Another woman has moved into my home. Or at least, my partner thinks so. For him, Alexa is “her.” But I dispute that. For me, Alexa is most definitely “it.”
Studies have repeatedly shown that both women and men prefer digital assistants to have female voices because they believe them to be more welcoming and understanding - which is why Alexa and friends are made with dulcet feminine tones. But isn’t that just a historic, old-fashioned stereotype? Do service bots really need to be ‘female’ to be relatable? If AI is going to run our lives, perhaps we need to challenge some of these preconceptions and come up with fresher perspectives.
AI and machine learning infiltrates almost everything we do: it helps organise our diaries, gives us the latest headlines, sorts out pizza for tea and soundtracks our evening with our favourite tunes. More than that, it determines our behaviours, thought processes, buying patterns, and even our worldviews – it’s like Facebook’s filter bubble but on a much grander scale. Increasingly in the future, AI will shape our perceptions of our world, and not just influence the choice of what we eat, buy or what we listen to.
Which means the hands and minds making the technology have a direct impact on us as humans, and on the world around us. Therefore it is vital that we include more female perspectives in this new world, and we need more women of diverse backgrounds to have a hand in creating it - and not just give virtual assistants female voices.
AI is like a child. How it grows is down to how we nurture it, and unless we design these systems from the start with inclusion in mind we will create systems that reflect the multiple biases and stereotypes that have damaged and limited our world today. AI becomes biased through the data that is used to train it and it’s hard for any of us, men and women, to be aware of our biases.
Bias creeps in when your data sets aren’t inclusive enough and AI then learns from our own prejudices. We’ve seen Facebook algorithms influence how we view world events, by skewing what’s on our newsfeed. We’ve seen how Twitter taught Microsoft’s AI chatbot Tay to become a misogynistic, anti-Semitic racist in less than a day. If we don’t challenge bias now, like a supertanker, it’ll be very hard to turn around.
Inclusion has to be the aim for the future of AI, but there’s a potential paradox in building diversity while being tolerant of all points of view. Who decides which points of view we want to take forward into this brave new world and which to leave behind? How do we create AI which is in tune with human minds, but ignores the worst elements of human prejudices? Where do we find neutral data sets - do they even exist? Should AI to be programmed around an aspirational image of the world we want or a realistic version of the world today? Data can take time to catch up with culture. How do we create AI that can be more sensitive to this?
It’s a fine line to tread but ultimately, we need to build trust with AI and the people creating it and trust they are creating unbiased technology.
Which isn’t so easy when men make up 85% of the machine learning workforce, and when there’s a parade of bad news about how women are treated in Silicon Valley. Tech innovation is actually a great environment for women – it’s a naturally open and collaborative industry. The key is to get girls interested in joining the industry from an early age. It’s going to be a challenge to get the numbers up, but the STEM movement and Melinda Gates’ AI4All campaign are working hard to improve the situation.
An independent report commissioned by the UK government last October recognises this and stresses the need for greater diversity in the British AI workforce. It states: “Government, industry and academia must embrace the value and importance of a diverse workforce for AI, and should work together to develop public information aimed at breaking down stereotypes and broadening participation.”
The report also proposes the creation of Data Trusts Support Organisation, incorporating an ethics body to ensure algorithmic accountability – something that governments globally should be considering.
That’s why it’s so vital to get more women into AI. Getting women involved is not just about ticking ethical and social boxes; it’s now becoming a commercial imperative.
An Oxford University team estimates that up to 47% of jobs could be taken over by AI in the next 20 years, meaning that humans will be left with the ones that machines haven’t mastered, like care-giving, wellbeing and nurturing – anything that requires the human touch and emotional intelligence. It has been estimated that AI could add an additional £630bn to the UK economy by 2035 and women’s empathy skills - the ability to collaborate, listen and self-regulate - will be in demand more than ever as AI continues to grow.
I don’t believe for a moment that women are innately better at these qualities than men, but I do know that we are encouraged to be. Maybe in the future this will change, as men discover a real incentive to be more empathetic: the demand for universal emotional intelligence could even, finally, shift the male/female archetype.
It’s a nice thought, and fits with the late tech historian Melvin Kranzberg’s observation that “Technology is neither good nor bad; nor is it neutral.” AI is all about the context. And in the context of my home, Alexa is gender neutral, OK?