Byte Queens

Women have made vital contributions to computer science ever since Ada Lovelace debugged the first algorithm for an actual computer (written by Charles Babbage) almost 200 years ago (more on CS4FN’s Women Portal). Despite this, women make up only a fraction (25%) of the STEM workforce: only about a fifth of senior tech roles and only a fifth of computer science students are women. The problem starts early: research by the National Centre for Computing Education suggests that female student’s intension to study computing drops off between the ages of 8 and 13. Ilenia Maietta, a computer science student at Queen Mary, talks about her experiences of studying in a male-dominated field and how she is helping to build a network for other women in tech.

Ilenia’s love for science hasn’t wavered since childhood and she is now studying for a master’s degree in computer science – but back in sixth form, the decision was between computer science and chemistry:

“I have always loved science, and growing up my dream was to become a scientist in a lab. However, in year 12, I dreaded doing the practical experiments and all the preparation and calculations needed in chemistry. At the same time, I was working on my computer science programming project, and I was enjoying it a lot more. I thought about myself 10 years in the future and asked myself ‘Where do I see myself enjoying my work more? In a lab, handling chemicals, or in an office, programming?’ I fortunately have a cousin who is a biologist, and her partner is a software engineer. I asked them about their day-to-day work, their teams, the projects they worked on, and I realised I would not enjoy working in a science lab. At the same time I realised I could definitely see myself as a computer scientist, so maybe child me knew she wanted to be scientist, just a different kind.”

The low numbers of female students in computer science classrooms can have the knock-on effect of making girls feel like they don’t belong. These faulty stereotypes that women don’t belong in computer science, together with the behaviour of male peers, continue to have an impact on Ilenia’s education:

“Ever since I moved to the UK, I have been studying STEM subjects. My school was a STEM school and it was male-dominated. At GCSEs, I was the only girl in my computer science class, and at A-levels only one of two. Most of the time it does not affect me whatsoever, but there were times it was (and is) incredibly frustrating because I am not taken seriously or treated differently because I am a woman, especially when I am equally knowledgeable or skilled. It is also equally annoying when guys start explaining to me something I know well, when they clearly do not (i.e. mansplaining): on a few occasions I have had men explain to me – badly and incorrectly – what my degree was to me, how to write code or explain tech concepts they clearly knew nothing about. 80% of the time it makes no difference, but that 20% of the time feels heavy.”

Many students choose computer science because of the huge variety of topics that you can go on to study. This was the case for Ilenia, especially being able to apply her new-found knowledge to lots of different projects:

“Definitely getting to explore different languages and trying new projects: building a variety of them, all different from each other has been fun. I really enjoyed learning about web development, especially last semester when I got to explore React.js: I then used it to make my own portfolio website! Also the variety of topics: I am learning about so many aspects of technology that I didn’t know about, and I think that is the fun part.”

“I worked on [the portfolio website] after I learnt about React.js and Next.js, and it was the very first time I built a big project by myself, not because I was assigned it. It is not yet complete, but I’m loving it. I also loved working on my EPQ [A-Level research project] when I was in school: I was researching how AI can be used in digital forensics, and I enjoyed writing up my research.”

Like many university students, Ilenia has had her fair share of challenges. She discussed the biggest of them all: imposter syndrome, as well as how she overcame it. 

“I know [imposter syndrome is] very common at university, where we wonder if we fit in, if we can do our degree well. When I am struggling with a topic, but I am seeing others around me appear to understand it much faster, or I hear about these amazing projects other people are working on, I sometimes feel out of place, questioning if I can actually make it in tech. But at the end of the day, I know we all have different strengths and interests, so because I am not building games in my spare time, or I take longer to figure out something does not mean I am less worthy of being where I am: I got to where I am right now by working hard and achieving my goals, and anything I accomplish is an improvement from the previous step.”

Alongside her degree, Ilenia also supports a small organisation called Byte Queens, which aims to connect girls and women in technology with community support.

“I am one of the awardees for the Amazon Future Engineer Award by the Royal Academy of Engineering and Amazon, and one of my friends, Aurelia Brzezowska, in the programme started a community for girls and women in technology to help and support each other, called Byte Queens. She has a great vision for Byte Queens, and I asked her if there was anything I could do to help, because I love seeing girls going into technology. If I can do anything to remove any barriers for them, I will do it immediately. I am now the content manager, so I manage all the content that Byte Queens releases as I have experience in working with social media. Our aim is to create a network of girls and women who love tech and want to go into it, and support each other to grow, to get opportunities, to upskill. At the Academy of Engineering we have something similar provided for us, but we wanted this for every girl in tech. We are going to have mentoring programs with women who have a career in tech, help with applications, CVs, etc. Once we have grown enough we will run events, hackathons and workshops. It would be amazing if any girl or woman studying computer science or a technology related degree could join our community and share their experiences with other women!”

For women and girls looking to excel in computer science, Ilenia has this advice:

“I would say don’t doubt yourself: you got to where you are because you worked for it, and you deserve it. Do the best you can in that moment (our best doesn’t always look the same at different times of our lives), but also take care of yourself: you can’t achieve much if you are not taking care of yourself properly, just like you can’t do much with your laptop if you don’t charge it. And finally, take space: our generation has the possibility to reframe so much wrongdoing of the past generations, so don’t be afraid to make yourself, your knowledge, your skills heard and valued. Any opportunities you get, any goals you achieve are because you did it and worked for it, so take the space and recognition you deserve.”

Ilenia also highlighted the importance of taking opportunities to grow professionally and personally throughout her degree, “taking time to experiment with careers, hobbies, sports to discover what I like and who I want to become” mattered enormously. Following her degree, she wants to work in software development or cyber security. Once the stress of coursework and exams is gone, Ilenia intends to “try living in different countries for some time too”, though she thinks that “London is a special place for me, so I know I will always come back.”

Ilenia encourages all women in tech who are looking for a community and support, to join the Byte Queens community and share with others: “the more, the merrier!”

– lenia Maietta and Daniel Gill, Queen Mary University of London

Visit the Byte Queens website for more details. Interested women can apply here.

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Working in Computer Science: An Autistic Perspective (Part 2)

by Daniel Gill, Queen Mary University of London

In Part 1, we spoke to Stephen Parry about his experiences of working in computer science as an autistic person. In this second part, we discuss with him his change from this stressful working environment to teaching A-Level computer science, and how rewarding he has found teaching as a career.

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.

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Working in Computer Science: An Autistic Perspective (Part 1)

by Daniel Gill, Queen Mary University of London

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.”

After working in industry for 20 years, the last half as which as a contractor, Stephen decided to take a considerable pay drop and become a computer science teacher. In the second part of this article, we will continue our conversation and find out what led him to choose a career change to teaching. 

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Joyce Weisbecker: a teenager the first indie games developer?

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by Paul Curzon, Queen Mary University of London

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.

RCA Studio II video games console
Image by WikimediaImages from Pixabay

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.

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Cartoons, comics and computer games – Ada Lovelace’s graphic novel

by Jane Waite, Queen Mary University of London

In 2009 for Ada Lovelace day, a comic strip about Ada and Babbage was created, not quite 100% historically accurate but certainly in the spirit of Lovelace’s love of science and mathematics. Her thrilling adventures in Victorian London have now become a graphic novel.

Image by Andrew Martin from Pixabay

In her own time, Ada was captured as a demure and beautiful young woman in portraits and sketches that were shared in books about her father. Ada would have sat for hours to have her portrait drawn, but she would have known about quick draw cartoons. Newspapers and magazines such as Punch contained satirical cartoons of the day. They were very influential in the 1840’s. Faraday was drawn in Punch, but Babbage and Lovelace didn’t make it then. But now they are crime busting mathematical superheros in their very own alternate history of computing comic book.

Books, films, even a musical have been created about Ada Lovelace, but as we write the circle has not quite been closed. There are no computer games about Ada. But maybe you could change that.


Further reading

The Thrilling Adventures of Lovelace and Babbage: The (Mostly) True Story of the First Computer by Sydney Padua.


This article was first published on the original CS4FN website and a copy can be found on page 17 of issue 20 of the CS4FN magazine, which celebrates the work of Ada Lovelace. You can also read some of our other posts about Ada Lovelace and she features as one of our Women in Computing poster set.


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Protecting your fridge

by Jo Brodie and Paul Curzon, Queen Mary University of London

Ever been spammed by your fridge? It has happened, but Queen Mary’s Gokop Goteng and Hadeel Alrubayyi aim to make it less likely…

Gokop has a longstanding interest in improving computing networks and did his PhD on cloud computing (at the time known as grid computing), exploring how computing could be treated more like gas and electricity utilities where you only pay for what you use. His current research is about improving the safety and efficiency of the cloud in handling the vast amounts of data, or ‘Big Data’, used in providing Internet services. Recently he has turned his attention to the Internet of Things.

It is a network of connected devices, some of which you might have in your home or school, such as smart fridges, baby monitors, door locks, lighting and heating that can be switched on and off with a smartphone. These devices contain a small computer that can receive and send data when connected to the Internet, which is how your smartphone controls them. However, it brings new problems: any device that’s connected to the Internet has the potential to be hacked, which can be very harmful. For example, in 2013 a domestic fridge was hacked and included in a ‘botnet’ of devices which sent thousands of spam emails before it was shut down (can you imagine getting spam email from your fridge?!)

A domestic fridge was hacked
and included in a ‘botnet’ of devices
which sent thousands of spam emails
before it was shut down.

The computers in these devices don’t usually have much processing power: they’re smart, but not that smart. This is perfectly fine for normal use, but to run software to keep out hackers, while getting on with the actual job they are supposed to be doing, like running a fridge, it becomes a problem. It’s important to prevent devices from being infected with malware (bad programs that hackers use to e.g., take over a computer) and work done by Gokop and others has helped develop better malwaredetecting security algorithms which take account of the smaller processing capacity of these devices.

One approach he has been exploring with PhD student Hadeel Alrubayyi is to draw inspiration from the human immune system: building artificial immune systems to detect malware. Your immune system is very versatile and able to quickly defend you against new bugs that you haven’t encountered before. It protects you from new illnesses, not just illnesses you have previously fought off. How? Using special blood cells, such as T-Cells, which are able to detect and attack rogue cells invading the body. They can spot patterns that tell the difference between the person’s own healthy cells and rogue or foreign cells. Hadeel and Gokop have shown that applying similar techniques to Internet of Things software can outperform other techniques for spotting new malware, detecting more problems while needing less computing resources.

Gokop is also using his skills in cloud computing and data science to enhance student employability and explore how Queen Mary can be a better place for everyone to do well. Whether a person, organisation or smart fridge Gokop aims to help you reach your full potential!

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The gender shades audit

by Jo Brodie, Queen Mary University of London

Face recognition technology is used widely, such as at passport controls and by police forces. What if it isn’t as good at recognising faces as it has been claimed to be? Joy Buolamwini and Timnit Gebru tested three different commercial systems and found that they were much more likely to wrongly classify darker skinned female faces compared to lighter or darker skinned male faces. The systems were not reliable.

Face recognition systems are trained to detect, classify and even recognise faces based on a bank of photographs of people. Joy and Timnit examined two banks of images used to train the systems and found that around 80 percent of the photos used were of people with lighter coloured skin. If the photographs aren’t fairly balanced in terms of having a range of people of different gender and ethnicity then the resulting technologies will inherit that bias too. The systems examined were being trained to recognise light skinned people.

The pilot parliaments benchmark

Joy and Timnit decided to create their own set of images and wanted to ensure that these covered a wide range of skin tones and had an equal mix of men and women (‘gender parity’). They did this using photographs of members of parliaments around the world which are known to have a reasonably equal mix of men and women. They selected parliaments both from countries with mainly darker skinned people (Rwanda, Senegal and South Africa) and from countries with mainly lighter skinned people (Iceland, Finland and Sweden).

They labelled all the photos according to gender (they had to make some assumptions based on name and appearance if pronouns weren’t available) and used a special scale called the Fitzpatrick scale to classify skin tones (see Different Shades below). The result was a set of photographs labelled as dark male, dark female, light male, light female, with a roughly equal mix across all four categories: this time, 53 per cent of the people were light skinned (male and female).

Testing times

Joy and Timnit tested the three commercial face recognition systems against their new database of photographs (a fair test of a wide range of faces that a recognition system might come across) and this is where they found that the systems were less able to correctly identify particular groups of people. The systems were very good at spotting lighter skinned men, and darker skinned men, but were less able to correctly identify darker skinned women, and women overall. The tools, trained on sets of data that had a bias built into them, inherited those biases and this affected how well they worked.

As a result of Joy and Timnit’s research there is now much more recognition of the problem, and what this might mean for the ways in which face recognition technology is used. There is some good news, though. The three companies made changes to improve their systems and several US cities have already banned the use of this technology in criminal investigations, with more likely to follow. People worldwide are more aware of the limitations of face recognition programs and the harms to which they may be (perhaps unintentionally) put, with calls for better regulation.

Different Shades
The Fitzpatrick skin tone scale is used by skin specialists to classify how someone’s skin responds to ultraviolet light. There are six points on the scale with 1 being the lightest skin and 6 being the darkest. People whose skin tone has a lower Fitzpatrick score are more likely to burn in the sun and are at greater risk of skin cancer. People with higher scores have darker skin which is less likely to burn and have a lower risk of skin cancer. A variation of the Fitzpatrick scale, with five points, is used to create the skin tone emojis that you’ll find on most messaging apps in addition to the ‘default’ yellow.

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EPSRC supports this blog through research grant EP/W033615/1. 

Playing the weighting game

by Paul Curzon, Queen Mary University of London

Imagine having a reality TV show where yet again Simon Cowell is looking for talent. This time it’s talent with a difference though, not stars to entertain us but ones with the raw ability to help find webpages. Yes, this time the budding stars are all words. Word Idol is here!

The format is simple. Each week Simon’s aim is to find talented words to create a new group: a group with star quality, a group with meaning. Like any talent competition, there are thousands of entries. Every word in every webpage out there wants to take part. They all have to be judged, but what do the specialist judges look for?

OK, we’re getting carried away. Simon Cowell may not be interested but there is big money in the idea. It’s a talent show that is happening all the time. The aim is to judge the words in each new webpage as it appears so that search engines can find it if ever someone goes looking. The real star of this show isn’t Simon Cowell but a Cambridge professor, Karen Spärck Jones. She came up with the way to judge words.

Karen worked out that to do this kind of judging a computer needs a thesaurus: a book of words. It just lists groups of words that mean the same thing. A computer, Karen realised, could use one to understand what words mean.

There is big money in the idea!

The fact that there are so many ways to say the same thing in human languages, makes it really hard for a computer to understand what we write. That is where a thesaurus comes in. If you ask a computer to search for web pages about whales, for example, it helps to know that, a page that talks about orcas is about whales too. Worse still, most words have more than one meaning, a fact that keeps crossword lovers in business.

Take the following example: “Leona is the new big star of the music business.”

The word ‘star’ here obviously means a celebrity, but how do you know? It could also mean a sun or a shape. The fact that it’s with the word ‘music’ helps you to work out which meaning is right even if you have no idea who or what Leona is. As Karen realised, a computer can also work out the intended meanings of words by the other words used with them. A thesaurus tells it what the critical groupings are, but what Karen wanted was a way a computer could work the thesaurus out for itself and now she had a way.

Her early approach was to write a program that takes lots and lots of documents and make lists of the words that keep appearing close together. If ‘music’ appears with ‘star’ lots then that is a new meaning. After building up a big collection of such lists of linked words, the program can then use it to decide which pages are talking about the same thing and so which ones to suggest when a search is done. So Karen had found the first way to judge whether a word has the right ‘talent’ to go in a group. The more often words appear together the higher the score or ‘weighting’ they should be given. Simple!

The only trouble is it doesn’t really work. That is where Karen’s big insight came. She realised that if two words appear together in a lot of different documents then, surprisingly perhaps, putting them together in a group isn’t actually that useful for finding documents! Do a search and they will just tell you that lots of web pages match. What you really want is to be told of the few web pages that contain the meaning you are looking for, not lots and lots that don’t.

The important word groupings are actually only in a small number of web pages. That suggests they give a very focused meaning. Word groups like that help you narrow down the search. So Karen now had a better way to judge word talent. Give high marks for pairs that do appear together but in as few web pages as possible. Rather than a talent show, it is more like a giant game of the quiz show Pointless where you win if you pick the words few other people did.

That idea was the big breakthrough and led to what is now called IDF weighting. It is the way to judge words, and is so good that it’s now used by pretty much every search engine out there. Playing the IDF weighting game may not make great TV but thanks to Karen it really does make for great web.

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EPSRC supports this blog through research grant EP/W033615/1. 

Collecting mini-beasts and pocket monsters

by Paul Curzon, Queen Mary University of London

Satoshi Tajiri created one of the biggest money-making media franchises of all time. It all started with his love of nature and, in particular, mini-beasts. It also eventually took gamers back into the fresh air.

As a child, Satoshi Tajiri, loved finding and collecting minibeasts, so spent lots of time outside, exploring nature. But, as Japan became more and more built up, his insect searching haunts disappeared. As the natural world disappeared he was drawn instead inside to video game arcades and those games became a new obsession. He became a super-fan of games and even created a game fanzine called Game Freak where he shared tips on playing different games. It wasn’t just something he sold to friends either: one issue sold 10,000 copies. An artist, Ken Sugimori, who started as a reader of the magazine, ultimately joined Satoshi, illustrating the magazine for him.

Rather than just writing about games, they wanted to create better ones themselves, so morphed Game Freak into a computer game company, ultimately turning it into one of the most successful ever. The cause of that success was their game Pokemon, designed by Satoshi with characters drawn by Ken. It took the idea of that first obsession, collecting minibeasts, and put it into a fun game with a difference.

It wasn’t about killing things, but moving around a game world searching for, taming and collecting monsters. The really creative idea, though, came from the idea of trading. There were two versions of the game and you couldn’t find all the creatures in your own version. To get a full set you had to talk to other people and trade from your collection. It was designed to be a social game from the outset.

It has been suggested that Satoshi is neuro-diverse. Whether he is or not, autistic people (as well as everyone else) found that Pokemon was a great way to make friends, something autistic people often find difficult. Pokemon, also became more than just a game, turning into a massive media franchise, with trading cards to collect, an animated series and a live action film. It also later sparked a second game craze when Pokemon Go was released. It combined the original idea with augmented reality, taking all those gamers back outside for real, searching for (virtual) beasts in the real world.

 

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EPSRC supports this blog through research grant EP/W033615/1. 

Follow those ants

by Paul Curzon, Queen Mary University of London

Ants climbing on a mushroom obstacle course
Image by Puckel from Pixabay

Ant colonies are really good at adapting to changing situations: far better than humans. Sameena Shah wondered if Artificial Intelligence agents might do better by learning their intelligent behaviour from ants rather than us. She has suggested we could learn from the ants too.

Inspired by staring at ants adapting to new routes to food in the mud as a child, and then later as adult ants raided her milk powder, Sameena Shah studied for her PhD how a classic problem in computer science, that of finding the shortest path between points in a network, is solved by ant colonies. For ants this involves finding the shortest paths between food and the nest: something they are very good at. When foraging ants find a source of food they leave a pheromone (i.e., scent) trail as they return, a bit like Hansel and Gretel leaving a trail of breadcrumbs. Other ants follow existing trails to find the food as directly as possible, leaving their own trails as they do. Ants mostly follow the trail containing most pheromone, though not always. Because shorter paths are followed more quickly, there and back, they gain more pheromone than longer ones, so yet more ants follow them. This further reinforces the shortest trail as the one to follow.

There are lots of variations on the way ants actually behave. These variations are being explored by computer scientists as ways for AI agents to work together to solve problems. Sameena devised a new algorithm called EigenAnt to investigate such ant colony-based problem solving. If the above ant algorithm is used, then it turns out longer trails do not disappear even when a shorter path is found, particularly if it is found after a long delay. The original best path has a very strong trail so that it continues to be followed even after a new one is found. Computer-based algorithms add a step whereby all trails fade away at the same rate so that only ones still being followed stay around. This is better but still not perfect. Sameena’s EigenAnt algorithm instead removes pheromone trails selectively. Her software ants select paths using probabilities based on the strength of the trail. Any existing trail could be chosen but stronger trails are more likely to be. When a software ant chooses a trail, it adds its own pheromones but also removes some of the existing pheromone from the trail in a way that depends on the probability of the path being chosen in the first place. This mirrors what real ants do, as studies have shown they leave less pheromone on some trails than others.

Sameena proved mathematical properties of her algorithm as well as running simulations of it. This showed that EigenAnt does find the shortest path and never settles on something less than the best. Better still, it also adapts to changing situations. If a new shorter path arises then the software ants switch to it!

Sameena won the award
for the best PhD in India

There are all sorts of computer science uses for this kind of algorithm, such as in ever-changing computer networks, where we always want to route data via the current quickest route. Sameena, however, has also suggested we humans could learn from this rather remarkable adaptability of ants. We are very bad at adapting to new situations, often getting stuck on poor solutions because of our initial biases. The more successful a particular life path has been for us the more likely we will keep following it, behaving in the same way, even when the situation changes. Sameena found this out when she took her dream job as a Hedge Fund manager. It didn’t go well. Since then, after changing tack, she has been phenomenally successful, first developing AIs for news providers, and then more recently for a bank. As she says: don’t worry if your current career path doesn’t lead to success, there are many other paths to follow. Be willing to adapt and you will likely find something better. We need to nurture lots of possible life paths, not just blindly focus on one.

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EPSRC supports this blog through research grant EP/W033615/1.