Biased Data and AI for Humanity
TT You said that the intelligence is from knowledge and knowledge is acquired from data?
YB That’s right.
TT But if data is biased, what happens? Some social scientists criticize most data for being based on male, Caucasian middle aged…
YB That’s right.
TT So if a young woman of colour applies, for instance, for an insurance policy, AI might say no because they don’t have enough data for those applicants.
YB Yes, absolutely. I think there are technical solutions and social solutions to this problem. We have to change our social norms, for example, so that companies building products use technological solutions and logistical solutions, for example, in the way that the data is collected, in the way that it’s described and managed, and in the particular learning algorithms that are used because we know techniques that can mitigate the bias and discrimination. So we can probably include those techniques, but more importantly we need to make sure that companies and governments use them.
TT Is that why you think it’s important that both social scientists and natural scientists work for AI together?
YB Yes.
TT I love the idea of “AI for humanity” as you have in the Mila here.
YB Right, because the AI researcher might not realise some of the social issues that could be involved in the deployment. I think it’s particularly important for people who are doing research or development of products that is close to something that people will use, in large-scale deployment for example.