How do you view the current rush among organisations to establish supremacy in the AI world?
Wilkerson: I think that we are trying to live in this world that we want to happen. We are speaking about it as though it already is. And, you know, it’s like, ‘Get on board!’ But we need to take a pause. We need to look at both sides, the front and the back, before we again step on the pedal. I think it’s to see AI as an augmenter and not as a replacement, to figure out how to make sure that the human element is integral to it, how management and leadership have to be different from what they were in the past, because this is a different sort of beast.
Even looking at it technically, when you are talking about a software development lifecycle, it’s different from the AI development lifecycle because of the hallucinations and all those types of things. And the fact that the data is not trained on so many portions of our world, and therefore it’s not really serving us right. And we have to be iterative about how we are applying it to our solutions.
How do you think greater presence of women in the tech industry can make things better?
Krishnan: I think women anywhere in leadership will have an impact. You cannot have the world run by people who do not represent the people it is run for. And there are very hierarchical rules of power that currently govern the universe, which need to be turned because the world is leaning towards community. And that comes in when you have representation from everybody. Brenner keeps saying that tech has to be built by the people it is being built for.
It cannot be built by a section of society that is not in touch with what the on-ground reality is. And if you come closer home to India, the technology landscape you see in urban India versus rural India is so different for the very same reason. The grassroots innovation you see coming up is so vastly different because, in India, that is a much larger populace.
But the tech world, especially the AI world, is right now completely dominated by men. How can women-led leadership actually change that?
Wilkerson: When I was in education, we brought robotics into the classroom. And what we found very quickly was that the boys would just keep trying something until it worked.
When I talked to a group of engineers at Microsoft who were doing AR and VR, and they were designing the headsets, a certain percentage of them would go to market and just fail, and they did not understand why. Well, they were male-only groups. When they added a woman to the test group as they were putting together the prototype, they would put the prototype on her head and the sound would immediately stop.
Well, it turns out that touching her curly hair stopped the mechanism from working. So they had never had anybody with hair past their ears to test, and no one with curly hair. I mean, that is a simple, weird kind of example, but it just shows you that you need different physicalities at the table. You need different backgrounds and experiences at the table to make a difference.
How do we dismantle it so as to build structures that are safe?
Wilkerson: There are these people who are developing the LLMs and the AI agents. And then there are people who want to be able to do whatever they want with it. So they have lobbyists who lobby against any sort of regulation to slow them down.
They are like little boys in school who just want to try and do not want anybody impeding them. And so we need voices that stand up and say, ‘Have you thought about this? We have done some testing and there is some harm here.’
And there is this assumption that people just need to get on board with it versus we need to get on board with making sure that it works for people, which is another thing that women are uniquely capable of.
Do you see women’s jobs more at risk in the age of AI?
Wilkerson: It is what I fear. And if you look at what is being automated first, it is the things that are seen as non-essential. It was sort of a joke in the US where, during the pandemic, the people who were lauded as essential are now the ones who are most at risk, not only of losing their jobs, but also of policy change that downgrades their jobs from essential to non-essential. And most of them are jobs that are heavily done by women.
Krishnan: There is also a United Nations report that says women’s jobs are disproportionately at risk from AI, with nearly 28 per cent of roles threatened versus 21 per cent for men. And when people lose jobs, women lose jobs first. For every child a man has, he gains about 7–9 per cent in salary. For every child a woman has, she loses 4–7 per cent of her salary. So when you look at any kind of climate impact, any kind of sustainability impact, or any kind of war, the first people who are impacted are women. And that is happening now with the AI flow as well.