Month: June 2025

An AI Oppenheimer Moment?

A nuclear explosion mushroom cloud
Image by Harsh Ghanshyam from Pixabay

All computer scientists should watch the staggeringly good film, Oppenheimer, by Christopher Nolan. It charts the life of J. Robert Oppenheimer, “father of the atom bomb”, and the team he put together at Los Alamos, as they designed and built the first weapons of mass destruction. The film is about science, politics and war, not computer science and all the science is quantum physics (portrayed incredibly well). Despite that, Christopher Nolan believes the film does have lessons for all scientists, and especially those in Silicon Valley.

Why? In an interview, he suggested that given the current state of Artificial Intelligence the world is at “an Oppenheimer moment”. Computer scientists, in the 2020s, just like physicists in the 1940s, are creating technology that could be used for great good but also cause great harm (including in both cases a possibility that we use it in a way that destroys civilisation). Should scientists and technologists stay outside the political realm and leave discussion of what to do with their technology to politicians, while the scientist do as they wish in the name of science? That leaves society playing a game of catch up. Or do scientists and technologists have more responsibility than that?

Artificial Intelligence isn’t so obviously capable of doing bad things as an atomic bomb was and still clearly is. There is also no clear imperative, such as Oppenheimer had, to get there before the fascist Nazi party, who were clearly evil and already using technology for evil, (now the main imperative seems to be just to get there before someone else makes all the money, not you). It is, therefore, far easier for those creating AI technology to ignore both the potential and the real effects of their inventions on society. However, it is now clear AI can and already is doing lots of bad as well as good. Many scientists understand this and are focussing their work on developing versions that are, for example, built in to be transparent and accountable, are not biased, racist, homophobic, … that do put children’s protection at the heart of what they do… Unfortunately, not all are though. And there is one big elephant in the room. AI can be, and is being, put in control of weapons in wars that are actively taking place right now. There is an arms race to get there before the other side do. From mass identification of targets in the middle East to AI controlled drone strikes in the Ukraine war, military AI is a reality and is in control of killing people with only minimal, if any, real human’s in the loop. Do we really want that? Do we want AIs in control of weapons of mass destruction. Or is that total madness that will lead only to our destruction.

Oppenheimer was a complex man, as the film showed. He believed in peace but, a brilliant theoretical physicist himself, he managed a group of the best scientists in the world in the creation of the greatest weapon of destruction ever built to that point, the first atom bomb. He believed it had to be used once so that everyone would understand that all out nuclear war would end civilisation (it was of course used against Japan not the already defeated Nazis, the original justification). However, he also spent the rest of his life working for peace, arguing that international agreements were vital to prevent such weapons ever being used again. In times of relative peace people forget about the power we have to destroy everyone. The worries only surface again when there is international tension and wars break out such as in the Middle East or Ukraine. We need to always remeber the possibility is there though lest we use them by mistake. Oppenheimer thought the bomb would actually end war, having come up with the idea of “mutually assured destruction” as a means for peace. The phrase aimed to remind people that these weapons could never be used. He worked tirelessly, arguing for international regulation and agreements to prevent their use. 

Christopher Nolan was asked, if there was a special screening of the film in Silicon Valley, what message would he hope the computer scientists and technologists would take from it. His answer was that the should take home the message of the need for accountability. Scientists do have to be accountable for their work, especially when it is capable of having massively bad consequences for society. A key part of that is engaging with the public, industry and government; not with vested interests pushing for their own work to be allowed, but to make sure the public and policymakers do understand the science and technology so there can be fully informed debate. Both international law and international policy is now a long way off the pace of technological development. The willingness of countries to obey international law is also disintegrating and there is a new subtle difference to the 1940s: technology companies are now as rich and powerful as many countries so corporate accountability is now needed too, not just agreements between countries.

Oppenheimer was vilified over his politics after the war, and his name is now forever linked with weapons of mass destruction. He certainly didn’t get everything right: there have been plenty of wars since, so he didn’t manage to end all war as he had hoped, though so far no nuclear war. However, despite the vilification, he did spend his life making sure everyone understood the consequences of his work. Asked if he believed we had created the means to kill tens of millions of Americans (everyone) at a stroke, his answer was a clear “Yes”. He did ultimately make himself accountable for the things he had done. That is something every scientist should do too. The Doomsday Clock is closer to midnight than ever (89s to midnight – manmade global catastrophe). Let’s hope the Tech Bros and scientists of Silicon Valley are willingly to become accountable too, never mind countries. All scientists and technologists should watch Oppenheimer and reflect.

– Paul Curzon, Queen Mary University of London

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Dr Who? Dr You???

Image by Eduard Solà, CC BY-SA 3.0 https://creativecommons.org/licenses/by-sa/3.0, via Wikimedia Commons

When The Doctor in Dr Who knows their time is up – usually because they’ve been injured so badly that they are dying – like all Time Lords, they can regenerate. They transform into a completely different body. They ends up with a new personality, new looks, a new gender, even new teeth. Could humans one day regenerate too?

Your body is constantly regenerating itself too. New cells are born to replace the ones that die. Your hair, nails and skin are always growing and renewing. Every year, you lose and regain so much that you could make a pile of dead cells that would weigh the same as your body. And yet with all this change, every morning you look in the mirror and you look and feel the same. No new personality, no new teeth. How does the human body keep such incredible control?

Here’s another puzzler. Even though our cells are always being renewed, you can’t regrow your arm if it gets cut off. We know it’s not impossible to regrow body parts: we do it for small things like cells, including whole toe nails and some animals like lizards can regrow tails. Why can we regrow some things but not others?

Creation of the shape

All of those questions are part of a field in biology called morphogenesis. The word is from Greek, and it means ‘creation of the shape’. Scientists who study morphogenesis are interested in how cells come together to create bodies. It might sound a long way from computing, but Alan Turing became interested in morphogenesis towards the end of his life. He was interested in finding out about patterns in nature – and patterns were something he knew a lot about as a mathematician. A paper he wrote in 1951 described a way that Turing thought animals could form patterns like stripes and spots on their bodies and in their fur. The mechanisms he described explain how uniform cells could end up turning into different things so not only different patttens in different places, but different body parts in different places. That work is now the foundation of a whole sub-discipline of biology.

Up for the chop

Turing died before he could do much work on morphogenesis, but lots of other scientists have taken up the mantle. One of them is Alejandro Sánchez Alvarado, who was born in Venezuela but works at the Stowers Institute for Medical Research in Kansas City, in the US. He is trying to get to the bottom of questions like how we regenerate our bodies. He thinks that some of the clues could come from working on flatworms that can regenerate almost any part of their body. A particular flatworm, called Schmidtea mediterranea, can regenerate its head and its reproductive organs. You can chop its body into almost 280 pieces and it will still regenerate.

A genetic mystery

The funny thing is, flatworms and humans aren’t as different as you might think. They have about the same number of genes as us, even though we’re so much bigger and seemingly more complicated. Even their genes and ours are mostly the same. All animals share a lot of the same, ancient genetic material. The difference seems to come from what we do with it. The good news there is that as the genes are mostly the same, if scientists can figure out how flatworm morphogenesis works, there’s a good chance that it will tell us something about humans too.

One gene does it all

Alejandro Sánchez Alvarado did one series of experiments on flatworms where he cut off their heads and watched them regenerate. He found that the process looked pretty similar to watching organs like lungs and kidneys grow in humans as well as other animals. He also found that there was a particular gene that, when knocked out, takes away the flatworm’s ability to regenerate.

What’s more, he tried again in other flatworms that can’t normally regenerate whole body parts – just cells, like us. Knocking out that gene made their organs, well, fall apart. That meant that the organs that fell apart would ordinarily have been kept together by regrowing cells, and that the same gene that allows for cell renewal in some flatworms takes care of regrowing whole bodies, Dr Who-style, in others. Phew. A lot of jobs for one gene.

Who knows, maybe Time Lords and humans share that same gene too. They’re like the lucky, regenerating flatworms and we’re the ones who are only just keeping things together. But if it’s any consolation, at least we know that our bodies are constantly working hard to keep us renewed. We still regenerate, just in a slightly less spectacular way.

– the CS4FN team (updated from the archive)

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How did the zebra get its stripes?

Head of a fish with a distinctive stripy, spotty pattern
Image by geraldrose from Pixabay

There are many myths and stories about how different animals gained their distinctive patterns. In 1901, Rudyard Kipling wrote a “Just So Story” about how the leopard got its spots, for example. The myths are older than that though, such as a story told by the San people of Namibia (and others) of how the zebra got its stripes – during a fight with a baboon as a result of staggering through the baboon’s fire. These are just stories. It was a legendary computer scientist and mathematician, who was also interested in biology and chemistry, who worked out the actual way it happens.

Alan Turing is one of the most important figures in Computer Science having made monumental contributions to the subject, including what is now called the Turing Machine (giving a model of what a computer might be before they existed) and the Turing Test (kick-starting the field of Artificial Intelligence). Towards the end of his life, in the 1950s, he also made a major contribution to Biology. He came up with a mechanism that he believed could explain the stripy and spotty patterns of animals. He has largely been proved right. As a result those patterns are now called Turing Patterns. It is now the inspiration for a whole area of mathematical biology.

How animals come to have different patterns has long been a mystery. All sorts of animals from fish to butterflies have them though. How do different zebra cells “know” they ultimately need to develop into either black ones or white ones, in a consistent way so that stripes (not spots or no pattern at all) result, whereas leopard cells “know” they must grow into a creature with spots. They both start from similar groups of uniform cells without stripes or spots. How do some that end up in one place “know” to turn black and others ending up in another place “know” to turn white in such a consistent way?

There must be some physical process going on that makes it happen so that as cells multiply, the right ones grow or release pigments in the right places to give the right pattern for that animal. If there was no such process, animals would either have uniform colours or totally random patterns.

Mathematicians have always been interested in patterns. It is what maths is actually all about. And Alan Turing was a mathematician. However, he was a mathematician interested in computation, and he realised the stripy, spotty problem could be thought of as a computational kind of problem. Now we use computers to simulate all sorts or real phenomena, from the weather to how the universe formed, and in doing so we are thinking in the same kind of way. In doing this, we are turning a real, physical process into a virtual, computational one underpinned by maths. If the simulation gets it right then this gives evidence that our understanding of the process is accurate. This way of thinking has given us a whole new way to do science, as well as of thinking more generally (so a new kind of philosophy) and it starts with Alan Turing.

Back to stripes and spots. Turing realised it might all be explained by Chemistry and the processes that resulted from it. Thinking computationally he saw that you would get different patterns from the way chemicals react as they spread out (diffuse). He then worked out the mathematical equations that described those processes and suggested how computers could be used to explore the ideas.

Diffusion is just a way by which chemicals spread out. Imagine dropping some black ink onto some blotting paper. It starts as a drop in the middle, but gradually the black spreads out in an increasing circle until there is not enough to spread further. The expanding circle stops. Now, suppose that instead of just ink we have a chemical (let’s call it BLACK, after its colour), that as it spreads it also creates more of itself. Now, BLACK will gradually uniformly spread out everywhere. So far, so expected. You would not expect spots or stripes to appear!

Next, however, let’s consider what Turing thought about. What happens if that chemical BLACK produces another chemical WHITE as well as more BLACK? Now, starting with a drop of BLACK, as it spreads out, it creates both more BLACK to spread further, but also WHITE chemicals as well. Gradually they both spread. If the chemicals don’t interact then you would end up with BLACK and WHITE mixed everywhere in a uniform way leading to a uniform greyness. Again no spots or stripes. Having patterns appear still seems to be a mystery.

However, suppose instead that the presence of the WHITE chemical actually stops BLACK creating more of itself in that region. Anywhere WHITE becomes concentrated gets to stays WHITE. If WHITE spreads (ie diffuses) faster than BLACK then it spreads to places first that become WHITE with BLACK suppressed there. However, no new BLACK leads to no more new WHITE to spread further. Where there is already BLACK, however, it continue to create more BLACK leading to areas that become solid BLACK. Over time they spread around and beyond the white areas that stopped spreading and also create new WHITE that again spreads faster. The result is a pattern. What kind of pattern depends on the speed of the chemical reactions and how quickly each chemical diffuses, but where those are the same because it is the same chemicals the same kind of pattern will result: zebras will end up with stripes and leopards with spots.

This is now called a Turing pattern and the process is called a reaction-diffusion system. It gives a way that patterns can emerge from uniformity. It doesn’t just apply to chemicals spreading but to cells multiplying and creating different proteins. Detailed studies have shown it is the mechanism in play in a variety of animals that leads to their patterns. It also, as Alan Turing suggested, provides a basis to explain the way the different shapes of animals develop despite starting from identical cells. This is called morphogenesis. Reaction-diffusion systems have also been suggested as the mechanism behind how other things occur in the natural world, such as how fingerprints develop. Despite being ignored for decades, Turing’s theory now provides a foundation for the idea of mathematical biology. It has spawned a whole new discipline within biology, showing how maths and computation can support our understanding of the natural world. Not something that the writers of all those myths and stories ever managed.

– Paul Curzon, Queen Mary University of London

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If you go down to the woods today…

A girl walking through a meadow full of flowers within woods
Image by Jill Wellington from Pixabay

In the 2025 RHS Chelsea Flower Show there was one garden that was about technology as well as plants: The Avanade Intelligent Garden  exploring how AI might be used to support plants. Each of the trees contained probes that sensed and recorded data about them which could then be monitored through an App. This takes pioneering research from over two decades ago a step further, incorporating AI into the picture and making it mainstream. Back then a team led by Yvonne Rogers built an ambient wood aiming to add excitement to a walk in the woods...

Mark Weiser had a dream of ‘Calm Computing’ and while computing sometimes seems ever more frustrating to use, the ideas led to lots of exciting research that saw at least some computers disappearing into the background. His vision was driven by a desire to remove the frustration of using computers but also the realization that the most profound technologies are the ones that you just don’t notice. He wanted technology to actively remove frustrations from everyday life, not just the ones caused by computers. He wrote of wanting to “make using a computer as refreshing as taking a walk in the woods.”

Not calm, but engaging and exciting!

No one argues that computers should be frustrating to use, but Yvonne Rogers, then of the Open University, had a different idea of what the new vision could be. Not calm. Anything but calm in fact (apart from frustrating of course). Not calm, but engaging and exciting!

Her vision of Weiser’s tranquil woods was not relaxing but provocative and playful. To prove the point her team turned some real woods in Sussex into an ‘Ambient Wood’. The ambient wood was an enhanced wood. When you entered it you took probes with you, that you could point and poke with. They allowed you to take readings of different kinds in easy ways. Time hopping ‘Periscopes’ placed around the woods allowed you to see those patches of woodland at other times of the year. There was also a special woodland den where you could then see the bigger picture of the woods as all your readings were pulled together using computer visualisations.

Not only was the Ambient Wood technology visible and in your face but it made the invisible side of the wood visible in a way that provoked questions about the wildlife. You noticed more. You saw more. You thought more. A walk in the woods was no longer a passive experience but an active, playful one. Woods became the exciting places of childhood stories again but now with even more things to explore.

The idea behind the Ambient Wood, and similar ideas like Bristol’s Savannah project, where playing fields are turned into African Savannah, was to revisit the original idea of computers but in a new context. Computers started as tools, and tools don’t disappear, they extend our abilities. Tools originally extended our physical abilities – a hammer allows us to hit things harder, a pulley to lift heavier things. They make us more effective and allow us to do things a mere human couldn’t do alone. Computer technology can do a similar thing but for the human intellect…if we design them well.

“The most important thing the participants gained was a sense of wonderment at finding out all sorts of things and making connections through discovering aspects of the physical woodland (e.g., squirrel’s droppings, blackberries, thistles)”

– Yvonne Rogers

The Weiser dream was that technology invisibly watches the world and removes the obstacles in the way before you even notice them. It’s a little like the way servants to the aristocracy were expected to always have everything just right but at the same time were not to be noticed by those they served. The way this is achieved is to have technology constantly monitoring, understanding what is going on and how it might affect us and then calmly fixing things. The problem at the time was that it needs really ‘smart’ technology – a high level of Artificial Intelligence to achieve and that proved more difficult than anyone imagined (though perhaps we are now much closer than we were). Our behaviour and desires, however, are full of subtlety and much harder to read than was imagined. Even a super-intellect would probably keep getting it wrong.

There are also ethical problems. If we do ever achieve the dream of total calm we might not like it. It is very easy to be gung ho with technology and not realize the consequences. Calm computing needs monitors – the computer measuring everything it can so it has as much information as possible to make decisions from (see Big Sister is Watching You).

A classic example of how this can lead to people rejecting technology intended to help is in a project to make a ‘smart’ residential home for the elderly. The idea was that by wiring up the house to track the residents and monitor them the nurses would be able to provide much better care, and relatives be able to see how things were going. The place was filled with monitors. For example, sensors in the beds measured resident’s weight while they slept. Each night the occupants weight could invisibly be taken and the nurses alerted of worrying weight loss over time. The smart beds could also detect tossing and turning so someone having bad nights could be helped. A smart house could use similar technology to help you or I have a good nights sleep and help us diet.

The problem was the beds could tell other things too: things that the occupants preferred to keep to themselves. Nocturnal visitors also showed up in the records. That’s the problem if technology looks after us every second of the day, the records may give away to others far more than we are happy with.

Yvonne’s vision was different. It was not that the computers try to second-guess everything but instead extend our abilities. It is quite easy for new technology to lead to our being poorer intellectually than we were. Calculators are a good example. Yes, we can do more complex sums quickly now, but at the same time without a calculator many people can’t do the sums at all. Our abilities have both improved and been damaged at the same time. Generative AI seems to be currently heading the same way, What the probes do, instead, is extend our abilities not reduce them: allowing us to see the woods in a new way, but to use the information however we wish. The probes encourage imagination.

The alternative to the smart house (or calculator) that pampers allowing your brain to stay in neutral, or the residential home that monitors you for the sake of the nurses and your relatives, is one where the sensors are working for you. Where you are the one the bed reports to helping you to then make decisions about your health, or where the monitors you wear are (only) part of a game that you play because its fun.

What next? Yvonne suggested the same ideas could be used to help learning and exploration in other ways, understanding our bodies: “I’d like to see kids discover new ways of probing their bodies to find out what makes them tick.”

So if Yvonne’s vision is ultimately the way things turn out, you won’t be heading for a soporific future while the computer deals with real life for you. Instead it will be a future where the computers are sparking your imagination, challenging you to think, filling you with delight…and where the woods come alive again just as they do in the storybooks (and in the intelligent garden).

– Paul Curzon, Queen Mary University of London

(adapted from the archive)

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