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Advocating for more women in AI & ensuring every voice is at the table

Tabitha Goldstaub, CogX

I’m a huge advocate for getting more women into technology and AI. I care so deeply about ensuring the technology we are building today benefits everyone equally. Be that technology applied to retail, art, logistics, healthcare, or science. You’d be surprised how every sector is butting up against the same challenges. As a result, the lack of diversity in genomic medicine and genomic data, whilst having unique challenges and opportunities within it, can learn a lot from more general technology and data diversity efforts and advice.

I wrote a book called How to Talk to Robots (HTTR) which gives an audience of savvy women who don’t currently care about AI, or think of themselves as techies, some pieces of advice. I want to share with you my story of how I came to understand that a future world dominated by AI wasn’t going to work for me as a woman. Just as anyone excluded from medical research and precision medicine efforts needs to understand and take action if they want future therapies, services, and care to be fit for them.

My story…

Growing up, my brother and I played Gameboy incessantly. Yoshi’s Dream World, Mario Kart Racers, Tekken. I loved the thrill of the win. Both my parents were in fashion, and we watched robot wars together with glee. In 1995, when I was ten, they bought me an Acorn computer. I would spend hours absorbed in the Microsoft Paint program, creating personalised desktop backgrounds for friends and family (and charging them!)

At school, the door to the Internet was Ask Jeeves, a British butler who fronted the search engine, and my guide to Word and Excel was Clippy, Microsoft’s helpful paperclip mascot. I remember having a Tamagotchi that was neither boy nor girl. All this is to say that I was happily unaware of the notion that gender could ever play a part in technology. It was not a male or a female thing: it was my thing.

Cut to a few years later, and during GCSE IT, I was bored. We were being shown how to run a doctor’s reception and were using mail merge to access patient’s data and send emails. I was not inspired.

I often wonder (not blaming my teachers) what if my teachers had explained to me that tech could help predict which of my patients would need life-saving treatment? Maybe I would have gone on to study science.

Instead, I followed in the footsteps of my grandpa and set about joining the advertising world. I was fascinated by the clever people behind the slogans, that captivated mine and my friends’ impressionable minds. At that point, I was enamoured and not yet fearful of their power.

Before university, I was working in a pub when brand-new, fully computerised till systems were installed. The manager decided to train his mates (the men!) on the tills first, which meant they became better faster and so were assigned more shifts behind the bar. The women ended up waiting tables. I didn’t even stop to think about whether this division was fair – I thought computer stuff wasn’t for me, and I think I just accepted that the guys should do the tills. But the consequence of this mindset meant I inadvertently accepted lower pay: waitresses earned less than bar staff, and I ended up hating a job I had come to love. What on earth had happened to me in those interim teenage years?! I still don’t know at what point it became the norm that the world of computers was a male one.

By the time I arrived at university to study advertising, new developments with the web had set the world alight. There was also a new way of communicating with each other, and I remember waiting for my university email to grant me access to the newly launched The Facebook (places me in the timeline). The nature of communication was changing, and my chosen route into advertising had begun to feel outdated. I was falling in love with the web.

Over the course of those three years, I chose modules that would enable me to redefine my relationship with computers. This included how to code. But I found that my dyslexia held me back. I was, quite honestly, hopeless. My real ‘aha’ moment came when I was introduced to Squarespace, a tool that meant I didn’t have to write code in order to create a webpage and reach people. There were companies and products being released every day that meant people like me, who didn’t get on with coding, could still benefit hugely from its power.

So, in 2008, on my hunt to either start a business or work for a start-up I met the CEO and Founder of t5m: a new style of digital studio that produced online video content with celebrities. I joined as an intern, learning how to add words as codes to propel each video to the top ranks of YouTube and then distribute them across the Internet. When I was promoted to managing a team of other recent graduates, we soon realised that the more laborious, mechanical aspects of our job had to become automated for full efficiency – and to avoid us going mad with boredom!

This is the moment I got to work directly with the engineering teams, and I finally felt at home. I’d draw enthusiastic schematics praying they’d be able to translate them into software and tools for me and the team.

It’s fair to say that I threw myself headfirst into the world of AI and tried to talk to every machine going. I was overly optimistic to say the least.

But things began to shift when I realised that AI techniques would make existing inequalities even starker and the genius of the fact AI could personalise down to the individual also made the people and companies developing AI incredibly powerful and potentially dangerous.

I started to read widely and deeply on the topic, and I woke up to the reality that AI could potentially have seriously negative effects for many women, people from Black, Asian and ethnic minorities and in fact could bias against anyone for a protected characteristic.

Weapons of Math Destruction by Cathy ONeil became my north star, and I was hungry to get to the root of the problem.

Thanks to encouragement from mentors like Dame Wendy Hall who wrote “where have all the women gone back in 1987” I started to gather women and host events called ‘Why Women in AI’, in the mission to understand the scale and depth of the challenge and point out why it needed to happen.

At the first event I met amazing women who explained the risks associated with leaving women and people of colour out of the research, programming and the data on which AI systems are built.

I learnt so much from these women and I was set on giving friends who didn’t get this front row seat the same awareness. HTTR was born out of a talk I was giving in 2018 at an event hosted by the achingly cool magazine for women in creative industries. I looked around the room and realised I couldn’t give my usual positive speech about AI and business. These women were at the top of their respective fields, media, fashion, film etc., and I needed to explain why AI would matter to them. It dawned on me how many women’s careers could be destroyed by smart machines, and they weren’t even going to see the tsunami coming. If they weren’t aware of how AI was set to change all the rules, how would they know how to master them? Luckily, my now publisher was in the audience, and she agreed this was a rallying cry more people needed to hear…. And so I wrote How To Talk To Robots to help women ensure that AI works for them... not they for it!

It’s important to say that in this book, though targeted at women and marginalised genders, I aim to consider everyone and especially all people who are currently underrepresented in the conversation about tech and AI.

The book starts with a history of AI showing the traditional list of lone genius on the left and on the right the groups of women who came together to advance AI. As Ottoline Leyser Chair of UL Research & Innovation (UKRI) recently said “the cult of the lone genius isn’t helpful”, so I wanted to show the reader how they can fit in as part of a wider community to advance the research and development of AI.

In the first chapter, I interviewed Karen Hao at Massachusetts Institute of Technology (MIT) to explore what AI is technically, and there are some exercises for people to try out. We explain that I used robots as a proxy for AI but that not all AI is robotics and not all robotics uses AI.

There is a bumper chapter of all the rewards that AI offers from climate, to health, and to just making jobs a little less dangerous, dirty and dull.

And of course, an even bigger chapter on all the risks - which I don’t need to tell this audience about!

Once the reader has this understanding under their belt, I then introduce 6 women in the industry all who have a different story to tell about AI.

Finally, there is an extensive book list because this really should be the beginning of their journey and I wanted to sign post the brilliant thinkers of our time.

Before the book list, there are the 5 recommendations which I’ve summarised for you today:

  1. Embrace change - What does it mean to embrace change when the change might take over some of the jobs that we are used to doing ourselves? Can we embrace change in a way that doesn’t leave us vulnerable and draws on our (often hidden) strengths? I believe we can. What does this mean, practically speaking? Whatever field you might be working in, or have worked in in the past, or would like to after you leave school, you can run a thought experiment where you consider which tasks could be automated and then double down on honing the uniquely human ones that can’t.

  2. Talk to a robot - I don’t want to promote any brands here, or unnecessary purchases, but voice activated assistants are a good way to practise constructing sentences and asking questions that AI machines can understand. You don’t need to rush out to the shops – there is AI you can talk to in products you might already have. If you’re an Apple user, talk to Siri, or Cortana if you use Microsoft and Google has an assistant too. Set your alarm to be voice-activated or use a voice assistant to add appointments to your calendar or search the Internet for you.

  3. Protect yourself - It’s important to be conscious that there is a price to pay for the convenience AI provides us. As you now know, data is used to train machine-learning algorithms and has become the most valuable commodity for businesses today. Digital products don’t come with the same warnings as food labels, so you have to do some of the work yourself and ask yourself some key questions to decide if you want to use the application. Being vocal and voting with your wallet is a good way to influence multinationals and reinforce existing legal regulations that they have to follow.

  4. Be part of the conversation - It’s not always easy but I encourage you to do whatever you can to get into the room where decisions are being made. Bring your unique expertise, it doesn’t have to be technical, AI projects will need designers, artists, journalists and people who can translate the real-world experience. But also, you could learn more about AI, train or retrain to become an AI developer. Set up your own group of people to discuss how AI is impacting you or better still find and join a union.

  5. Ensure others are heard - In the book, I’ve focused on the western working woman and ask you to consider your individuality in relation to changing technologies. I also want to stress that we need to think about how this will affect other people, other areas of the globe and life outside of our immediate communities and ways of living. We can’t, for example, just ask, ‘Is this technology for good?’ because what’s good for some people won’t be for others. I ask myself: what are my blind spots? How can I work to address them? Whose voices have I not heard from and why? I decided that the best way I could support women whose voices weren’t being included in the conversation was donating proceeds from this book to Rosa, a charitable fund set up to finance initiatives that benefit women and girls in the UK. You can find out more here.

Just as people who have been excluded from medical research, and worse abused, for centuries are being supported to campaign and rally against the forces and institutions which have caused so much harm, and work with those that want to rectify this. I’d encourage you to have your How to Talk to Robots moment. How will you ensure and fight for a future where equitable genomic medicine helps everyone equally?


Tabitha is the co-founder of CogX, a festival and online platform. Alongside CogX, Tabitha is the chair of the UK government's AI Council and a member of the DCMS Digital Economy Council and on the TechUK board. A serial entrepreneur, Tabitha was the co-founder of video distribution company Rightster (IPO 2011.) Tabitha is the author of How To Talk To Robots - A Girlsguide to a World Dominated by AI. She's also an advisor to Tortoise Media, The Stack, TeensInAI, Raspberry Pi, CarbonRe, Monumo, Cambridge Innovation Capital and The Alan Turing Institute.

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