming world, layers of abstractions if you will. A layer of abstraction is designed to make your life as a programmer easier, but only if you understand that it's there of course.

Example:

I was developing an aspect of certain types in our project, namely that they can be bookmarked. With Zope(3), you can write an adapter. This class does nothing but add specific behaviour to another object. Now I can have a lot of different bookmarkable types, without changing all their classes in the same way (and no, inheritance is not an answer for everything). All I need to do is adapt them via an interface when I want to bookmark them, like this:

bookmarkable = IBookmarkable(context)

My adapter object will make sure that the adapted object has an 'bookmarked' attribute, a boolean:

def __init__(self, context):
     self.context.bookmarked = False

But oh! Everytime I'd adapt some object via IBookmarkable to work on its bookmarked attribute, a new adapter is created (via __init__()). So each time I adapt, I set the bookmarked attribute on False. So let's change that to:

def __init__(self, context):
     if not hasattr(self.context, 'bookmarked'):
         self.context.bookmarked = False

Now I was happy. But later, my unit tests indicated to me that whenever I bookmarked a folder object, the bookmarked attribute would in the same way be triggered for all bookmarkable objects contained in the folder!

After a while, I found that the code that checked for the bookmarked attribute triggered Zopes implicit acquisition. The acquisition mechanism uses attributes from objects higher up in the containment hierarchy when the object itself doesn't have it. So in the code above, I check for the attribute, thereby (through implicit acquisition) setting it to be the one of the containing folder. When I then later boomark the folder, I also bookmark the contained object, since they use the same boolean object. To prevent this, here is the solution:

def __init__(self, context):
     if not hasattr(self.context.aq_explicit, 'bookmarked'):
        self.context.bookmarked = False

And I was so close to bother the Zope mailing list - Now I am a bit proud to have figured the abstraction layers out myself :)

Helping your fellow citizens is often a little different over here in Amsterdam.

I live on top of a coffee shop. It's nothing more than a take-away. Get in, buy weed from a little window, get out.

1.

A young man approached me when I wanted to unlock my door. He gave me 5 Euros and asked if I would buy him weed (because he isn't 18 yet). I said yes.

I stepped inside, went to the counter and said "Weed for 5.". The guy placed three little bags on the counter and I took them. Turns out this is wrong. I should've chosen one of them.

I: "Oops, this is my first time."

He: "Did someone send you?"

I: "No, no, I just moved in..."

2.

The next day, an old woman in a wheelchair waited in fornt of the coffeeshop and kept knocking the door. "Mag ik u helpen?" I asked. I stepped inside (there is a small stairway in the entrance) and told the guy: "You have a customer here."

Whereas in other countries you help old ladies across the street, here you help them buy weed. Good times ...

Dr. Moira Gunn interviews Keith Devlin, author of "The Unfinished Game" (22 minutes).

He talks about letters that two mathematicians -- Pascal and Fermat -- exchanged in the 17th century. They pondered over a really simple gambling problem: The unfinished game.

To describe uncertain future outcomes in numbers was Pascals simple answer - and it is the foundation of probability theory. From that followed the modern finance and insurance systems we see everywhere.

The interesting thing is that Fermat quickly came up with a simple solution that today everyone will understand. It's teached in 6th grade. But Pascal, one of the best mathematicians that ever lived, didn't get it.  Putting numbers on future events was a new kind of thinking. Framed like this, it's a powerful lecture about how culture changes thinking over short time spans.

In this lecture (video below) from January 31st, 2008, Lessig sums up his work over the last years that lead him to create the Creative Commons licence and start a grassroot movement against lobbyism.

You'll watch one of the best presentations I have seen, speech-wise and slide-wise. You'll learn how and why copyright has grown to be a serious threat to free culture and media dialogues in the last century.

I came to see this because I wanted to see Rip - A remix Manifesto (trailer below) at the Amsterdam international documentary film festival. But it was sold out. So I'll have to wait for it to be finished...

Sentence 5 on page 56 of "Collapse" by Jared Diamond:

All that because of a few small plants whose dangers were mostly unappreciated at the time and some of whose seeds arrived unnoticed!

Book meme:

- Grab the nearest book.
- Open it to page 56.
- Find the fifth sentence.
- Post the text of the sentence in your journal along with these instructions.
- Don’t dig for your favorite book, the cool book, or the intellectual one: pick the CLOSEST.

via Leah Culvers blog.

I am currently on the BNAIC 2008 conference (The 20th Belgian-Netherlands Conference on Artificial Intelligence) in Bad Boekelo.

As I was (along with several others) greeted with a sign at the train station for the first time in my life, I might as well also engage in this new thing they call live-blogging. Here are some first impressions from the first day (I present my paper tomorrow):

In general:

• The community of AI researchers here seems to be very nice and interesting. I'm looking forward to taqlking to even more people.
• Some people have these new, fancy mini laptops. Nice... I want one (of course)
• loads of formulas and text on the slides. Ten sessions in one day are hard to follow this way. The importance of presentation should be known by now, but here the scientific community is late.
• Everything happens in a nice resort in the dutch countryside. Maybe I play some pool later :)
• They have free Wifi. And it's completely open (granted, here in the countryside there a few abusers)

Here are a few notes of things I found interesting today:

Nao, the Robot
------------------

A french startup company managed to build a robot so versatile and so programmable that it got chosen to be the new platform for the RoboCup robo-soccer world contest. And - they brought some to Bad Beokelo to play. He walks like a robot god, has hands, Wifi and is designed for looks very well.

Isn't he cute? Notice especially how he gets up after being knocked over (but first he says: "I'm okay. I think I'd better get up"). The motion looks fabulous. He has 25 degrees of freedom and is bipedal, helped by an inertia sensor.

He is not smart just by itself, but very easily programmable, as I saw live. See the company website for more. On the dinner tonight, we had a band playing folklore music and they put a Nao on stage and he danced a japanese dance someone programmed for him. A-dor-a-ble!

The guys said they already used Nao with autistic people. Maybe it's also nice for elderly people and children, but first it will be sold to researchers, since it still gets developed.

Keynote by Ruth Aylett: "Interactive Storytelling - emergent narrative or universal plans?"
 

Her group works on Interactive Storytelling. It tries to integrate common planning theory with all these ideas.
What are the necessary ingredients of a story? You need a world and people, and they have to change each other. And a dramatic trajectory.
The levels of a framework for this are the media used, the plot (the tale) and fabula (everything that actually happened). In interactive storytelling, all levels are updated simultaneously. This needs heavy planning.
They also use "Emergent Narrative" as a bottom-up approach. To only have interesting characters is not enough for global goals... (but they can take part of the burden of generating new plans for actions).

Nice sources:
Riedl & Young: Plot repair (when user threatens plan). Is repair believable? If you want to shoot Robin Hood and try 20 times, and the system makes you miss each time because he can't die, that's not believable.
Mateas & Stern: Library of Story fragments: Facade Beats
Cavazza: Plan Trees

Goals are not enough for drama. You need emotions. Being rational alone is not interesting (drama). They elicit world-directed and/or emotion-directed responses. Ortony et al (1988) have a nice grouping of emotions.




Mihail  Mihaiylov: Collective Intelligent Wireless Sensor Networks

In Sensor Networks, nodes decide themselves what to do and they have to be careful about their energy. A network should have good data responses, but also live long - a tradeoff.

A waste of energy are the following situations: Idle listening time, Overhearing, Collision of signals, control traffic. Just going to sleep sometimes to reduce the listening cost is bad for response times. Basically, the intentions of single agents  (live longer) are bad for the system.

Solution: A node only cares for a set of "affected nodes" - i.e. it doesn't care about everyone, but only about those whose cooperation you'll need soon (because they route your signals to the base station). Learn their energy level (yes, that's control traffic, but not much).
Nodes learn their own tradeoff between sleeping and taking actions. As a result, the system is then a little less responsive, but the lifetime is much longer.

Update 01.11.

I gave the presentation and everything went well. I got a lot of questions and some were really interesting for further research. I uploaded the slides.

Also, I must say I noticed something else: While the people here in Netherlands are pretty diverse skincolor-wise, this wasn't the case at the conference. All in all it was 155 people: a lot of white men, some white women and three Asians

I am following the development of Amarok2 since a week. It's near completion, though still a little buggy. The second beta was just released.

I noticed that if you use a software everyday, you build a relationship. I donated some Euros to the Amarok team yesterday and I decided to run the beta despite some crashes since today. I do appreciate a fresh spirit in my music listening. Thanks, Amarok team.

Now. The main concept of the latest KDE 4 software is to have widgets (I especially love Folder Views). So in Amarok, too, you get an area (between media area on the left and playlist on the right) which you design yourself. Well, at least you decide which widgets you want to have.

In this screenshot, you can see that I opted to see the lyrics for the actual track and the Wikipedia entry for the artist:

Especially the widget area could use more programming love (You can zoom in, but not in the nicest way yet. Some widgets still crash.). But I must say that with KDE4 I became a real KDE fan. Thanks to Pete for encouraging me to try again.

P.S. The playlist there was assembled randomly. I skipped Robbie Williams.

stolen from realvrou

Some weeks ago, three friends visited me in Amsterdam. We rented them three bikes at orangebike. After a long pub night, we locked the bikes and got on my boat to have a last drink on the calm water. We witnessed a guy walking up to one of the rental bikes, unlocking it somehow and driving away with it. It took 30 seconds. Sadly, we needed a minute to reach the shore and couldn't follow him.

In the end, we had to pay 240 Euros to orangebike. Had we opted to pay three Euros more per bike, the we would have been insured and only payed 50 Euros. We didn't do that, sadly.

Why? Because we lacked information. Most people who have to make decisions about a risk within a new, complex situation, lack information. That's what the ungodly high profits in the insurance world are all about.

I live in Amsterdam for a year now and have not seen a bike robbed or heard of a friend being robbed. I thought locking your bike is enough. Well, obviously it depends on what bike you have. I suspect a difference in risk between private bikes and rental bikes. Because after we came back, the guy at orangebike said that ours was already the fourth stolen orangebike on that same day. And only in that office (they have several in Amsterdam) Thanks for that extra information! You lose several bikes a day??

When you really know the stakes of all players in a market situation, you get a better picture (like mine I know have and sketched below*). But if you lack information, betting on a risk is unfair.

As we open up so much information these days, I would really like to see a public database, fed by everyone, for information attached to risks. Information like the one I present here about rental bikes in Amsterdam, but somehow organized. Imagine you come into a new situation, like having to decide wether to insure yourself against some risk, and you get the experience and information from a lot of  customers and other involved stakeholders from the internet.

Risks, and the bets we have to place on them, are a really essential part of our lifes these days, and horribly abstract. It goes wrong all the time (look at the banking crisis). I am close to saying that it might be one of the great issues that the information age should tackle.

Not because of bikes. Although bikes are really important in this city. As you see, I take this issue pretty seriously myself :)

* Everyone but the tourist wins. Obviously, orangebike doesn't really care to have the best locks or give you a second lock for the wheel (like some other services do as I learned). They'll get their money for a new bike anyway. And as tourists normally leave the town the next day, they don't have to care about customer satisfaction. And for thieves it makes sense to go for the rental bikes. They can specialize on only one kind of lock, and all orangebikes use the same and are easily recognizable. You can walk up to one of them and break it if you are trained on the lock. And as we saw it, the whole processs looks like you're unlocking your own bike. Lastly, the insurance would stop insuring rental bikes if they wouldn't make a profit. Luckily for them, bike rental services don't really inform customers and so they don't really have to pay out recoveries a lot.

I am currently doing a literature research on Wireless Sensor Networks. Basically, those sensors can be very small and cheap and measure everything from your heart rate to wildfire occurences or enemy combatant movements.

This is an exciting research area which is based on how the communication between those little guys should be done. I like it because they provide simple models whith which decentral communication can be simulated, but these models are also meaningful, because there are applications around the corner (and you might even get to try them out in reality if someone gives you a bunch of those sensors).

Well, the assumption is that Wireless Sensor Networks will be abundant in 10 years. Put them in cloths and you have smart underwear. Throw a million of them off a plane and you can have a lot of cheap and error-resilient knowledge of the environment.

Well, at least until all their little batteries are down.

My point today is: What if we throw a lot of them off planes and use them until they are out of power? What if we do this a lot? Seems likely. It's so damn useful, in every branch of life, from military to environmental observation.

Maybe Wireless sensors will be the junk of the next decades. They might be everywhere, lying around, polluting, rotting. We are going to tell our kids not to pick up old wireless sensors and the vets will get them out of our dogs intestines.

We just got mail from the Belgian-Netherlands Conference on Artificial Intelligence:

Dear Nicolas, Tomas and Martijn,
we would like to inform you that your Regular Paper entitled
"Beating Cheating: Dealing with Collusion in the Non-Iterated Prisoner's Dilemma"
is accepted as an oral presentation for the BNAIC 2008 conference.

This paper is a follow-up work on my paper that I presented at the student conference in Utrecht, but to have a paper accepted at this conference is a much bigger scientific honour :) I thank the anonymous reviewers for their helpful comments and look forward to meet interesting people on BNAIC at the end of october.

Update 01.11.08: The proceedings are out. I give you  the paper  and the bibtex.

My favorite futurologist, Jamais Cascio (see the "Participatory Panopticon" vision), recently gave a talk in San Francisco. He talks for one hour, starting with education, but moving to almost all topics that he is interested in right now. He says the talk is about "his work in progress". Some of the thoughts are not as new as this year (e.g. see my review of "Radical Evolution" by Joel Garreau), but some I've seldom or never heard. I'm looking forward to hear Cascio's new scenario that might come out of this.

I started taking some notes halfway through the talk when I noticed that some interesting ideas of Cascio were popping up, rather than a coherent picture. Here are his ideas that I remembered:

• A future of education: Every students creates his/her own curriculum totally from scratch?
• There is a recent price drop for molecular 3D Printers. Looks like the price slope for other technologies, e.g. CD burners. They will be really affordable in a few years.
• What if we could have wearable pattern recognizers? A really vague concept right now, but what a great idea! Best thought of the talk.
• Some researchers notice an increasing ability of modern humans to think complex (by themselves). All new media stuff from the last 60 years played a role in that (albeit being called "junk food" for the brain, each at its time).
• We will want to have personal data security in a world that will undergo physical changes (think climate change). Dislocation will happen to a lot of us.
• Revisiting the Participatory Panopticon: How will it influence our daily storytelling when every detail is seen and we maybe even can have two or three views on it?
• Physical augmentation will soon be for everyone (who has money, of course). Well, I knew that, but the place to pay attention to right now is the development for the disabled. Their stuff is already so cool (e.g. legs, eyes, ears) that "normal" people are starting to want them these days because they are better than our natural set!
• On the non-material augmentation market (think physical drugs), this has already happened. Students took mental drugs (e.g. attention enhancers) to learn better. Now they arrived in the workplace. Be ready to compete against mental doping - on your job.
• Collaboration, bottom-up Developing, Open Source - these concepts are moving into more workplaces, but also into politics. Warfare think tanks discuss why terrorism is so successful. It is because it already embraces these terms. The big players start thinking how they can play this game, too (but still remain a big global power). I read this first on Jeff Vails site (Terrorism in a Post-Cartesian World: PDF, Network Defense strategies: HTML).

It's weird that when someone dies that you never met can ruin your day. Esbjörn Svensson died while diving 2 days ago. I have spent countless hours listening to his music, while working or chilling. I am very grateful.

I saw them in Oldenburg last year and they were awesome. So into the moment from the first second on. I'm sad now.

Funny thing that Germans as well as Englishmen should understand this dutch title :) - which I am not totally sure is correct, I need more practice.

Anyway, so I was a speaker on this student conference, organised by the dutch society of AI students. All other presentations were in dutch, but the organisers were kind enough to let me apply even if I only could give my talk in english. And they accepted my paper, which results in an official publication in the conference proceedings.

The project which this is about has been done last semester in the course "Advanced Self-Organisation" by Martijn Schut. It deals with trust-building in complex markets. My partner on this was Tomas, but as he is currently in China learning to play Go, I wrote the paper by myself. Maybe we'll work on the topic some more...

Last Friday, I went to Utrecht and attended the conference, which was a nice meetup and my talk was well received.

Websites are getting heavier by the years (and this one is no big exception). As people crave nicer designs and functionality and internet connections are getting faster, our web servers include more HTML, CSS, Javascript and pictures when they reply to a page request.

But: Not everyone's internet connection gets faster at the same rate. Some people are stuck with modems, for instance a lot of places in Africa. The internet becomes more and more unusable for them. It's called the Digital Divide, and it's a shame, basically. It's getting bigger for them as web pages grow heavier.

No one puts in extra work to maintain light versions of websites so that these people can conveniently surf them. They don't have money, so they're not important.

But if rich people need light websites, stuff will happen fast. Luckily, with the advent of internet-browsing phones like the iPhone, a lot of big websites offer mobile versions. Now that is something for the rich and, by luck, also for the poor.

So, Africans or other people with low bandwith: Check out mobile Reddit, mobile GMail, mobile Facebook, mobile MySpace and others (I just googled for 2 minutes)! Save yourself a lot of mind-numbing page load time. Note: Some webservers see if you actually use a mobile phone browser, like mobile Spiegel, but you can fake what browser you are using.

On my website, I have a widget showing the articles I had recently starred with Google Reader. That widget  stopped appearing recently. After some research, I found out that  the javascript error  "opera.version is not a function" is caused by my scripts initialising a variable with the name "opera" (thanks to David Buchmann for his writeup).

You see, to render nicely in Opera, the Google javascript wants to work with a variable by that name. If it runs in an Opera browser, Opera will provide that variable. If not, it should be "undefined" because it doesn't exist. Unless, of course,  my script (or any other that ran before) instantiated a javascript variable "opera".

Well, my scripts did (it's a natural variable name to come up with if you want to store somewhere that the browser is/is not an Opera browser). I renamed that variable and the Google Reader items show up again.

Here, we have a nice first-hand experience why namespaces are a great idea. But as the web grows in an organic manner, we have to take what is there.

Lessons learned?

• Name variables in your code more specific than general. For instance, isOpera would have been better than opera.
• When there are no namespaces defined, the big eat the small. If your script is less important than, say, Operas or Googles, then watch the hell where you're naming, little guy.

There is a beginning discussion that the wealth difference between the West and other parts of the world is not just a result of mere aggression. And it is not only noticed in the West. As others realize their shortcomings, the West has to work even harder.

Don't get me wrong, there is aggression out there, but a lot of people recognize that it doesn't make up for the whole equation. Writes Jeff Vail:
 

I can think of one justification that remains to some degree in America—we still seem to be better than anyone else in the world at combining just the right mix of structure and freedom, discipline and creativity, conformity and rebellion to create the kind of synergy that drives business innovation. That, too, seems to be changing, but for now I think it still justifies some kind of multiplier—but this mix is also subject to the forces of globalization.

However, I am not posting this to make that point yet again. I came across two sources that show how this reasoning makes its way into scientific discussion:

Study finds anti-social punishment in more traditional societies, dragging profits down

A recent study by Herrmann, Thöni and Gächter (published in Science magazine) conducted cooperational games among students in a world-wide experiment. Groups that cooperate can maximize their profits, but individuals can also defect the others. In addition, punishment was possible. The paper can be found here (without paying a Science magazine fee) and a comment that also appeared in that Science issue is here. It concludes:

A few subjects, when punished, rather than contributing more, suspected that it was the high contributors who punished them, and responded with antisocial punishment: They punished the high contributors in future rounds, leading the latter to reduce both their contribution and altruistic punishment. Herrmann et al. collected data in 15 countries with widely varying levels of economic development. The subjects were university students in all societies. The authors found that antisocial punishment was rare in the most democratic societies and very common otherwise. Indexed to the World Democracy Audit (WDA) evaluation of countries’ performance in political rights, civil liberties, press freedom, and corruption, the top six performers among the countries studied were also in the lowest seven for antisocial punishment. These were the United States, the United Kingdom, Germany, Denmark, Australia, and Switzerland. The seventh country in the low antisocial punishment group was China, currently among the fastest-growing market economies in the world. The countries with a high level of antisocial punishment and a low score on the WDA evaluation included Oman, Saudi Arabia, Greece, Russia, Turkey, and Belarus.

China reassures scientists not to fear failure

This news is big:

China will tolerate experiment failures by its scientists to ease pressure, encourage innovation and cut the chances of fraud, a top official said on Thursday.

China recognizes a cultural shortcoming in its scientific community. The ratio of worthless or even wrong studies is far higher than in the West. As far as I know, this is not rooted in the very old chinese history. But at least in the last 100 years, China has built up a dangerous perfection cult. Dangerous for its own progress, that is. It is politically remarkable for the change China is going through that this is acknowledged.

So, while the Middle East suffers from its honor culture, China wrestles with perfection cult.  I am not saying that we don't have cultural problems on our own. My point is:  (at least some) others are working on their self-understanding. Let's start working on ours again.

* image by tarotastic

I recently came around to get pictures off my mobile via bluetooth. They have been locked in there a long time.

A lot of them I had completely forgotten or never looked at on a real screen. The camera is not very good, but sometimes I obviously saw things that the world needs to see anyway. Here a some jewels:

In the library of the university of Osnabrueck: Lexicon of nutrition. Volumes A to Fat, Fat to M and N to Z.

On the train station of Muenster, Germany. If you would really spell Osnabrueck like that, it would sound as if Adolf Hitler says "Osnabrueck".

Seen in the window of a turkish supermarket in Osnabrueck: "Smartklamp: Circumcision with one click!" If this is satire, it is damn good and the place of action has been well chosen. If not, I have nothing  to add.

Update: Jan found out that it seems to be for real. Ugh. But at least the company's site is down. Maybe a rabbi or whoever does it is still the way to go.

One of my first trips to Amsterdam in search of appartment and a new life. But the Blue Screen Of Death is everywhere! I bought my ticket elsewhere.

This is how you transport kids and other stuff on your bike in Amsterdam.

Looking at this patent from 1914, you got to admit it: The Americans had ad placement in their hearts since day 1.

It's genius: A scarecrow is an attention attraction device. Why waste all this potential only on crows? Since humans will also look, display an ad!

Samuel Hunter, I salute you! I wonder if it made him rich or if he got chased out of town :-)

Oh, don't forget to look at the drawing.

What would happen if people lose trust in Google, success-wise? If they stop believing that the good people at Goole will keep their servers running forever, let their spiders crawl to get the latest internet content and make sure that the search results are excellent?

When people lose trust in the success of a shareholder company, they try to sell their shares before they become worthless, which makes them worthless really quick. That could happen to Google one day, of course.

But there would be another dimension: Everyone would rush to get his data from Google before the servers are dead. Gigabytes of Gmail conversations, Google Analytics statistics, Google Calendar Entries, Google Reader collections. Imagine Google does have technical problems, and then we all, at once, try to get our data back. Then they have technical problems (Even if they don't have technical problems I think it would be hard to survive such a data rush). 

Google has published  plans to build a Wikipedia rival. The key difference: There can be more than one article (a "knol") about a topic. One article is related to one author and people can approve to it by voting. Googles ranking algorithm skills shall assure that people will find high-quality articles.

Now, I think that this has great potential. For over one year, people complain about Wikipedias admin elite. The discussion pages seldom became more than a fist fight over who is right and it is never obvious if controversies exist. The problem seems to lie in the system.

We have to face it: Sometimes, there is no general consensus reachable. That is a wrong idea from the seventies. In five years, we will maybe laugh at the idea that people on the internet could agree on one way of explaining something.

As I write this, I suspect some highly-skilled Googlers are discussing how to rank those "knol" pages. Controversial terms like "facism" will have a lot of articles. When I search for "facism", what will Google show me?

What I am heading for is this: Suppose that 90% of the people agree on one type of definition, while 10% favor another (Note that I say "type" - several articles can all define the term in basically the same way). There is a controversy, and I - as someone interested in the term - am interested in learning about it. I want to see both sides of it and then decide for myself what side I am on.

A stupid, popularity-only ranking algorithm would only show me terms from the 90% bulk. But 10% is a strong minority. I say: Put both sides on the top page, Google. Use this new way of having user rankings and identify if users fall into distinct groups, upvoting distinct types of articles. And then, don't bury the minority opinion. This might be a new way to show knowledge on the internet.

P.S. Another thing comes to mind: Maybe we will have to get familiar with amazon-like greetings concerning opinions: "People who share your opinion on X, also think that Y."

Wow .. this is exciting news:

The 419 Scam aka  Nigeria Connection spammers now don't only send out weird english mails (telling you to send them money so you get rich by helping them to transfer billions of dollars somewhere).

I have just received my first weird german 419 scam mail! It is an honor to the german economy to be recognized as worthy and dumb enough to open a whole spam division devoted to bad german spam mail writings. They even gave me a hotline to call (which, by the way, is in Belgium)! The german is very bad indeed, but they are still in the beta phase I think. They will learn from customer feedback. Kudos!

Here are some snippets from this exciting and hilarious new product:

Als unser Vater hat angefangen Todebedrohungen empfangend, hat er mir erzählt, dass er die Summe von 6.400.000 Dollar (SECHS MILLIONEN VIER HUNDERT TAUSEND AMERIKANISCH DOLLAR) in einem Finanz Sicherheitshaus in Brüssel-Belgien deponiert hatte. Er hat erzählt, dass mich jener inacse irgendetwas zu ihm geschieht, sollte ich versuchen und soll in Kontakt mit der Sicherheitsfinanzierungsgesellschaft ankommen, und dass er mich der nächste Angehörige gemacht hat, und dass der Inhalt als FAMILIE WERTSACHEN erklärt wurde. 

Wir haben entschieden, Ihnen 20% von der gesamten Summe für Ihre Hilfe anzubieten, und einzugeben. Sie werden auch uns mit Ihnen zu Ihrem Land nehmen und werden uns helfen, das Geld für uns zu verwalten, während wir unsere Studien fortsetzen werden.  

Wir sind diplomatische Reisepässebehälter, damit wir kein Problem haben, überhaupt zu irgendwo in der Welt zu reisen. Bitte Erwiderung zu uns durch unsere private E-Mail-Adresse, die ist: Johntumba2007@yahoo.com
Wenn Sie uns rufen, kann ich Deutsch mit Ihnen sprechen so es ist kein Problem.
Unsere Telefonnummer hier ist 0032448349849.

Germans, look out for your parents!

And Gmail, I see new work for your spam filters ahead.

During the 77 year celebration for the institute of sciences ("Exacte Wetenshapen"), I took part in a Salsa workshop. Now, pictures emerged on the interwebs. I am the one with the black hat.

Thank god, I am not making terrible mistakes on any of them :-)

It was fun, though. And a great buffet.

[pictures from fotorene.nl]

Wow - this is absolutely impressive. It is something I'd like to study in my Master's programme. And - as I am currently preparing for my examination in Philosophy Of Mind - Can you imagine what it is like to be a part of this? How is it like to be a starling?

For my Bachelorthesis (I write it using Latex), I wanted to have little bordered textboxes that would float next to the main text.

They should explain terms that are mentioned in the main text, so that everyone could read more about that term if (s)he needed to.

It turns out that this is no easy task with Latex. All standard elements I tried would either not float very good, have no border and/or failed to wrap the lines within the info text.

I spent three hours to come up with a nice solution, so it might be useful for people if I share it here.

I defined a new command in the top of the document:

%%%% Custom Command for floating Infoboxes
%%%% usage: \infobox{<title>}{<text>}
\usepackage{picins}                 
\newcommand{\infobox}[2]{
    \parpic(0.34\textwidth,0pt)[lf]{
        \parbox[b]{0.32\textwidth}{
             \bigskip {\bf #1}  \small{{{\sffamily #2}}} \bigskip
        }
    }
    \bigskip
}

The picins package is normally used to place pictures within the text, but when I place a \parbox inside, it works really nice for text.

To create such a infobox somewhere in the document, you just use it like this:

 \infobox{XSLT}{
    XSLT is a stylesheet language that can parse XML files and transform them. The output will be another text file, possibly XML. It offers a lot of capabilities as it is a fully functional programming language.\\
    Like XML, XSLT has also been specified by the W3C consortium.   
  }

Here "XSLT" depicts the bold-faced title within the infobox and the second argument is your info text. Here is a screenshot that shows how a result will look like (I bold-faced "XSLT" in the main text myself):

The text block that the infobox floats around is simply the one it precedes in the Latex document. You can also have the infobox on the right. Give the parpic command "rf" instead of "lf" as an option.

The picins command is praised as a really nice package, but it has some problems: If the remainder of the paragraph text is insufficient to fill the area to the side of the infobox, the text from the following paragraph will run through it. It also won't work with enumerate/itemize besides the text. Both of these issues can be fixed on a case-by-case basis, but it can be nasty...

Feel free to drop me a comment if you like it / can do it better / can make it more beautiful.

Update (05.08.2007): I made the height of the infobox independent of the text length and used sffamily for the font. I now also mention some problems with picins  that I (and others) ran across.

Just a recommendation: great talks from the TED conference are now freely available.

I just watched Ze Frank and he is hilarious as always (to me, at least). Go have a look, it's only 18 minutes.

You might also want to check out Malcom Gladwell.

Plus, you can just get the audio if you want. I just downloaded Peter Donnelly (How juries are fooled by statistics), Helen Fisher (The science of love, and the future of women) and Jane Goodall (What separates us from the apes?) to my ipod :-)

It happens to me once in a while that I get the feeling to be overwhelmed by the complexity of all the electronic stuff I am working with.



Programs that I use as tools, libraries that I use to write code and the source code I write myself. They interplay. They may work or they don't. It may be my fault or not.
And there are those thousands or maybe millions of tools and libraries out there that I could use but haven't heard of. Maybe I would find the perfect solution within the next click on Google? Where is it?

This article by the creator of one of my favorite leisure time surf sites brings another issue to the point: Software projects, ours included, fail way more often than we like to admit. OK, we felt that this true. Building nice, reliable software is hard. It's somehow an unsolved problem.
But here is the punchline: You can call a project successful when it lasts 15 years.

15 years. Somehow I knew about this, but I never consciously thought about it. It's true. Today, especially in information technology (but not exclusively), putting something out there that lasts for 15 years is almost all you can hope for.
It happens if you're really good.

In five years, there will be new ways of doing things and your project will be considered old. They'll probably think your code has that old-man-odor and it takes another two years until someone finally rewrites it, but that will be it, mostly.

It's stuff to make you throw the keyboard away and run away to start a new happy life in the forests.
With software, it feels like the effort needed to be put into the work to make it last a few years is ridiculously high.

But then again, maybe we can take joy in this modern craftsmenship again by  accepting that it's faster, but it's not so different. I love this story from David Humphrey, who swims through the ocean of Open Source software trying to make sense of it. He learned about his grandfather and found out how much the things they do/did are/were alike, even with 50 years difference:

[ed: Like him,] I take things that were never meant to go together and work with them until they fit, patiently refusing to give up - even when it’s not clear I can make it work. Where she and my grandfather worked with pump motors, I work with source code.

Maybe not even the success rate changes so dramatically. As more programs get written (aka. as more tools are made), there is more success and more failure, both of those numbers go up.
What changes is the time frame. It's faster.
And also the standards rise. Less people feel they need to keep that ol' piece of software when there is so much innovation out there.
It's the way of the world.

However, maybe we are telling our kids the same stuff again one day: "When I was young, you could fix or build most of the software yourself. Today, it seems impossible!! *cough*"

Chris Crawford was in Darmstadt on a conference dealing with Interactive Storytelling.

Hm, never heard of it.

That's bad.

He doesn't recognize anyone who contributes anything remotely interesting. So, the market of competition is still relatively empty.

That's good.

Time to dive in!

• I listen to shows anyway and now I force myself to really delve into some of the topics and speakers
• I get to train my english writing skills

• autism has genetic roots, but the environmental issues that activate genetic dispositions are unclear
• it seems that a brain area responsible for computing social interactions is impaired
• Rising rates of autism might be due to the rise of science and fast transportation and communication, leading to more and more "systemizing minds" (aka. engineers, geeks and the like) mating their (fe)male counterpart.

1. Causation: Is it purely genetic? Purely environmental? Which genes might be responsible?  If we know the cause, can we cure it?
   
2. Classification: What is autism? Who is autistic, and who is just "nerdy"? Are the rising numbers of diagnoses over the last decades just due to the attention the disease has gotten? Are people gradually distributed on the spectrum of autistic traits, or are "normal" people on one cluster, and "ill" people on another?
   

• There are advances in graphic capabilities, but they have gotten slower. It's not the same Aha-moment we had 6 years ago. Why pay hundreds of dollars?
• The advances in technical capabilities mostly include added functionalities that have nothing to do with gaming: Playing music, a web browser and so on. I don't think that those capabilities are really able to impress a lot of people that have real computers at home. In addition, those features will all be pretty proprietary. I see a lot of frustration on the horizon.
• The most important point: There is no innovation in ideas for games. In the end, almost all of them are mere finger training. They don't capture your imagination. Microsoft hired Peter Jackson to bring stories to games, but one attempt might not be enough. Maybe the  industry needs a crash, so that bottom-up innovation can make its path (And of course this is where I see interesting opportunities for developers to get heard).

1. One thing that I also thought about back in Africa is what happens when you open these children to email or instant messaging. There are certainly bad experiences to be made out there. Children in western countries are endangered by pedophiles or other threads, too, but they are better informed as they grow up with the technology and, most important, they are rich and thus far less easy to be tempted.
2. Mitra (the indian scientist) compares those self-educated children to indian cable technicians. Most of those people can do a good job without any deeper understanding of the system they're dealing with. They just remember sequences of actions that lead to successs. Maybe that's a necessary intermediate step to a knowledge society. But maybe it's inherent to indian culture. The latter option would be a really bad sign for India...

• For Mac users: use Authoxy. It's a tool that will intercept all requests and forward them to the Proxy. I got Skype working that way.
• For FTP: There might be just no way you can get a decent FTP program to work properly behind some proxies. I installed lftp and got it working somehow, but it wouldn't let me delete. What the... ? So I remembered a hint someone gave me years ago and surfed to www2ftp.de. These guys let you do File Transfer over HTTP with the browser. And it works great. You can even upload a whole Archive with stuff and the tool will put every file at the right place!
• For subversion, the place to specify a proxy is ˜/.subversion/servers - but I do have my issues with it, still.
• And again sthg for Mac-Users: Darwinports (slow, but worthwile) will need to know the Proxy, too. Set the system variables "http_proxy" and "FTP_PROXY". For example, you could add these lines to your .profile - file (replacing the UCD proxy with yours):

• gnu make
• autotools
• gccxml
• opencv
• doxygen
• g++
• XML
• libxml
• Python
• diacanvas
• GTK
• Glade

At least, Jaron Lanvier calls it "art". Cephalopods are a class of mollusks containing octopus, squid, cuttlefish and nautilus. Their means of communication is so different to ours that Lanvier used it as an example when he was interviewed about what the future could bring for mankind. Maybe communication will be enhanced, he thinks, pointing to cephalopods.

Take a look at this page and see them in action (there are two movies on it, refresh the page to see them again). You'll see that cephalopods can show amazing stuff on their skin: moving patterns or, chameleon-like, the colours of the surroundings. Researchers know that the patterns are used for communicating with mates or prey. It's an interesting way to show what you're up to and the researchers even like to compare it to humans:

"Although there is no evidence that cephalopods communicate symbolically like we do, there are other forms of communication that we have in common. For example, cuttlefishes gesture with their bodies by striking specific postures that signal their intentions. Humans also gesture and assume postures both to signal intentions and to reinforce what they are saying. Cephalopods use gestures or postures to reinforce body patterns in a display. Humans blush when they are embarrassed, ashamed, or sometimes just anxious. The mechanism of this response is different, physiologically speaking, than the body color changes of a cephalopod, but they still communicate an internal state of being."

Cephalopods seem to us like weirdos from another planet. But still, they live on the same planet as we do. While we're being naughty in envisioning the future, why not imagine us using displays to communicate feelings? Blushing is so old-fashioned... :-)

1. The Operating Systems get more and more comfortable. Mac OSX is really nice and top-rated by most of its users. Linux distributions like Suse and Ubuntu are really close to be usable for a broad userbase (in fact, I came to Linux last year and getting it installed and configured is not such a geek-honour like it was 5 years ago).
2. More applications are available on all platforms. There are projects like Firefox, Thunderbird or OpenOffice - which is really usable for people with normal demands. And there are more and more applications that are available online.
3. 1) and 2) are product of the hard work of many people over the last years. Those things were described years ago, but I feel that they are just about becoming really close to reality. Also, 1) and 2) are more important for the administrators, those people like me who set up systems for friends and family. The user side argument is: There are a lot of users who basically do not install anything special. They just surf the internet and write emails and documents and that's it. Those users, mostly people over 40, are a lot of people, a huge part of "my" machines are operated by those. They expect that "the machine just works". If there is something broken or not working as expected, they'll be calling me anyway. Then, why the hell shouldn't I install on their machine what I know to handle best? That would be reasonable. All they need to know is where to find which button. Also, with Linux, I could avoid the legal/illegal Windows copy - question (which is getting more important in a few month as it seems)
   

1. you need to chose a domain where computers are not even close to reaching human performance. Object recognition is worth a try, but it is already a domain where computers start to reach first successes. Why not try reading people's intentions? Present situations with several participants/objects involved and let the user guess what person A is about to do. This task -well designed- can be solved by first graders and not in 10 years by a computer. reading intentions is out of reach.
2. the fact that you can theoretically decode computationally everyhing that was encoded computationally needs to be taken care of. The ingredients of the task need to be combined at runtime. That is a combinatorial issue and cryptography has thought this through: A 128 bit key is theoretically computable, but practically this takes a long time. A situation that I described in point 1 is a good model for that...
   
3. There remains the problem that spammers might use humans to solve those tasks: they delegate the actual CAPTCHA-task to some human that gets paid a little money (i don't know if that actually is cost-effective for them) or incidentally wants to see some delicate content that the spammer provides in that moment. What happens here is that "our" machine asks "their" machine to do the task, and "their" machine delegates the task to some human, just like a proxy server. So we need to make that delegation difficult. Maybe that would need some anti-semantic web approach: Data that is well-formed, but definitely not machine readable or delegatable. That is: the bot might transport a bunch of data to the human, but not the sense of the task.

• homo sociologicus (acts to fulfill the norms)
  
• homo oeconomicus (acts to maximize his profits - whatever they may be. this definition of what we can call a profit is a theoretical problem - some people want to explain suicide with this model)
  
• emotional man (whatever emotions rule you, you will follow them)
  
• identity insisters (you have a strong picture of what you are? -Then you will try to act according to this view of yourself)

1. collect all those ideas and
2. make it possible to assert connections between them in an easy way

• Content Holder - display content in another pane so you can compare two content areas (I also tried out Split Screen, but it doesn't seem to work on FF 1.5 yet)
• Mouse Gestures - draw lines on the screen with the mouse. That'd be used to connect chunks of content to each other.

• What are the semantic structures the user would need? And how would the XHTML chunks be addressed?
  
• How can the user view and reuse his associations?
  
• How should we model the processes that a human makes when associating concepts?

I just installed the iBrowser plugin for TinyMCE to make image upload possible (it is not by default included in TinyMCE). This is a pretty good description.

Besides chmoding the ibrowser directories to 777 (not 775) I had to make two extra adjustments:

• I switched the name of editor_plugin.js to editor_plugin_src.js because otherwise, there would no ibrowser-button be seen in TinyMCE
  
• I still couldn't upload pics because the "Browse..."-button that lets you select a file on your computer was hiding the button that lets you say: "Yes, please upload!" I changed the size of the input field in ibrowser.php, made it 10 chars shorter. Maybe that's a general ibrowser-problem with Firefox on Unix (Opera worked well).

Since 2 weeks I always had problems installing software on my beloved Ubuntu Linux.
There was always some 404 Page Not Found Error on some Server, even with "apt-get update".
Honestly, I didn't have the time to go after that, because the semester is really rolling these days. And I'm not a Linux genius, you know. I had no iea where to start looking.

Today, after googling a little, I remembered editing the file /etc/apt/sources.list right after installing Ubuntu. I inserted some backport then, as it is (still!) proposed on the Ubuntu Forum . You specify that some "backport"-Server will be
"http://ubuntu-backports.mirrormax.net/":
In detail, you ought to write this:
"deb http://ubuntu-backports.mirrormax.net/ hoary-backports main universe multiverse restricted"

However, on the Ubuntu backport project page it says:

"NOTE: This hoary-backports line is obsolete. Please don't use it:
deb http://ubuntu-backports.mirrormax.net/ ..."
Now I thought I found it. I just edited /etc/apt/sources.list, replacing the URL with
one of the other mirrors that are proposed there.
They all failed, too.

I love remembering those seconds where you are so close to giving up. I browsed to one of those mirror servers to look if there is anything at all. I already had noticed that "http://ubuntu-backports.mirrormax.net/" contains no files for the distribution "hoary" which happens to be mine.
But "http://acm.cs.umn.edu/ubp/" has everything there. It's just in a directory with a slightly different label. Instead of "dists/hoary-backports/" it is "dists/hoary-backports-staging/". Seeing that, I tried using that in /etc/apt/sources.list:

"deb http://acm.cs.umn.edu/ubp/ hoary-backports-staging main universe multiverse restricted"

and voila - it worked. "apt-get update" finally yielded no errors and Synaptic now installed what I was looking for.

With so much documentation that Ubuntu has build up, it is no big surprise that it is not easy to be updated at all places (though I think this backport server list is a little flawed - you need to know the directory structure on the server...).

I'm working on some Cognitive Psychology papers on text comprehension these days.

In the experiments those papers describe, they always use their undergraduate students as participants. I have to participate in those kinds of experiments myself to get the credits.

Now, I am not a Psychology student. But I know that to be allowed at studying Psychology, you should be really smart. At least that is the case here in Germany.

When all those experiments are conducted with some kind of elite brainies, can they really be transfered to all kind of people? Im not questioning their relevance, but if the data is really giving you a profile of the mean brain?

For example, when they say: "Calvo and Castillo (1996, 1998, 2001) and Calvo et al. (1999) observed facilitation in naming the inferential target word under 1,250- and 1,500-ms SOA conditions, but not when 500- or 1,000-ms SOAs were used."

This means that the partipant's brains did  react when the stimulus and the measurement were 1,250 - 1.500 milliseconds apart. They did not react significantly when they were only 500 or 1,000 milliseconds apart.  Now we know how fast smart young people react, when they are asked to name a target word. But:

Is this still true when you stop testing only the nerds? When you test  people that are not very bright, it might be that you get  results that don't have anything in common with the results above.

Maybe there is a study on that question, but how would the question be? "Are smart people accurate subjects for psychological studies?" No one can define what "smart" means. We all know where the problem is, but science needs more specific grounds.

I would suggest to differentiate people on their memory ability because that is what came to my mind first when I thought about Psychology students - they know how to learn :-)

I just noticed that the Java Script Code I showed in this 2cents was not very well readable. I just colored it in green. Everybody saw it was Source Code, but nobody would have fun to read it.

I use Jedit as my favorite code editor and I remembered it has this cool plugin called code2html for turning Code into nicely highlighted HTML. Unfortunately, the plugin manager returned some awkward ftp error again (is Jedit not maintained anymore? They even have a MySQL access error on their index page!).

So I googled "code2html" and found this online CGI Script. It works really well and the output looks nice, but sadly, its output is not XHTML. The font element is used with its "color" attribute:< font color="4444FF">

Shortly before giving up I thought: "Why not copy and paste it all into my TinyMCE Editor I have for my Webpages? Let's see what it does with it."

And voila: <font style="color: rgb(68, 68, 255)">. Here the styling is CSS (of course, the "font" tab has to be configurated as valid_element in tinymce).

A nice example how good a software TinyMCE seems to be.

Today I wanted to make some progress on my private Homepage Framework.

Sadly, I spent most of the afternoon surfing. You know how that works... I finally tried out TadaLists after I read about it the tenth time and then also Backpack . I read blogentry after blogentry about it for no reason than curiosity... I think that besides the points they make with simplicity and the smile on your face when all the JavaScript stuff works so elegantly, some of the features are really cool (like email a list entry or note or pictures).

But not all is heaven. I tried out the SMS Reminder Service (they even have O2 Germany, my Provider, listed there). It didn't work. I can program an alarm call on my handy with the same effort anyway... And why all the hype about this easy text format for their wiki? It's just another script language and you will have to learn it. Why not use a cool WYSIWYG - Editor ?

So then I finally read about Ruby On Rails. I even watched the presentation movie. Maybe I got around that so long because I feared it might be so good I'd stop working on my own project. And it is pretty cool. Ruby on Rails makes all that maintaining boring db access code (be it editing or retrieving) a snap. Imperior to my stuff (at least in today's version) is that you can arrange it all just the way you want. You can take gifts, and then you change the gifted code where you want it to look your way. It seems that, if you don't change too critical things, just the presentational pages (*.rhtml), the gifted code will still scale smoothly with the database. No Mapping! You change the database, your webpage changes. I can understand why David, the main author, is angry about J2EE guys claiming the whole ground of good frameworks.

So that made me interested, I even found a nice cheap Webhoster that offers Ruby but I also asked myself desperately if I should really go on coding or just switch to Ruby On Rails - for time is money :-). I decided that, yeah, I should go on:

• after all, I'll know what it means to make up a Web Framework on your own. Somebody who just knows Ruby On Rails knows Shit. Okay, (s)he might be faster and better than me but (s)he doesn't know what (s)he's doing there. Who cannot value the gift is gifted, but poor. And then, there is the law of leaky abstractions. Every abstraction leaks, somewhere, inevitable. You cannot know everything down to the bytes, but I would rather hire someone who knows what concepts are mapped beneath his level of abstraction than someone who thinks (s)he is walking on concrete while (s)he is really walking on nothing but sunshine (sounds like a reversed LSD trip...).
• I would still need to learn Ruby. And then Ruby On Rails. Honestly, I'm making this project up to get some requested Webpages up quickly (this one included). And I want to know what I'm doing, roughly. In short term thinking, which is not aaalways avoidable, I cannot ride a totally new horse now.
• My Framework makes some more gifts than you get just using Ruby On Rails. There is menues, grouping, RSS, some Javascript things, I include and configure a WYSIWYG Editor as well as an image gallery, Image Rotating and so on. Now that is because I do something that is not so flexible as Ruby On Rails is (way not), but rather a cocktail of cool things about web applications. Of course, I could rewrite my PolyPager so that it uses Ruby On Rails. Presumably I could save half of my code and get live-db-updating for free. I do hope I someday find the time for that, but a good deal of the time I already out into this was for decisions about the things I mentioned above.

While researching the web for Generators that do what I try to, I found CodeCharge (among others). It promises to be a really mature Generator for Web applications.
All the more interesting, it works just like mine: The input is an XML File, and a lot of XSL: "over the years the complexity of our XSL has grown tremendously".
A lot of the way they did it reminds me of my last project at RoeperWeise. where I programmed Version 1.0 of a VB6-Generator. The tying of developer-defined actions to events, for example. Interesting.
But Codecharge might not be perfect. Try that URl in Opera: All the main links are gone...
Good thing to know nobody is perfect. I know how complex this Generator thing can be when you keep adding features (and they have a lot!).

So get it on!

1. use xsl:text whenever a special char is NOT used in XHTML that can be properly parsed (that means: it's valid). So when we have the operator smaller-then ("<") in PHP or SQL, or the PHP delimiters (""), use <. Also do this when xsl:value-of - elements are coded within a XHTML-Element to dynamically fill in values. The WHOLE XHTML-Element then has to be masked.
2. When you echo out XHTML-Code that uses quotation marks (e.g. for an attribute value), use single qt. marks for the echo-function and for the XHTML string use whatever you like. Either way, it will be double qt. marks in the oputput! Some portions of the code will have to be less readable, but only few. Another Consequence will be that PHP-Vars must be outputted in their own call to echo.