Ethics for urgency means making ethics a core part of AI rather than an afterthought, says Jess Whittlestone.
"What needs to change?
We need to think about ethics differently. It shouldn’t be something that happens on the side or afterwards—something that slows you down. It should simply be part of how we build these systems in the first place: ethics by design...
You’ve said that we need people with technical expertise at all levels of AI design and use. Why is that?
I’m not saying that technical expertise is the be-all and end-all of ethics, but it’s a perspective that needs to be represented. And I don’t want to sound like I’m saying all the responsibility is on researchers, because a lot of the important decisions about how AI gets used are made further up the chain, by industry or by governments.
But I worry that the people who are making those decisions don’t always fully understand the ways it might go wrong. So you need to involve people with technical expertise. Our intuitions about what AI can and can’t do are not very reliable.
What you need at all levels of AI development are people who really understand the details of machine learning to work with people who really understand ethics. Interdisciplinary collaboration is hard, however. People with different areas of expertise often talk about things in different ways. What a machine-learning researcher means by privacy may be very different from what a lawyer means by privacy, and you can end up with people talking past each other. That’s why it’s important for these different groups to get used to working together."
