Women and the Fourth Industrial Revolution

In a series exploring women in international affairs, Gitika Bhardwaj talks to mathematician Anne-Marie Imafidon, founder of STEMettes, about how the coming technological change could affect women.

Interview
6 minute READ

Dr Anne-Marie Imafidon MBE

Co-Founder and CEO, STEMettes

Gitika Bhardwaj

Former Editor, Communications and Publishing

Technology is reshaping the world of work with automation, artificial intelligence and robotics increasingly being integrated into workplaces. What advantages does the so-called Fourth Industrial Revolution present for women?

There are two key ones I would like to highlight. The first is that, research has shown that some of the careers that won’t be as impacted by the Fourth Industrial Revolution, are the caring and teaching professions, professions where you have to connect to human beings. If this is so, there’s actually a huge opportunity for women who work in these industries. They almost have a head start over men since they have the opportunity to keep their jobs in these sectors, move up the career ladder and attain managerial positions, conditional on their expertise being valued in these professions of course.

The second is the set of opportunities that technological change presents for women who work in industries where you don’t have to be on site. With a sector like mining, you have to be there physically working in the mines. But a lot of the technical roles will be able to be done from a distance. So there is the benefit for women to be able to learn, train and work at a distance in these roles, working flexibly, even more so then they are able to do at the moment.

The technological transition has also been criticized for the negative impact it could have on workers, who could increasingly be replaced by these technologies, with women expected to be more disproportionately affected than men.

What are the challenges that women face in this time of change and how could it affect women differently in developed and developing countries, in low-skilled and high-skilled jobs and from low-income and high-income backgrounds?

Currently, we don’t value the work that women do, which if everyone started to fight over [the same jobs], women would face the risk of losing out over their male counterparts. The reason for this is, if something is seen as important, the men usually take over, which is what we’ve seen happen in the technology industry. Originally, it was women who were doing it, and then when it became more important, and more commercially viable, we saw the men get involved. So what we’re seeing is that, when we talk about people losing work, it’s usually the women that are giving up working to do childcare – and everything else that counts as unpaid labour – at home.

When things are replaced by algorithms that are trained on historical datasets we’re seeing these applications making decisions based on biases against women.

The other problem is with the biases we’re seeing being replicated in some applications. When things are replaced by algorithms that are trained on historical datasets, we’re seeing these applications making decisions based on biases against women. Whether that’s in recruitment for jobs, decisions being made for mortgages and everything else you can think of where a computer can literally say no to someone because of the biases that have been fed into them. Without us being proactive in forcing people to be, not only ethical, but equitable, in what they’re building, we will likely continue to see women being disproportionately affected.

How could it affect women differently? I’m not sure. The fact that we are much more globally connected now than in the past few technological revolutions means that, anything that happens to women in the developed world, will happen even more so to women in developing countries.

If we look at the number of women working in the science, technology, engineering and mathematics industries at the moment, we know in developing countries, the proportion is slightly higher, so that means they have more technical women working in these sectors, although whether they are staying in those sectors is another matter but, importantly, they’re doing better than women in developed countries.

But technology is only as good as the adoption you have from the people and the reaction to technology has been different around the world. That might have something to do with language: a lot of these programme languages are in English so there might be a correlation between English-speaking versus non-English speaking countries.

The impact of artificial intelligence, for example, is also shown to have more of an impact on women in developed countries than women in developing countries because of how much it has been realized in the developed world.

Research, as you mentioned, has revealed that some applications based on machine learning have been found to replicate the social biases which are fed into them, notably biases around gender. How can these processes be improved, so as not to perpetuate gender biases, and who is responsible for its oversight?

That’s the big question at the moment. Should it be governments or technology companies or someone else overseeing the technological change that the world is experiencing? There are several quick wins we could do to improve these processes. For example, regulation can help – although it feels like a stick rather than a carrot in trying to solve the problem – but it is one that needs to be considered because the sector doesn’t necessarily see it as its responsibility. For example, recently, Mark Zuckerberg said that governments should be regulating the public’s use of data, which is a bit of a strange thing to say, when he is the one who has created the platform that’s using our data.

For better or for worse, everyone should be able to contribute to the discussion around technology in order to arrive at appropriate solutions, but this involves a shift of power.

Interestingly, the Institute for the Future of Work is looking at frameworks you might be able to apply to the use of algorithms at work to ensure you have considered what ethical practice looks like and any gaps in the datasets that you have before building anything. It’s important that we don’t just have people who are technically competent working in roles but that they also have some sort of training in ethics. This will help to limit the probability of any biases being fed into the codes when building applications.

In terms of whose responsibility it is, I think it’s a joint responsibility, because it’s a joint risk, since all of us lose out when our applications are biased. Governments lose out, companies lose out and society loses out too. That’s why I’m advocating to set up a discussion across society where governments, companies and the layperson can come together to discuss the best way forward.

We currently have this thing in technology where it’s the programmer against the user when we should all be participants in the system. What this means is that, for better or for worse, everyone should be able to contribute to the discussion around technology in order to arrive at appropriate solutions. But this involves a shift of power which we know is a difficult thing to get people to do. But it is an important step that we have to take otherwise we will get companies marking their own homework which is not good.

Image 2

Space scientist and mathematician, Katherine Johnson, works at her desk with an adding machine and a 'Celestial Training' device at NASA Langley Research Center in 1962 in Hampton, Virginia in the United States. Photo: Getty Images.

Space scientist and mathematician, Katherine Johnson, works at her desk with an adding machine and a ‘Celestial Training’ device at NASA Langley Research Center in 1962 in Hampton, Virginia in the United States. Photo: Getty Images.

— Space scientist and mathematician, Katherine Johnson, works at her desk with an adding machine and a 'Celestial Training' device at NASA Langley Research Center in 1962 in Hampton, Virginia in the United States. Photo: Getty Images.

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From Ada Lovelace, to Marie Curie, to Katie Bouman – who recently developed an algorithm which made it possible for the world to see the first photo of a blackhole – there have been countless women working in the science, technology, engineering and mathematics (STEM) industries.

However, research shows that girls are less likely to study STEM subjects at school and less than 30 per cent of the world’s STEM researchers are currently women. What have been the challenges to women working in these fields and can the Fourth Industrial Revolution change this?

I put it down to poor storytelling based on social norms. This, in fact, came up with Katie Bouman recently. When we talk about Albert Einstein or Isaac Newton – in other words dead white males – history appears to celebrate them as if they worked in isolation, whereas, when Katie Bouman’s achievement was revealed to the world, some commentators drew attention to the fact that she was only in charge of a team of people developing the algorithm that made it possible to take the photo of a blackhole.

‘She’s only one of a group of people’ was the angle some were taking. But what about the other 100 or so people that helped Albert Einstein or Isaac Newton? Because they had people who helped them in their work too.

We have this habit of erasing people’s stories if it doesn’t fit with the dead white male archetype which has a knock-on effect because others aren’t then aware that someone like them has done something incredible in the STEM sectors.

So whether it’s Ada Lovelace or Marie Curie – two women that actually a lot of people can now name but we also have Hedy Lamarr, Steve Shirley and Katherine Johnson – there are so many of these amazing stories that have gone untold which has emboldened people who don’t believe that women should be working in STEM.

Sadly, there are people who then use this as an opportunity to frustrate women studying or working in STEM and unfortunately we don’t currently have the right kind of structures to prevent this from happening. So that, for me, is the biggest challenge that women face.

The Fourth Industrial Revolution presents us with the opportunity to unite as human beings against the algorithms. That means being more inclusive about what being a human is. It’s not just about men losing roles to women but also humans losing roles to algorithms. There are opportunities to right the wrongs of the past with the Fourth Industrial Revolution and to do so en masse. We’re still working out the most ethical way to do this where we are countering the biases in the datasets that we’re building all of our algorithms on. We all know that life is imperfect, but by repeating these imperfections in our algorithms, we are just designing our future with all of those still included.

Looking forward, in your view, is the technological transition going to be a force for division or equality for society in the future?

Working with a lot of young girls at STEMettes, I have seen the capacity for social mobility that learning technical skills can provide them with, which they are then going to take with them into their careers so I do see the technological transition as being capable of being a force for equality.

The Fourth Industrial Revolution presents us with the opportunity to unite as human beings against the algorithms.

I do worry, though, about the impact it will have on human beings. I don’t think it’s technology that’s dividing us, it’s human beings driving the technology that’s dividing us, the same way that human beings have divided themselves throughout human history, before they had technology to blame.

Technology is a reflection of us. It doesn’t want to be a divider or an equalizer. It just follows the instructions that it’s been given by us. We would do well to remember that.