The Wild (emotional) Robot

[Spoiler Alert]

A robot head, after Roz with only two circular eyes.
Robot head image by CS4FN

If you are in the business of designing robots for the coming, personal robot dominated world, who would you employ? Robotics engineers naturally, AI experts, computer scientists … and of course artists, animators, actors and film makers! Why the latter? Well, they have been designing robots far longer than either robotics engineering or computer science has even existed as a career. What they might add is illustrated (literally) in the animated film ‘The Wild Robot.’

The Wild Robot tells the story of a newly dispatched personal robot, ROZZUM Unit 7134 or “Roz”, that is shipwrecked in a storm on a remote wilderness island. Looking for a task to do to justify its existence, it unexpectedly finds itself having to learn how to be a mother. This is not part of its training. However, it is adaptable. It starts the film very robotic but gradually, as it teaches itself more about its new role, it develops much more human-like emotions. After all a first requirement of any parent is to show love. The film is as much about Roz’s journey learning and reprogramming itself to be emotional as the actual story.

So, suppose you are designing a robot to show human emotions, where would you start…with a programmable mouth probably. After all, happiness, sadness and lots more are all there in the mouth. Then you would want eyes that can change shape, eyebrows, and then, to really get it right, something in place of all those muscles in our faces that give us the ability to show micro-emotions.

So what did the film makers give Roz? Two big circular eyes that are cameras and … nothing much else. No face, no nose, no eyebrows, no muscles to move in the face at all. Just some lines of LEDs that can change colour. And yet, it is very clear throughout the film that Roz is becoming gradually more emotional, and exactly what emotions they are feeling. This was something director Chris Sanders was explicitly after. He wanted something much more than a 2-dimensional robot switching from being robotic to being human-like and that is what the film delivers. It has even been praised by critics for its “emotional depths”.

Emotions of course are not the same as facial expressions. We can understand the emotions of others through expression but through lots of other means too, including gestures (like slumping and arm movements) and tone of voice. It is easy to program a robotic face with mouth and eyes etc to show different expressions but that of course does not mean the robot shows emotions, any more than carving a pumpkin to smile means it is happy! However, humans are easily fooled and naturally attach emotions to things that show expressions we recognize. We also use it to help us understand others, so if robots are to live with us it probably needs to fake emotions somehow (assuming it doesn’t actually feel anything). If a robotics company wants us to feel comfortable around robots, and live with them happily, they need to get this right. As the film shows, that doesn’t just mean making robots that are impossible to distinguish from humans (and that approach has risks as unless you make it really, really accurate you hit what is called the “uncanny valley” where what we see are zombie like monsters rather than pleasant companions).

A lot of Roz’s emotions come from the brilliant voice acting of Lupita Nyong’o, who plays Roz. She gradually changes the way she voices Roz through the film. It isn’t a sudden switch but a gradual change you hardly notice. The artists and animators also put an enormous amount of time into developing Roz too. In the story, Roz, gradually reprograms herself based on her ability to mimic others. In terms of animation, the robot uses more and more human-like gestures but also gradually uses those LEDS more and more to show different emotional states, both in the way they flash and in changing colour between red and blue. That was something the animators improvised , using what they had, rather than the plan from the start. This mirrors ideas in Ian M. Banks Culture novels where robot AIs show emotional states through wide use of coloured lights.

We could move towards a world of everyday, everywhere robots that look robotic and emotion-less, or one where they mimic humans with exact copies of the way humans show emotions, Blade Runner style, but much more interesting would be one where, as with Roz, they are clearly something else: where they have their own language to express emotions, that helps us understand them. As the film-makers have shown, wide emotional range can be shown in many subtle but different ways. Time to recruit some artists, film-makers and actors to your robotics start-up if your robots are going to stand out from the crowd?

Paul Curzon, Queen Mary University of London

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Ringing the changes

Image by lidago from Pixabay

Like a mystic Dr Strange-like superhero, whose simple hand gestures make the world around them spring to life, the Zero Ring, makes things happen.

It may sound like it’s part of an infinity gauntlet, but it actually contains motion sensors that track how your hand moves around. Linked by Bluetooth to your mobile phone, this gesture signal is compared with template gestures saved in the phone. If they match then the phone sends a message to make something useful happen. One gesture might cause your smart-enabled light bulb to turn on. Another might turn the central heating up a notch. Critically, the ring has an on-off switch to prevent it working when you don’t want it to! After all you don’t want all your hand movements to be tracked and so control things all the time.

This wearable tech is one of the first consumer goods to be operated by recognising simple gestures as orders. As the technology progresses, more complex hand patterns will be possible opening up whole new ways to interact.

Just don’t have it switched on when you are having a scratch … or your personal universe might just collapse by mistake.

Peter W McOwan, Queen Mary University of London

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Audio illusions: music on repeat

Cat listening, image by Monic Heinen from Pixabay

All too often things get repetitive. Songs in the chart repeat their lyrics, comedy catchphrases begin to jar and friends can keep saying the same things over and over again. But strange things can happen when speech is repeated; yes when speech is repeated we can find it begins to sound like music. You can’t believe everything you hear!

American speech researcher Diana Deutsch discovered this strange speech to music illusion by accident one day when she was editing a spoken sound track. She had the phrase ‘sometimes behave so strangely’ on a loop, and noticed that after a short while the spoken words sounded as if they were being sung. She experimented with changing the way the phrase was played and found that the change from speech to song only happened when the phrase was repeated exactly and regularly. So it seems that the way our brain processes sound to perceive whether it is a song or speech requires that the sound have particular characteristics. However, if we set it up correctly we can fool the brain into thinking that speech has some of the characteristics of a song.

If I didn’t say that, who did?

Diana has been responsible for uncovering and exploring many of the strange ways our ears and brain play word tricks on us. Another illusion she discovered is a way that phantom words emerge from a babble of other words. It sounds a little spooky, but it’s one of the illusions our auditory cortex, the part of the brain near our ears, can be tricked by. If you listen to a sequence of stereo overlapping repeating words and phrases, your brain starts to try and make sense of them. The auditory cortex’s task is to make sense of the sounds arriving so even if it’s a jumble it will work hard to pull something from the racket. The illusionary words that you hear are often dependent on what you’re thinking about at the time, so if you are hungry you may hear words related to food. It’s quite a creepy experience just before lunch. This strange phenomena is called the ‘phonemic restoration effect’, phonemes being the component sound that make up words.

Hearing like a human

One strand of computer science aims to understand how the brain works by creating computer models that do the same thing. These kinds of illusions, both optical and auditory give good test cases. If you really understand how humans hear then you should be able to create programs that allow computers to hear the same way. If you get it right then the programs should be fooled in the same way that humans are and hear the same illusions. The fact that we hear sounds based on what we are thinking means to truly create a computer that hears like a human, you need to have modelled our thought processes too!

Hearing like a human is a lot harder than just recording sounds.

Peter McOwan and Paul Curzon, Queen Mary University of London

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Your Chair is Watching You

Image by Alexa from Pixabay

QMUL’s Sophie Skach is interested in both textiles and computers. In a recent summer project she explored how much your chair could tell about you.

When sitting talking, we change postures a lot, and maybe that gives vital clues to what is actually happening when groups of people are talking. By embedding sensors in the fabric of a chair, perhaps it can tell something about the social roles involved – who is dominant in the conversation, who is passive, who is speaking, who is listening, who isn’t. Intelligence starts with being able to sense the world, so sytems like this may one day help make computers more intelligent, making it easier for them to work out, unobtrusively, the nuances of what we humans are up to.

One day soon your chair may be keeping an eye on you!

Paul Curzon, Queen Mary University of London

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Babbage: making money through game AI

A game of noughts and crosses
Image by Clker-Free-Vector-Images from Pixabay

Victorian Innovator, Charles Babbage, had big ideas. He intended to build the first ever general purpose computer, despite living in the age of steam and cogs. But he needed money to do it, and he didn’t have any. He was also notorious for alienating those who invested money in his schemes. He needed a new source of income. Perhaps he could do it through games?

He came up with the idea of building a less ‘serious’ money making machine that would capture the imagination and part people with their money as a curiositiy. His big idea was to design a machine that could play Noughts and Crosses (called at the time Tit-Tat-To) and so also create the first AI game playing machine.

He had previously used game playing (and specifically Chess) as a theoretical demonstration of his argument that machines, such as his proposed Analytical Engine, would be able to do things that were thought at the time to need human reasoning. He even did a mini-survey asking “the opinions of persons in every class of life and of all ages” to find out if people believed that playing games of skill needed human reasoning (the answer was overwhelmingly, yes!) He therefore set about analysing games, and specifically Noughts and Crosses as the simplest such game of skill that he knew.

Having seen that the number of states of the game (possible positions) of Noughts and Crosses was well within the scope of what his proposed machines could handle, he started to think more seriously about actually building one. His reasoning was that by exhibiting it and charging people to play against it, he would raise enough money to fund the completion of the Analytical Engine. After all, he thought, if it could even beat the parents at a child’s game, then any parent would want to take their child to see it.

He even thought about fun, decorative automata details such as:

“I imagined that the machine might consist of the figures of two children playing against each other, accompanied by a lamb and a cock. That the child who won the game might clap his hands whilst the cock was crowing, after which, that the child who was beaten might cry and wring his hands whilst the lamb began bleating.”

He worked out the design of the machine in general terms, determining different mechanisms that could be used and noting that they it would be far simpler than the Analytical Engine itself. A specific issue he worked on was how the machine should make a choice when two equally good options were possible as he didn’t want the machine to be predictable. He came up with the solution that it could keep a record of how many times it had won so far and use that number to make the choice between moves, so use a simple version of pseudo-randomness. An even number of wins so far meant do option 1 and an add number eant do option 2. If there were three options it would take the remainder when dividing by three. He thought that this would be opaque enough that noone watching it play would work out how it was deciding where to go. He noted that this engineering design nicely illustrated definitions of chance given by philosophers

“Chance is but the expression of man’s ignorance.” – Laplace

and poets

“All chance, design ill understood.” – Pope

Sadly, before building it, when doing his equivalent of working on the business case, he discovered others had tried making money from machines. Both a machine that made Latin verse, and another that talked had failed to make money. Combined with the time it would take him to build it, he therefore gave up on the whole money-making idea. 

Perhaps if he had just had more faith in people’s interest in games (over Latin!) it would have been a success and he might have raised the money to successfully build the first computer 100 years before it eventually happened. Now, of course, the computer games industry is worth billions! (The Latin verse industry is not so strong, though of course Generative AIs are now writing poems, in living languages like English, to people’s delight, if not yet making money from doing so!)

Now, what might I build to fund my research? Donations welcome!

Paul Curzon, Queen Mary University of London

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William Kamkwamba: The boy who harnessed the wind

William’s wind turbine made from local wood, scrap metal and a destroyed bicycle by CS4FN

[SPOILER ALERT]

“The boy who harnessed the wind” is a new musical from the Royal Shakespeare Company that tells the inspiring story of teenage innovator William Kamkwamba, based on his autobiography of the same name. As a young teenager he helped save his African village from famine by working out how to build a windmill to generate electricity from scrap, that might ultimately pump water to irrigate the crops.

William grew up in the village of Wimbe in Malawi, at a time when magic was still present in people’s lives and few had electricity or running water. Drought killed, and disease was rife. He, however, was obsessed with gadgets and working out how they worked. He was especially intrigued by the dynamo on a bike and how rather than just using electricity, it created it. It generated electricity that could be used to power other things.

Unfortunately, his family were too poor to pay the fees so he was forced to leave his village school aged only 14. He was left having to learn what he could from the books he could get hold of and his own tinkering.

A famine followed with crops failing and there being too little grain produced to feed the village to last through the winter. However, he had an idea, having read a book about western wind power. There was plenty of wind in Malawi, so if he could build a windmill connected to a dynamo, the power it generated could drive a water pump to irrigate crops, allowing a second planting even in the dry season.

With no one to teach him he had to work out the science himself from books, and overcome the engineering problems on his own. Also, all he had to make it from was scrap metal, local wood and broken gadgets. To make things even harder for a long time few in the village believed he was anything but a mad dreamer, mocking him rather than helping. His family also needed him to help work on the farm just to survive in the short term.

However, he was determined he could make his idea work if only he could solve the problems using scrap parts. The book and musical (and linked film) tell the story of his village’s struggle with famine and his struggle to be believed.

Ultimately, he made a wind turbine, that powered a radio, proving to everyone that the idea could work. He then used it to power other devices around their home. The story spread, leading to international fame, leading to him giving a TED talk, having his schooling paid for him and going to university in the US. With grants he gained he trained others in his village to build windmills and fix water pumps and he built a solar powered water pump for his village.

Sometimes what local communities need is simple not complex technology that meets their real needs, and empowerment for people with ideas of how to solve them. William Kamkwamba has since set up a foundation “Moving Windmills” to support innovation and the building of infrastructure in Malawi, so to do just that.

Paul Curzon, Queen Mary University of London

“The boy who harnessed the wind” is playing at Soho Place London until 18 July 2026

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Emotional glasses

Image by Km Nazrul Islam from Pixabay

It’s fun to add emoticons to messages, and they help ensure people understand our feelings. They are helping some people understand feelings face-to-face too, with a bit of help from an Artificial Intelligence.

Reading faces

We take it for granted that we can look at someone’s face and tell whether they are happy or sad, angry or surprised. Autistic children, however, often struggle to understand people’s expressions. When anxious we also all tend to avoid eye contact. Some autistic children do that all the time. They are then even less likely to see the clues in people’s faces, and so start to understand emotions. This can make it harder to make friends.

From robots to glasses

Many hi-tech ways have been tried to help autistic children learn about emotions. One, for example, involves letting them play with robot ‘friends’ as some find the cartoon-like expressions on a robot face more comfortable and easier to follow. A different approach is based on wearable technology. Researchers at Stanford University have created a program for autistic children that works out a person’s expression and displays an emoticon of it in a pair of smart glasses.

An AI reading faces for you

A camera in the glasses records what the wearer sees and the Artificial Intelligence (AI) program detects any faces. This kind of technology is also used in smartphones to detect faces in your photo collection. It uses ‘machine learning’: the program learns what a face is by being shown lots of images, some with and some without faces. The program uses all that data to work out the patterns in an image that mean there is a face. It then uses that pattern to spot new faces.

In a similar way it can be trained on faces with different expressions. A training set of faces are used that are labelled with the emotion in that image. This allows the program to spot what pattern in a face makes a happy face, what makes a sad face, and so on. Having recognised an expression, the glasses finally act as a screen and show an emoticon, such as a smiley, corresponding to that expression. Superimposing digital images on the real world like this is called augmented reality. It makes looking at faces like a game and means that the child can use the emoticon to understand what the person in front of them is feeling. It also means they can start to learn for themselves – almost like the AI! The AI is labelling the faces for them, just as people had done for it. With the glasses, autistic children can be sure what each face is actually saying rather than having to guess. Eventually they might then form their own rules and so do it on their own.

Making a difference

The Stanford system was trialled with autistic children in their own homes. They used the system for several months and their parents found it made a clear difference. By the end many of the children were engaging much more with their family including making a lot more eye contact.

Emoticons are making a real difference to their lives.

Paul Curzon, Queen Mary University of London

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Moons, maths and mystical maidens

A QMUL astronomy banner with the Moon behind it
Credit: Jo Brodie – under a Public Domain CC0 licence

Heavens above, you’ve discovered a new celestial object! What would you call it? Would you name it Clom, Skaro, Poosh, or even Raxacoricofallapatorius? Or maybe those names are already taken. This sort of thing is complicated – even when it comes to naming new planets, moons or asteroids there are rules, and the need for a bit of computer science too.

It’s not Spock

Asteroids start off being designated using the year and the month they were first detected. Only once their orbit has been correctly predicted can they then be named. Predicting the orbit needs a cosmic fusion of astronomy, physics and lots of computer processing to predict and then check they are where they should be. Choosing a name is not too easy either. Since 1971 when one astronomer named an asteroid ‘2309 Mr. Spock’ after his pet cat, the International Astronomical Union decided to ban pets’ names, but that didn’t stop some creative discoverers getting the names ‘6042 Cheshirecat’ and ‘9007 James Bond’ agreed.

Over the moon

Moons are more difficult to name – more rules apply and more physics and computer science are needed to show they are what they are. A moon not only has to orbit a planet, it must do it in a well-defined way. For example the Cassini probe that’s exploring Saturn and its wonderful ring system discovered a range of small moons that keep the rings of Saturn crisp. Some of these tiny ‘shepherd moons’ orbit near the edges of the gaps in the rings. Materials that drift close to them are pulled back by gravity into the rings, spun off into space or made to crash on the shepherd moon itself. To be able to name one of these moons you need to be able to show that its orbit is stable. When the scientists think they have found a moon, the data from the sensors on the Cassini probe is fed into sophisticated computer simulations to show if that moon has a stable orbit. The outcome of the calculation decides if the moon is, well, a moon.

Good Moon Hunting

The software can even hunt down and find unknown moons. Using the laws of geometry and Kepler’s laws of planetary motion (three rules that German astronomer Johannes Kepler discovered in the 16th century) and applying them to the data from the probe it‘s possible to guess where a moon might be. Scientists then perform a full analysis of the data, including whether the possible moon’s orbit is affected by other known moons, and are able to determine where the previously unknown moons actually are. Using this method, scientists have even discovered so-called retrograde moons, which orbit in the opposite direction to Saturn’s rotation.

Once the orbit is predicted and checked the computer-discovered moon can be named. The scientists have now found so many of these mini-moons that the rules about names have had to change.

More giants and monsters please

To start with the moons of Saturn were named after mythological Greek and Roman giants, but as more were discovered astronomers went over to naming them after the mythical Titans, who fought alongside the giants (and were pretty huge themselves). Finally as more moon hunting showed an ever larger and more fascinating picture the names had to expand to include giants and monsters in Norse, Inuit and Gallic mythologies. Astronomer Carl Murray of Queen Mary, University of London, part of the team who discovered the Saturnian moons Polydeuces and Anthe said “I never thought that a knowledge of ancient mythologies would help me do astronomy”. Quite where this moon-related voyage of discovery will end no one quite knows.

Galileo was the first to observe
Saturn’s rings though he had no
idea what they were. He wrote in his
notebook that the planet had ‘ears’.

Knowing the neighbourhood

Finding moons and keeping an eye on asteroids is an activity that involves astronomers, physicists and computer scientists. Without these scientists all working together, each bringing their skills to work on the problem, our solar system could be a less well-known and more dangerous place to live. We know where things are, after all. We don’t want to end up like Poosh and loose a moon.

Out of the way

Computer science also allows the paths of asteroids to be predicted, which is what’s needed to name them. More importantly these computer models can predict if the asteroids will cut across Earth’s orbit. We don’t want to be unexpectedly hitting one of these lumps, even if the idea makes for a good movie.

Paul Curzon, Queen Mary University of London

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Looking inside medicine – computer scientists in the body

Medical scanner image from Bethesda naval medical center, Maryland via Pixabay

Computer scientists are helping doctors, surgeons, biologists and psychologists get inside the body and mind, and improving the way that medical care will be provided now and in the future. It’s a fascinating story of biology, maths and computing and it all starts with an X.

What a picture!

X-rays were the first practical method of examining the inside of a living body. The process involves firing high energy X-rays through the body with a photographic plate at the other side. Dense bits of the body like bones absorb radiation. That leads to a lighter area on the developed photographic negative. In effect a shadow is cast through you onto the photograph, giving a view inside. A problem with this is that, as with any camera, it’s hard to get the photograph exposure right. Worse you have to find the space to store hundreds and thousands of sheets of film. Worse still, suppose your doctor in Manchester needs the X-ray taken of you when you are wanting to play football so you are in Frankfurt. The film has to be sent by post. Enter computer scientists to make things easier.

Portable pixel pictures

New digital X-ray systems are being developed. These use X-ray detectors not film and produce digital images rather than the standard photographic images. The advantage here is that those images can be processed using clever algorithms to correct for problems in exposure, or even to pick up particular shapes in the image. The diagnosis can be helped by the artificial intelligence in the computer, which can spot unusual patterns in the image and alert the doctor. Better still since these digital X-rays are computer based. They can be easily stored and transmitted throughout the world to places where they are needed.

A slice of life

X-rays, even digital X-rays, can only give you flat images of the body innards. Like a shadow they squash all the depth details. Your insides are three-dimensional (3D) though, so it would be useful to be able to slice through your body and get a view inside. This is possible using a computer based method called tomography, from the Greek tomos (slice) and graphia (describing). It still uses X-rays but in a Computed Tomography (CT) scan the X-ray source and the detector rotate round the body taking lots of images at different angles. It’s like casting different shadows as the sun moves round you. So imagine you’re using tomography on a cylinder, and your X-ray source is a torch. Move the torch round the cylinder and look at the shadow cast on a piece of paper moving at the opposite side to the torch. Each ‘shadow’ picture would look the same because a cylinder is circularly symmetric. Now imagine a more interesting shape. Each of the shadow pictures would depend on where you were at the time in relation to the shape. With some clever maths, a reconstruction algorithm and a computer you can go from the shadow pictures back to the shape. These shapes are the organs and innards of your body, and they can be recorded in their full 3D glory. There are now systems that spiral the X-ray source round the body making it quicker. You can even do tomography at very high speed allowing slices through the beating heart to be calculated. Interestingly the maths behind this technology, called the “Radon transform” after Czech mathematician Johann Radon (1887-1956), was developed purely as an abstract mathematical theory. No one at the time could see any use for it!

Check in at the Digital Hospital

Life-saving healthcare and medical imaging is going digital. Using video conferencing, mobile scanners and even remote operated robotic surgery the field of tele-medicine allows expert medical care to be provided any time, any place. Today’s progress towards the digital hospital combines different ways of taking information about the state of your body, such as digital X-rays, or tomographic images, readings from digital thermometers or digital blood pressure readers. We can combine all this information with your personal information into one big file, so there is no need for multiple paper copies to get out of date or lost. The hospital information system keeps track of all your data, and also importantly who has access to it.

Tomorrow’s world and you

According to Alan McBride, a computer scientist who is working on these state of the art medical systems:

“This technology is a major step forward in health care where the UK is leading the way. The government’s grand scheme will allow images taken in Newcastle to be shown on your GP’s desk in London, together with the hospital report, which will automatically be emailed to their inbox. Computer science is playing the major role in all this, creating new ways to aid clinical practice, with plenty of scope in the future for talented computer scientists to get involved.”

The computer scientists who make this happen will not only be technical specialists but also experts in understanding human behaviour. We will only get the benefits such a grand scheme promises if the conflicting needs and concerns of all those involved are taken into account: patients, nurses, doctors, managers and politicians…that will take major people-skills.

Paul Curzon, Queen Mary University of London

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As Easy As A Bee Sees

A bee sitting on the leaves of a blossom tree in Blackheath
Bee on blossom by Jodiepedia, Public Domain Dedication (CC0) via Flickr.

If it weren’t for the bees we would be in trouble. In the worst case, life on Earth could go the way of Mars. No plants, no animals, no life. Bees are the main way that flowers get pollinated. As the bees sup the nectar they carry pollen from flower to flower, allowing new generations of flowers to grow. But the way a flower looks to our eyes isn’t the same way a bee sees it. For example, bee vision works into the ultraviolet part of the spectrum and under the correct lighting in a laboratory the wonderful, normally invisible, patterns that bees can see are revealed. Biologists all over the world have been collecting information about the sorts of patterns that particular flowers display. This display is called a spectral profile, and Samia Faruq, a computer science undergraduate at Queen Mary University of London has done her bit to help these scientists peer into the world of the bees.

Her project involved creating a massive online database containing worldwide spectral profile information, so scientists can search this information easily. They can also combine information to help discover new facts using a method called clustering, where the computer pulls together all the data with similar properties.

Samia enjoyed the project: “I met and worked with amazing biologists during the project. It was great to find out what they needed and to be able to create it for them. I got the chance to collaborate and publish material together with them too. To know it will be used in their research is also very rewarding.”

Peter W McOwan, Queen Mary University of London

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