Telling all on I'm a Scientist

In future if anyone wants to know what I think - about almost anything scientific and quite alot else - all I have to do is point them to my profile and my collected answers on I'm a Scientist get me out of here. It's been a week now since IAS concluded and the winners announced and I've had time to collect my thoughts, catch up on the day job, and reflect on taking part in this most excellent event.

I'm a Scientist get me out of here is aptly named. By Thursday on the second week I was - on balance - more relieved than disappointed to be evicted from the virtual jungle clearing, called the Chlorine Zone, that I'd been sharing with four other scientists. (Beyond the eviction thing the analogy with I'm a Celebrity breaks down. We five were not required to undertake challenges designed to freak-out the squeamish nor rewarded with discomfort reducing morsels.)

No. I'm a Scientist is an altogether more civilised affair. It's a direct engagement with school children; meet-the-scientist on-line in which school children can ask the scientists questions on more or less anything they like. There are two types of engagement, chat and ask. The live chat sessions are booked by teachers and scheduled during school science lessons - a bit like having a panel of scientists sitting at the front of the classroom answering questions, except it's on-line. Ask allows the children to submit their questions through the web page for the scientists to answer in their own time. Both types of engagement are moderated by the good people who run I'm a Scientist.

Why then - if I'm a Scientist is so wonderful (which it is) - was I relieved to be evicted? Well, it's because after nearly 2 weeks the questions just keep coming and trying to keep up (especially given that we all have day jobs) became, if I'm completely honest, something of a test of endurance. Not counting the live chat school sessions I answered about 175 questions altogether. Other I'm a Scientist scientists who read this will scoff and say "pah, only 175!". And they'd be right - Sarah Thomas in my zone answered over 300 questions, and the awesome David Pyle in the potassium zone around 600! But even my paltry 175 questions took I reckon about 30 hours to answer, at an average 10 minutes per question (which is going fast).

But I'm not going to whinge here about my inability to keep up (although I do strongly advise future I'm a Scientists to set aside plenty of question answering time). I really want to reflect on the questions themselves. Firstly I was slightly surprised there were so few on my specialist subject of robotics. Only 22 out of the 175. But they were good ones! Here are some of my favourites:

• Do you think that us humans could ever start turning like robots and get all high tech like robots?
• Do you believe truly that robots can be just like a human? Do they have all of the 5 senses?
• Would it be possible to train/build a robot that is able to fight in wars?
• Will your research help understand how our brain works?

Some of these will form the basis of future blog posts. But it was the general science questions that were the most interesting, for instance:

• Do you think the idea of a graviton is stupid? 
• How likely is it that there are other life forms like us?
• Atoms and particles act in probabilistic ways and our brain is made up of atoms and particles, so is there such thing as free will?

Brilliant - it was a kind of science soap box! I got to pontificate on life on Mars, the end of the world and human extinction, global warming, nuclear power, dreams, light years, my favourite animal, my favourite car, string theory, the Higgs Boson and dark matter. But the non-science questions make you stop and think - hmm how much do I want to reveal about what I think about antidisestablishmentarianism, my religous beliefs, resurrection or the meaning of life..?

By far the biggest category of questions was about doing science: why and how you do science, what's the best thing about being a scientist, what you think you have achieved, or will achieve and so on (and quite a few on what you will do with the prize money if you win). These are great questions because they allow you to explode some myths about science: for instance that you have to be super smart to do science, or that one scientist can change the world on their own. I was especially flattered by

• You seem like the elder of the Science-Group - do you think knowledge come with experience?

If you're thinking of putting yourself forward for I'm a Scientist I would say yes go for it. It's hugely good fun and massively worthwhile. But (1) set aside plenty of time, (2) be prepared to answer questions on more or less anything and (3) be honest about yourself and what you really think about stuff.

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Here are some great blog posts from other March 2011 I'm a Scientists:
Suzie Sheehy's Reflections on I'm a Scientist
David Pyle's I'm a Scientist: 600 questions later
Eoin Lettice's I'm a Scientist and I'm out of here

Dilemmas of an ethical consumer

I have a dilemma and it is this. I'm torn between lusting after an iPad 2 and serious worries over the ethics of its manufacture.

There's no doubt that the iPad is a remarkable device (Jobs' hyperbole about magical and revolutionary is quite unnecessary). Several academic friends have told me that the iPad and one application in particular - called iAnnotate - has changed their working lives. Having seen them demonstrate iAnnotate there's no doubt it's the academic's killer iPad app. You see, something we have to do all the time is read, review and edit papers, book chapters, grant applications and working documents. For me that normally means printing a paper out, writing all over it, then either tediously scanning the marked up pages - uploading them to Google docs - then emailing the link, or constructing a large email with a list of all my changes and comments. What my friends showed me was them reviewing a paper on the iPad, writing all over it with a stylus, then just emailing back the marked up document. Amazing - this could save me hours every week.

But here's the problem. The iPad may well be a marvel of design and technology but - like most high tech stuff these days - it's profoundly unsustainable and it's manufacture is ethically questionable. Now to be fair to Apple, this is not a problem that's unique to them - and I'm prepared to believe that Apple does genuinely care about the conditions under which it's products are manufactured and is doing all it can to pressure it's subcontractors to provide the best working conditions for their employees. But the problem is systemic - the only reason that we can buy an iPad, or laptop, or flat screen TV, or any number of consumer electronics products for a few hundred pounds is that they're manufactured in developing countries where labour is cheap and working conditions are a million miles from what we would regard as acceptable. And I'm not even going to start here about the sustainability of those products - in terms of the true energy costs, and costs to the environment, of their manufacture during incredibly complex supply chains, or the environmental costs of their disposal after we've finished with them.

This may sound odd given that I'm a professional electronics engineer and elder-nerd. But I'm a late adopter of new technology. Always have been. (My excuse is that I was an early adopter of the transistor.) I also keep stuff for a very long time. My Hi-Fi system is 25 years old and is working just fine. My car is now 6 years old and I fully expect to run it for another 10 years - a modern well-built and maintained car can easily last for 250,000 miles. The most recent high tech thing I bought was a new electric piano. It replaced my old one, bought in 1983, which had become unplayable because the mechanics of the keys had worn out and I fully expect to keep my beautiful new Roland piano for 25 years. My MacBook pro (yes I do like Apple stuff) is now 5 years old and works just fine - not bad for something that's probably had 10,000 hours use. In short I aim to practice what's sometimes called Bangernomics - except I try and apply the philosophy to everything, not just cars. (I'm not exactly a model consumer.)

Maybe that's part of the answer to my dilemma - get an iPad and run it for 20 years..? But even applying Bangernomics still won't salve my conscience when it comes to the ethics or sustainability of its manufacture. So, what am I to do?

Making sense of robots: the hermeneutic challenge

One of the challenges of the artificial culture project that we knew we would face from the start is that of making sense of the free running experiments in the lab. One of the project investigators - philosopher Robin Durie - called this the hermeneutic challenge. In the project proposal Robin wrote:

what means will we be able to develop by which we can identify/recognise meaningful/cultural behaviour [in the robots]; and, then, what means might we go on to develop for interpreting or understanding this behaviour and/or its significance?

Now, more than 3 years on, we come face to face with that question. Let me clarify: we are not - or at least not yet - claiming to have identified or recognised emerging robot culture. We do, however, more modestly claim to have demonstrated new behavioural patterns (memes) that emerge and - for awhile at least - are dominant. It's an open-ended evolutionary process in which the dominant 'species' of memes come and go. Maybe these clusters of closely related memes could be labelled behavioural traditions?

Leaving that speculation aside, a more pressing problem in recent months has been to try and understand how and why certain behavioural patterns emerge at all. Let me explain. We typically seed each robot with a behavioural pattern; it is literally a sequence of movements. Think of it as a dance. But we choose these initial dances arbitrarily - movements that describe a square or triangle for instance - without any regard whatsoever for whether these movement sequences are easy or hard for the robots to imitate.

Not surprisingly then, the initial dances quickly mutate to different patterns, sometimes more complex and sometimes less. But what is it about the robot's physical shape, its sensorium, and the process of estimation inherent in imitation that gives rise to these mutations? Let me explain why this is important. Our robots and you, dear reader, have one thing in common: you both have bodies. And bodies bring limitations: firstly because you body doesn't allow you to make any movement imaginable - only ones that your shape, structure and muscles allow, and secondly because if you try to watch and imitate someone else's movements you have to guess some of what they're doing (because you don't have a perfect 360 degree view of them). That's why your imitated copy of someone else's behaviour is always a bit different. Exactly the same limitations give rise to variation in imitated behaviours in the robots.

Now it may seem a relatively trivial matter to watch the robots imitate each other and then figure out how the mutations in successive copies (and copies of copies) are determined by the robots' shape, sensors and programming. But it's not, and we find ourselves having to devise new ways of visualising the experimental data in order to make sense of what's going on. The picture below is one such visualisation; it's actually a family tree of memes, with parent memes at the top and child memes (i.e. copies) shown branching below parents.

Unlike a human family tree each child meme has only one parent. In this 'memeogram' there are two memes at the start, numbered 1 and 2. 1 is a triangle movement pattern, and 2 is a square movement pattern. In this experiment there are 4 robots, and it's easy to see here that the triangle meme dominates - it and its descendants are seen much more often.

The diagram also shows which child-memes are high quality copies of their parents - these are shown in brown with bold arrows connecting them to their parent-memes. This allows us to easily see clusters of similar memes, for instance in the bottom-left there are 7 closely related and very similar memes (numbered 36, 37, 46, 49, 50, 51 and 55). Does this cluster represent a dominant 'species' of memes?

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Also posted on the Artificial Culture project blog.