Kay talks to us about why AI Ethics matter during her presentation at the RE•WORK Applied AI Virtual Summit. But the second piece is really, well, if you are not creating trusted AI, then you're going to have a loss of brand value if something goes wrong, so the risks have to really be weighed with the benefits of AI. I also I don't think that you could ignore trusted AI or AI ethics anymore because we've got over 160 different sets of ethical principles out there, from Beijing to Montreal to everywhere in the world. We also worked with the Singaporean Government on how companies could ethically use AI. A few other places where we have high-risk case uses of AI and lots of ethical issues involved is obviously facial recognition technology, we're working on a project with France around that.

You might have noticed a comment was made on the first article in this series: I didn't mention the'why' as a KSF in bringing home a machine learning project. And it's true, forgetting the why is a serious problem. As the commenter noted: Unless there's a why and a businessperson involved, all you've got is a handicapped specialty group who have been given tools, but not told what to do with them. So here's my amended list of KSFs for a machine learning project: The why is the business reason for the project. It's rarely as exciting or motivating as the technology involved. But it pays the bills.