What is an algorithm? It is just a set of instructions that if followed precisely and in the given order, guarantees some result. The concept is important to computer scientists because all computers can do is follow instructions, but they do so perfectly. Computers do not understand what they are doing so can’t do anything but follow their instructions. That means whatever happens the instructions must always work. We can see what we mean by an algorithm by comparing it to the idea of a self-working trick from conjuring.
If you follow the steps of a self-working trick you will have the magic effect even if you have no idea how it works. Below is a a demonstration of a self-working magic jigsaw trick (you can download it from here https://conjuringwithcomputation.wordpress.com/resources/ print it, cut out the pieces and do it yourself, following the instructions below).
Image by CS4FN
The step of the trick are.
1) Count the robots (ignore the green monsters and the robot dog)….There are 17.
2) Swap the top two pieces on the left with those on the right lining the jigsaw back up
3) Count the robots ….There are 16. One has disappeared.
Magically a robot has disappeared! Which one disappears and where did it go? Was it swallowed by a green monster, did it teleport away?
How did that happen anyway?
Image by CS4FN
By following the steps you can make the trick work…even if you haven’t worked out how it works, a robot still disappears. You do not need to understand, you just need to be able to follow instructions. It is a self-working trick. Follow the steps of the trick exactly and the robot disappears. It is just an algorithm. Self-working tricks are just algorithms for doing magic. When you follow the steps of the trick you are acting like a computer, blindly following the instructions in its program!
Mid-September, as many young people are heading back to school after their summer holiday, is Asthma Week where NHS England suggests that teachers, employers and government workers #AskAboutAsthma. The goal is to raise awareness of the experiences of those with asthma, and to suggest techniques to put in place to help children and young people with asthma live their best lives.
One of the key bits of kit in the arsenal of people with asthma is an inhaler. When used, an inhaler can administer medication directly into the lungs and airways as the user breathes in. In the case of those with asthma, an inhaler can help to reduce inflammation in the airways which might prevent air from entering the lungs, especially during an asthma attack.
It’s only recently, however, that inhalers are getting the technology treatment. Smart inhalers can help to remind those with asthma to take their medication as prescribed (a common challenge for those with asthma) as well as tracking their use which can be shared with doctors, carers, or parents. Some smart inhalers can also identify if the correct inhaler technique is being used. Researchers have been able to achieve this by putting the audio of people using an inhaler through a neural network (a form of artificial intelligence), which can then classify between a good and bad technique.
As with any medical technology, these smart inhalers need to be tested with people with asthma to check that they are safe and healthy, and importantly to check that they are better than the existing solutions. One such study started in Leicester in July 2024, where smart inhalers (in this case, ones that clip onto existing inhalers) are being given to around 300 children in the city. The researchers will wait to see if these children have better outcomes than those who are using regular inhalers.
This sort of technology is a great example of what computer scientists call the “Internet of Things” (IoT). This refers to small computers which might be embedded within other devices which can interact over the internet… think smart lights in your home that connect to a home assistant, or fridges that can order food when you run out.
A lot of medical devices are being integrated into the internet like this… a smart watch can track the wearer’s heart rate continuously and store it in a database for later, for example. Will this help us to live happier, healthier lives though? Or could we end up finding concerning patterns where there are none?
Following a tough experience at his last workplace, Stephen decided he needed a change. He used this as a prompt to start thinking about alternatives:
“[When] things aren’t working out, you need to take a step back and work out what the problem is before it becomes really serious. I still hadn’t had a diagnosis by that point, so things probably would have gone very differently if I had, but I took a step back after that job. I was fed up of being stressed, trying to help people [who] have already got far too much money make more money, and then being told that I was being paid too much. That was kind of my experience from my last employer. And so, I decided that I wanted to get stressed for something worthwhile instead: my mum had been a teacher, so I’d always had it in mind as a possibility.”
Stephen did, of course, have some reservations financially.
“I’d always thought it was financially too much of a step down, which a lot of people in the computer science industry will find out. I did take pretty much a 50% pay cut to become a trainee teacher: in fact, worse than that. But it’s amazing when you want to do something, what differences that makes! And there’s plenty of people out there that will sacrifice a salary to start their own business, and all the power to them. But people don’t think [like this] when they’re thinking about becoming a teacher, for example, which I think is wrong. Yes, teachers should be better paid than they are, but they’re never going to be as well paid as programmers or team leaders or whatever in industry. You shouldn’t expect that to be the case, because we’re public servants at the end of the day, and we’re here for the job as much as we are for the money. We want our roof over our head, but we’re not looking to get mega rich. We’re there to make a difference.”
While considering this change of profession, Stephen reflected on his existing skills, and whether they fit the role of teaching. With support from his wife and a DWP (Department for Work and Pensions) work coach, he was reminded of his ability to “explain technical stuff to [people] in a language [they] could understand.”
Stephen had the opportunity to get his first experience of teaching as a classroom volunteer. Alongside a qualified teacher, he was able to lead a lesson – which he found particularly exciting:
“It was a bit like being on drugs. It was exhilarating. I sort of sat there thinking, you know, this is something I really want to do.”
It’s around this time that Stephen got his autism diagnosis. For autistic people who receive a diagnosis, there can be a lot of mixed emotions. For some, it can be a huge sense of relief – finally understanding who they are, and how that has affected their actions and behaviours throughout their life. And for others it can come as a shock [EXTERNAL]. For Stephen, this news meant reconsidering his choice of a career in teaching:
“I had to stop and think, because, when you get your diagnosis for the first time as an adult or as an older person anyway, it does make you stop and think about who you are. It does somewhat challenge your sense of self.”
“It kind of turns your world a bit on its head. So, it did knock me a fair bit. It did knock my sense of self. But then I began to sort of put pieces together and realise just what an impact it had on my working life up until that point. And then the question came across, can I still do the job? Am I going to be able to teach? Is it really an appropriate course of action to take? I didn’t get the answer straight away, but certainly over the months and the years, I came to the conclusion it was a bit like when I talk to students who say, ‘should I do computer science?’ And I say to them, ‘well, can you program?’ ‘Yes.’ ‘Yes, you do need to do computer science.’ It’s not just you can if you want to – it’s a ‘you should do CS.’ It’s the same thing if you’re on the spectrum, or you’re in another minority, a significant minority like that, where you’re able to engage with a teaching role: you should do.”
Stephen did go on to complete teacher training, and has now worked as an A-Level and GCSE teacher for 15 years. He still benefits from his time in work, however, as he is able to enlighten future computer science students about the workplace:
“Well, you know the experiences I’ve had as a person in industry, where else are the students going to be exposed to that second-hand? Hopefully they’ll be exposed to it first-hand, but, if I can give them a leg up, and an introduction to that, being forewarned and forearmed and all that, then that’s what should happen.
“I do spend a chunk of my teaching explaining what it’s like working in industry: explaining the difficulties of dealing with management; (1) when you think you know better, you might not know better – you don’t know yet; (2) if you do, keep your mouth shut until the problem occurs, then offer a positive and constructive solution. Hopefully they won’t say ‘why didn’t you say something sooner?’ If they do, just say, ‘Well, I wasn’t sure it was my place to, I’m only new.’”
Teaching is famously a very rewarding career path, and this is no different for Stephen. In our discussion, he outlined a few things that he enjoyed about teaching:
“It’s [a] situation where what you do, lives on. If I drop dead tomorrow, all that stuff that I learned about; how different procedure calls work or whatever, could potentially just disappear into the ether. But because I’ve shared it with all my students, they will hopefully make use of it, and it will carry on. And it’s a way of having a legacy, which I think we all want, to a certain extent.”
“Young people nowadays, particularly those of us on the spectrum, but it applies to all, the world does everything possible at the moment to destroy most young people’s self-esteem. Really, really knock people flat. Society is set up that way. Our social media is set up that way. Our traditional media is set up that way. It’s all about making people feel pretty useless, pretty rubbish in the hope, in some cases, of selling them something that will make them feel better, which never does, or in other cases, just make someone else feel good by making someone else feel small. It’s kind of the more the darker side of humanity coming out that teaching is an opportunity to counter that. If you can make a young person feel good about themselves; if you can help them conquer something that they’re not able to do; if you could help them realise that it doesn’t matter if they can’t, they’re still just as important and wonderful and valuable as a human being.”
“The extracurricular activities that I do: ‘Exploring the Christian faith’ here at college. And part of that is helping people [to] find a spiritual worth they didn’t realise they had. So, you get that opportunity as a teacher, which a bus driver doesn’t get, for example. Bus drivers are very useful – they do a wonderful job. But once they’ve dropped you off, that’s the end of the job. Sometimes we’re a bit like bus drivers as teachers. You go out the door with your grades, and that’s fine, but then some people keep coming back. I haven’t spotted the existential elastic yet, but it’s there somewhere. I’m sure I didn’t attach it. But that is another one of the things that motivates me to be a teacher.”
Stephen Parry now teaches at a sixth-form college near Sheffield. The author would like to thank Stephen for taking time out of his busy schedule to take part in this interview.
Autism is a condition with many associated challenges, but for some people it presents some benefits. This distinction is greatly apparent in the workplace, where autistic people often find it difficult to get along with others (and their boss), and to complete the work that has been set for them. It’s not all negatives though: many autistic people find the work in which they thrive, and given the right circumstances and support, an autistic person is able to succeed in such an environment.
We often rightly hear about the greats in computer science; Ada Lovelace, Alan Turing, Lynn Conway (who sadly passed away earlier this month) – but let us not forget the incredible teams of computer scientists working around the clock; maintaining the Internet, building the software we use every day, and teaching the next generation. For this two-part article, I have spoken with Stephen Parry, an autistic computer scientist, who, after working in industry for 20 years, now teaches the subject in a sixth-form college in Sheffield. His autistic traits have caused him challenges throughout his career, but this is not a unique experience – many autistic computer scientists also face the same challenges.
Stephen’s experience with programming started at the age of 14, after being introduced to computers at a curriculum enrichment course. He decided against taking a then “really rubbish” O-Level (now GCSEs) Computer Science course, and the existence of the accompanying A-Level “just didn’t come up on my radar”. He was, however, able to take home the college’s sole RML 380Z for the summer, a powerful computer for the time, with which, he was able to continue to practice programming.
When it came time to go to university, he opted first to study chemistry, a subject he had been studying at A-Level. Though after a short amount of time he realised that he wasn’t as interested in chemistry as he first thought – so he decided to switch to computer science. In our discussions, he praised the computer science course at the University of Sheffield:
“[I] really enjoyed [the course] and got on well with it. So, I kind of drifted into it as far as doing it seriously is concerned. But it’s been a hobby of mine since I was 14 years old, and once I was on the degree, I mean, the degree at Sheffield was a bit like a sweetie shop. It really was absolutely brilliant. We did all kinds of weird and wonderful stuff, all of it [was] really interesting and engaging, and the kind of stuff that you wouldn’t get by either playing around on your own or going out into [the] workplace. As I’ve always said, that’s what a university should be. It should expose you to the kind of stuff that you can’t get anywhere else, the stuff that employers haven’t realised they need yet.”
Of autistic people who go to university, research shows they are much more likely the general population to pick STEM subjects [EXTERNAL]. For lots of autistic people, the clear logical and fundamental understanding behind scientific subjects is a great motivator. Stephen describes how this is something that appeals to him.
“[What] I enjoy about computer science is how it teaches you how the computer actually works at a fundamental level. So, you’re not just playing with a black box anymore – it’s something you understand. And especially for someone on the [autism] spectrum, that’s a really important aspect of anything you do. You want to understand how things work. If you’re working with something, and you don’t understand how it works, usually it’s not very satisfying and kind of frustrating. Whereas, if you understand the principles going on inside of it then, when you know you’ve got it, it kind of unlocks it for you.”
While autistic traits often result in challenges for autistic people, there are some which can present a benefit to someone in computer science. A previous CS4FN article described how positive traits like ‘attention to detail’ and ‘resilience and determination’ link well to programming. Stephen agrees that these traits can help him to solve problems:
“If I get focused on a problem, the hyper focus kicks in, and I will just keep plugging away until it’s done, fixed or otherwise overcome. I know it’s both a benefit and hazard – it’s a double edged sword, but at the same time, you know you have to have that attention to detail and that, to put it another way, sheer bloody mindedness to be determined that you’re going to make it work, or you’re going to understand how it works, and that does come definitely from the [autism] spectrum.”
Although he enjoyed the content greatly, Stephen had a rocky degree, both in and out of lectures. However, some unexpected benefits arose from being at university; he both found faith and met his future wife. These became essential pillars of support, as he prepared to enter the workforce. This he did, working both as a programmer and in a variety of IT admin and technical support roles.
About 78% of autistic adults are currently out of work [EXTERNAL] (compared with 20% in the general population). This is, in part, reflective of the fact that some autistic people are unable to work because of their condition. But for many others, despite wanting to work, they cannot because they do not get the support they need (and are legally entitled to) within their workplace.
At this time, however, Stephen wasn’t aware of his condition, only receiving his diagnosis in his 40s. He described how this transition from university to work was very challenging.
“I moved into my first job, and I found it very, very difficult because I didn’t know that I’ve got this sort of difference – this different way my brain works that affects everything that you do. I didn’t know when I came across difficulties, it was difficult to understand why, at least to an extent, for me and for other people, it was deeply frustrating. I mean, speak to just about every manager I’ve ever had, and the same sort of pattern tends to come out. Most of them recognised that I was very difficult to manage because I found myself very difficult to manage. But time management is an issue with everything – trying to complete tasks to any kind of schedule, trying to plan anything. Oh, my days, when I hear the word SMART. [It’s an] acronym [meaning] specific, measurable, achievable, realistic and time specific. I hear that, and it just it makes me feel physically ill sometimes, because I cannot. I cannot SMART plan.”
However, during his time in work, he had some good luck. Despite the challenges associated with autism, some managers took advantage of the positive skills that he brings to the table:
“I found that a real challenge, interpersonally speaking, things like emotional regulation and stuff like that, which I struggle with, and I hate communicating on the phone and various other things, make me not the most promising employee. But the managers that I’ve had over the years that have valued me the most are the ones who recognised the other side of the coin, which is [that] over the years, I have absorbed so much knowledge about computer science and there are very [few] problems that you can come across that I don’t have some kind of insight into.”
This confidence in a range of areas in computer science is also a result of Stephen’s ability to link lots of areas and experiences together, a positive skill that some autistic people have:
“I found that with the mixture of different job roles I did, i.e. programming, support, network admin and database admin, my autism helped me form synergies between the different roles, allowing me to form links and crossover knowledge between the different areas. So, for example, as a support person with programming experience, I had insight into why the software I was helping the user with did not work as desired (e.g. the shortcuts or mistakes the programmer had likely made) and how maybe to persuade it to work. As a programmer with support experience, you had empathy with the user and what might give them a better UX, as well as how they might abuse the software. All this crossover, also set me up for being able to teach confidently on a huge range of aspects of CS.”
For autistic students who are planning on working in a computer science career, he has this to say:
“As an autistic person, and I would say this to anybody with [autism], you need to cultivate the part of you that really wants to get on well with people and wants to be able to care about people and understand people. Neurotypical people get that ability out of the box, and some of them take it for granted. I tend to find that the autistic people who actually find that they can understand people, that they work at it until they can, [are] often more conscientious as a result. And I think it’s important that if you’re an autistic person, to learn how to be positive about people and affirm people, and interact with them in positive ways, because it can make you a more caring and more valuable human being as a as a result.”
“Look for jobs where you can really be an asset, where your neurodiversity is the asset to what you’re trying to do, but at the same time, don’t be afraid to try to, and learn how to engage with people. Although it’s harder, it’s often more rewarding as a result.”
Undersea telecommunications cables let the world communicate and led to the world spanning Internet. It was all started by the Victorians. Continents were connected, but closer islands were too including the Scilly Isles.
Autumn 1869. There were great celebrations as the 31 mile long telecommunications cable was finally hauled up the shore and into the hut. The Scilly Isles now had a direct cable communication link to the mainland. But would it work? Several tests messages were sent and it was announced that all was fine. The journalists filed their story. The celebrations could begin.
Except it didn’t actually work! The cable wasn’t connected at all. The ship laying the cable had gone off course. Either that or someone’s maths had been shaky. The cable had actually run out 5 miles off the islands. Not wanting to spoil the party, the captain ordered the line to be cut. Then, unknown to the crowd watching, they just dragged the cut off end of the cable up the beach and pretended to do the tests. The Scilly Isles weren’t actually connected to Cornwall until the following year.
Paul Curzon, Queen Mary University of London (from the archive)
Navajo Code Talkers, Image from National Archives at College Park, Public domain, via Wikimedia Commons
Bletchley Park, the British code cracking centre helped win World War II, but it is not just breaking codes and ciphers that wins wars, creating unbreakable ones to keep your own secrets safe matters too. Bletchley Park wasn’t the first or only time a secret cryptography team helped win battles or even wars. In World War I secret messages had been successfully sent using Choctaw, the language of a tribe of Native Americans, including to help organise a surprise attack. It worked with their messages left un-cracked. This led to an even more successful code-creating team in World War II based on Navajo. The Navajo “Code Talkers” as they were called, could encode, transmit and decode messages in minutes when it would take hours using conventional codes and ciphers.
In World War II, the US forces used a range of Native American languages to communicate, but a code based on a native Indian language, Navajo, was especially successful. The use of a Navajo-based code was the idea of Philip Johnston after the attack on Pearl Harbour. His parents were missionaries so he had grown up on a Navajo reservation, speaking the language fluently despite how difficult it was. Aged only 9, he acted as an interpreter for a group who went to Washington to try to improve Indian rights.
He suggested using Navajo as a secret language and enlisted in the marines to help bring the idea to fruition. He thought it would work as a secret code because there was no written version of Navajo. It was a purely a spoken language. That meant he was one of very few people who were not Navajo who could speak it. It was also a complex language unlike any other language. The US marines agreed to trial the idea.
To prove it would work, Johnston had Navajo transmit messages in the way they would need to on the battlefield. They could do it close to 100 times faster than it would take using standard cipher machines. That clinched it.
Many Navajo had enlisted after Pearl Harbour and a platoon soley of Navajo were recruited to the project, including a 15 year old, William Dean Yazzie. However, they didn’t just speak in Navajo to transmit messages. The original 29 Navajo recruited worked out the details of the code they would use. Once deployed to the Pacific a group of them also met to further improve the code. None of it was written down apart from in training manuals that did not leave the training site, so there was no chance the code book could be captured in battle. All those involved memorised it and practiced sending messages quickly and accurately. Messages were also always spoken, eg over radio and never written down, making it harder for the code to be cracked based on analysing intercepted messages.
Commonly needed words, like ‘difficult’ or ‘final’ had direct Navajo code words (NA-NE-KLAH and TAH-AH-KWO-DIH). However for critical words (countries, kinds of planes, kinds of ships, etc) they first swapped English words for other English words using one code. They then translated those words into Navajo. That meant even a Navajo speaker outside their trained group wouldn’t immediately understand a message. The code, for example, used birds names in place of kinds of planes. So the English code word for a bomber plane was Buzzard. But then the Navajo for Buzzard was actually used: (JAY-SHO).
Another part of the code was to use Navajo words for letters of the alphabet, so A is for ant translated to WOL-LA-CHE in Navajo. However, to make this more secure two other words stood for A too (apple: BE-LA-SANA and axe: TSE-NILL). Each letter had three alternatives like this and any of the three could be used.
Finally the way that it was used meant a message would always just be a series of unconnected words making no sense even to a Navajo speaker.
The code talkers played a key part in many battles including the iconic battle of Iwo Jima, capturing the heavily defended Japanese controlled island of that name. The US Major responsible for communications said of the battle, “Were it not for the Navajos, the Marines would never have taken Iwo Jima.”
Not only did it make communications much faster than they would have been, unlike other US codes and ciphers, the code talker’s code was never cracked … all thanks to the Navajo team who devised it.
Video games were once considered to be only of interest to boys, and the early games industry was dominated by men. Despite that, a teenage girl, Joyce Weisbecker, was one of the pioneers of commercial game development.
Originally, video games were seen as toys for boys. Gradually it was realised that there was a market for female game players too, if only suitably interesting games were developed, so the games companies eventually started to tailor games for them. That also meant, very late in the day, they started to employ women as games programmers. Now it is a totally normal thing to do. However, women were also there from the start, designing games. The first female commercial programmer (and possibly first independent developer) was Joyce Weisbecker. Working as an independent contractor she wrote her first games for sale in 1976 for the RCA Studio II games console that was released in January 1977.
Joyce was only a teenager when she started to learn to program computers and wrote her first games. She learnt on a computer that her engineer father designed and built at home called FRED (Flexible Recreational and Educational Device). He worked for RCA (originally the Radio Corporation of America), one of the major electronics, radio, TV and record companies of the 20th century. The company diversified their business into computers and Joyce’s father designed them for RCA (as well as at home for a hobby). He also invented a programming language called CHIP-8 that was used to program the RCA computers. This all meant Joyce was in a position to learn CHIP-8 and then to write programs for RCA computers including their new RCA Studio II games console before the machine was released, as a post-high school summer job.
The code for two games that she wrote in 1976, called Snake Race and Jackpot, were included in the manual for an RCA microcomputer called the COSMAC VIP, and she also wrote more programs for it the following year. These computers came in kit form for the buyer to build themselves. Her programs were example programs included for the owner to type in and then play once they had built the machine. Including them meant their new computer could do something immediately.
She also wrote the first game that she was paid for in that Summer of 1976. It was for the RCA Studio II games console, and it earned her $250 – well over $1000 in today’s money, so worth having for a teenager who would soon be going on to college. It was a quiz program, called TV School House I. It pitted two people against each other, answering questions on topics such as maths, history and geography, with two levels of difficulty. Questions were read from question booklets and whoever typed in the multiple choice answer number the fastest got the points for a question, with more points the faster they were. There is currently a craze for apps that augment physical games and this was a very early version of the genre.
Speedway screen from Wikimedia
She quickly followed it with racing and chase games, Speedway and Tag, though as screens were still very limited then, with only tiny screens, the graphics of all these games were very, very simple – eg racing rectangles around a blocky, rectangular racing track.
Unfortunately, the RCA games console itself was a commercial failure as it couldn’t compete with consoles like the Atari 2600, so RCA soon ended production. Joyce, meanwhile, retired from the games industry, still a teenager, ultimately becoming a radar signal processing engineer.
While games like Pong had come much earlier, the Atari 2600, which is credited with launching the first video game boom, was released in 1977, with Space Invaders, one of the most influential video games of all time, released in 1980. Joyce really was at the forefront of commercial games design. As a result her papers related to games programming, including letters and program listings, are now archived in the Strong National Museum of Play in New York.
What could a blind or partially-sighted person get from a visit to an art gallery? Quite a lot if the art gallery puts their mind to it. Even more if they make use of technology. So much so, we may all want the enhanced experience.
The best art galleries provide special tours for blind and partially-sighted people. One kind involves a guide or curator explaining paintings and other works of art in depth. It is not exactly like a normal guided tour that might focus on the history or importance of a painting. The best will give both an overview of the history and importance whilst also giving a detailed description of the whole picture as well as the detail, emphasising how each part was painted. They might, for example, describe the brush strokes and technique as well as what is depicted. They help the viewer create a really detailed mental model of the painting.
One visually-impaired guide who now gives such tours at galleries such as Tate Britain, Lisa Squirrel, has argued that these tours give a much deeper and richer understanding of the art than a normal tour and certainly more than someone just looking at the pictures and reading the text as they wander around. Lisa studied Art History at university and before visiting a gallery herself reads lots and lots about the works and artists she will visit. She found that guided tours by sighted experts using guided hand movements in front of a painting helped her build really good internal models of the works in her mind. Combined with her extensive knowledge from reading, she wasn’t building just a picture of the image depicted but of the way it was painted too. She gained a deep understanding of the works she explored including what was special about them.
The other kind of tour art galleries provide is a touching tour. It involves blind and partially-sighted visitors being allowed to touch selected works of art as part of a guided tour where a curator also explains the art. Blind art lover, Georgina Kleege, has suggested that touch tours give a much richer experience than a normal tour, and should also be put on for all for this reason. It is again about more than just feeling the shape and so “working out its form that”seeing” what a sighted person would take in at a glance. It is about gaining a whole different sensory experience of the work: its texture, for example, not a lesser version just of what it looks like.
How might technology help? Well, the company, NeuroDigital Technologies, has developed a haptic glove system for the purpose. Haptic gloves are gloves that contain vibration pads that stimulate the skin of the person in different, very fine ways so as to fool the wearer’s brain into thinking it is touching things of different shapes and textures. Their system has over a thousand different vibration patterns to simulate different feelings of touching surfaces. They also contain sensors that determine the precise position of the gloves in space as the person moves their hands around.
The team behind the idea scanned several works of art using very accurate laser scanners that build up a 3D picture of the thing being scanned. From this they created a 3D model of the work. This then allowed a person wearing to feel as though they were touching the actual sculpture feeling all the detail. More than that the team could augment the experience to give enhanced feelings in places in shadow, for example, or to emphasise different parts of the work.
A similar system could be applied to historical artifacts too: allowing people to “feel” not just see the Rosetta Stone, for example. Perhaps it could also be applied to paintings to allow a person to feel the brush strokes in a way that could just not otherwise be done. This would give an enhanced version of the experience Lisa felt was so useful of having her hand guided in front of a painting and the brush strokes and areas being described. Different colours might also be coded with different vibration patterns in this way allowing a series of different enhanced touch tours of a painting, first exploring its colours, then its brush strokes, and so on.
What about talking tours? Can technology help there? AIs can already describe pictures, but early versions at least were trained on the descriptions people have given to images on the Internet: “a black cat sitting on top of the TV looking cute”, The Mona Lisa: a young woman staring at you”. That in itself wouldn’t cut it. Neither would training the AI on the normal brief descriptions on the gallery walls next to works of art. However, art books and websites are full of detail and more recent AIs can give very detailed descriptions of art works if asked. These descriptions include what the picture looks like overall, the components, colours, brushstrokes and composition, symbolism, historical context and more (at least for famous paintings). With specific training from curators and art historians the AIs will only get better. What is still missing for a blind person though from the kind of experience Lisa has when experiencing painting with a guide, is the link to the actual picture in space – having the guide move her hand in front of the painting as the parts are described. However, all that is needed to fill that gap is to combine a chat-based AI with a haptic glove system (and provide a way to link descriptions to spatial locations on the image). Then, the descriptions can be linked to positions of a hand moving in space in front of a virtual version of the picture. Combine that with the kind of system already invented to help blind people navigate, where vibrations on a walking stick indicate directions and times to turn, and the gloves can then not only give haptic sensations of the picture in front of the picture or sculpture, but also guide the person’s movement over it.
Whether you have such an experience in a gallery, in front of the work of art, or in your own front room, blind and partially sighted people could soon be getting much better experiences of art than sighted people. At which point, as Georgina Kleege, suggested for normal touch tours, everyone else will likely want the full “blind” experience too.
On Thursday 4th July 2024, millions of adults around the UK went to their local polling station to vote for their representative in the House of Commons. However, for the 18% of adults who have a disability, this can be considerably more challenging. While the right of voters to vote independently and secretly is so important, many blind and partially sighted people cannot do so without assistance. Thankfully this is changing, and this election was hailed as the most accessible yet. So how does technology enable blind and partially sighted people to vote independently?
There are two main challenges when it comes to voting for blind and partially sighted people. The names of candidates are listed down the left-hand side, so firstly, a voter needs to find the row of the person who they want to vote for. They then, secondly, need to put a cross in the box to the right. The image below gives an example of what the ballot paper looks like:
To solve the first problem, we can turn to audio. An audio device can be used to play a recording of the candidates as the appear on the ballot paper. Some charities also provide a phone number to call before the election, with a person who can read this list out. This is great, of course, but it does rely on the voter remembering the position of the person that they want to vote for. A blind or partially sighted voted is also allowed to use a text reader device, or perhaps a smart phone with a special app, to read out what is on the ballot paper in the booth.
Lots of blind and partially impaired people are able to read braille: a way of representing English words using bumps on the paper (read more about braille in this CS4FN article). One might think that this would solve all the problems, but, in fact, there is a requirement that all the ballot papers for each constituency have a standard design to ensure they can be counted efficiently and without error.
The solution to the second problem is far more practical: the excitingly named tactile voting device. This is a simple plastic device which is placed on top of the ballot paper. Each of the boxes on the ballot paper (as shown to the right of the image above), has a flap above it with its position number embossed on it. When the voter finds the number of the person they want to vote for, they simply turn over the flap, and are guided by a perfectly aligned square guide to where the box is. The voter can then use that guide to draw the cross in the box.
This whole process is considerably more complicated than it is for those without disabilities – and you might be thinking, “there must be an easier way!” Introducing the McGonagle Reader (MGR)! This device combines both solutions into one device that can be used in the voting booth. Like the tactile voting device, it has flaps which cover each of the boxes for drawing the cross. But, next to those, buttons, which, when pressed, read out the information of the candidate for that row. This can save lots of time, removing the need to remember the position of each candidate – a voter can simply go down the page and find who they want to vote for and turn over the correct flap.
When people have the right to vote, it is especially important to ensure that they have the ability to use that right. This means that no matter the cost or the logistics, everyone should have access to the tools they need to vote for their representative. Progress is now being made but a lot more work still needs to be done.
To help ensure this happens in future, the RNIB want to know the experiences of those who voted or didn’t vote in the UK 2024 general election – see the survey linked from the RNIB page here.
Reality is weird, very weird. The first thing you have to do to understand the reality of reality is to drop your common sense. Only then can you start to understand it especially when it comes to the quantum world of the very small. Our brains evolved to naturally make sense of human scale things, rather than the very large or very small. Accept the weirdness, though, and there are lots of opportunities, especially for computer scientists.That is why it is now an exciting area of research with theoretical physicists, engineers and computer scientists working together to make progress.
Not common sense
Imagine you are a person trying to understand the world a thousand years ago. Clearly the world MUST be flat. It looks flat and suggesting you are standing on a sphere is just ridiculous. People living on the other side would obviously fall off if it was a sphere! Except the world is a sphere and people in Australia (or Europe if you are Australian) don’t fall off. Common sense doesn’t work (until you understand how gravity works). That’s why science is so powerful. Common Sense also doesn’t work for understanding the reality of the very small. This branch of physics, quantum physics, is very important for computer scientists not only because the building blocks of our computers are becoming ever smaller, but because when you get so small that the laws of quantum physics matter, computers can work in new, exciting ways, ways that are far better than our current computers.
Bits and qubits
Let’s start with binary, the fundamental way we represent information in a computer. The basic building block of information is the bit. A bit is something that can have one of two states. It can be a 1 or a 0. That means a bit can store some information. These two states of 1 and 0 might be physically represented in lots of ways, such as a high voltage stored versus a low voltage stored, or a pulse of light versus no pulse of light, or someone’s hand up versus their hand down. If you have two bits then you can store one of 4 pieces of information in them because of the possible combinations (00, 01, 10 and 11), with three bits and you can store 8 different things. Those collections of bits can then stand for different numbers (that is all binary is), and by building big circuits from simple basic circuits that do simple manipulations on bits (i.e., logic gates) we can do ever more complex calculations with them and ultimately everything our current computers are capable of.
Bits can be represented by anything that has 2 states. So suppose you want to represent your bits using something really small like electrons. Electrons have a property called spin. You can imaging them as spinning balls of charge (though they are not exactly spinning like a spinning ball … electrons aren’t balls and they aren’t actually rotating in the normal sense – remember reality is weird so these analogies are just there to help give an idea, but it is never as simple as that). Now, electrons can “spin” in exactly one of two ways called spin up and spin down. There are only two possible kinds of spin because in the quantum world things come in discrete amounts, not continuous ones. They jump from one state to another, like a pedestrian (walk/don’t walk) traffic light going from red to green instantly) rather than gradually changing between them (such as the way a car gradually speeds up to the speed limit). An electron is either spin up or spin down, like the pedestrian lights, never something in between.
Now, it is possible to set the spin of an electron and to measure whether it has spin that is spin up or spin down, so an electron can, in principle, be used to store a binary bit given it has two states (spin up for 1 and spin down for 0, say). However, this is where weirdness really comes in. It turns out that it is possible for an electron to be both spin up and spin down at once as long as the spin is not measured, due to the way the quantum world works. A quantum pedestrian light doing a similar thing would have only one light that could be red or green. However, it would be both red and green at the same time UNTIL someone looked at it to see which state it was in (so measured the state). At that point they would become, and the person would only see, one colour or the other. This is called quantum superposition. To understand this it is better to think about reality being about probabilities not certainties. Imagine that the electron is like a tossed coin that is still in the air. It has a probability of being Heads and of being Tails. Only when it lands (so is measured) is it actually one or the other. An electron is combining both possibilities until the spin is measured.
The quantum tortoise and the hare
You may have the quaint idea that reality is made of sub-atomic particles (like electrons or protons) that are solid little bits of matter that are very ball like and exist in one place at any given time. Actually they aren’t like that at all. It is better to think of particles as just having probabilities of being at one place or another – they are kind of smeared across space, everywhere at once, like a ripple pattern across a pond, just with different probabilities of actually being in any place when their position is measured. When you do measure their position you find they definitely are in one place or another, appearing to be a particle again, not a wave.
It may help to think of this in terms of watching slow moving tortoises and fast moving hares passing you as they race. The position of a slow moving tortoise you see wander by is easy to call: it has a very high probability to be in a particular place. The position of a fast moving hare that whizzes past is much harder to call: it has a far lower probability to be in a given place at any time. However, without looking you can’t tell. You just know the probabilities. Of course with particles it isn’t exactly like that just as an electron’s spin isn’t exactly like a ball spinning. It is only when a particle’s position is actually checked (i.e. measured) that it is definitely at a known place and that smeared probability collapses to certainty. A quantum tortoise and hare racing past would be in all possible positions round the race track just with different probabilities. Suppose you only checked (so measured their position) at the finish line. It is only because of that measurement that the probabilities of where they were through the race turn into specific measured so known positions with a quantum hare or a quantum tortoise having actually won.
This weirdness is linked to the fact that the fundamental components that reality is made up of are both particles in given places (think of an electron or a proton) and waves passing through space (think of light or ripples in a pond) at the same time. So light behaves like a particle and like a wave. Similarly, an electron does too.
Electron spin as Qubits
Other properties of sub-atomic particles act in the same way as a particle’s position being smeared across lots of possibilities at once. This includes the spin of an electron. Until it is measured, an electron is superposed in both a spin up and spin down state at the same time (spinning both ways at once!): there is just a probability that the electron is in each state, it isn’t actually definitely in either. That means as long as you do not measure its spin, the electron as a device storing a piece of information is storing both 1 and 0 at the same time, each with a given probability. As such it behaves differently to an actual bit which must be either 1 or 0. We therefore call such an electron-based storage a qubit rather than a bit.
In theory, we can do computations on qubits manipulating and combining them in simple ways using the quantum equivalent of logic gates. Once we have created quantum logic gates to do simple manipulations, we can combine those gates into bigger and bigger circuits that do more complicated quantum calculations. As long as the states of the qubits are not measured all the states through the circuit are superposed in both states with particular probabilities. Unlike a normal circuit which does one series of computations based on its inputs, these quantum circuits are in effect doing all possible computations of that circuit at once. It is only when we measure the answer at the output, say, that the qubits in the circuit are fixed at either 1 or 0 and an actual result is delivered. This is like the tortoise and hare being everywhere (whatever racing strategy they followed) with some probability until we measure the result at the finish line (the output of the race). Because all states existed at once, lots of computation exists simultaneously, this means that such a circuit can, in theory, and with the right algorithms, deliver answers far, far faster than a conventional circuit could possibly do, given the latter can only do one computation at a time,
From theory to practice
That is the theory, and it is gradually being realised in practice. Qubits can be created and their values changed. Various quantum logic gates have also now been invented and so small quantum computers do now exist. Quantum algorithms to do certain tasks quickly have been invented. Since the original ideas were mooted, progress has been relatively slow, but now that the ideas have been shown to work in practice, more and more is being achieved, making it an exciting time to be doing quantum computing research.
More on …
Quantum Computing (to come)
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This blog is funded through EPSRC grant EP/W033615/1.
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