Shohini Kundu
Scientific American
Originally published July 3, 2019
Here is an except:
Unfortunately, in that decision-making process, AI also took away the transparency, explainability, predictability, teachability and auditability of the human move, replacing it with opacity. The logic for the move is not only unknown to the players, but also unknown to the creators of the program. As AI makes decisions for us, transparency and predictability of decision-making may become a thing of the past.
Imagine a situation in which your child comes home to you and asks for an allowance to go see a movie with her friends. You oblige. A week later, your other child comes to you with the same request, but this time, you decline. This will immediately raise the issue of unfairness and favoritism. To avoid any accusation of favoritism, you explain to your child that she must finish her homework before qualifying for any pocket money.
Without any explanation, there is bound to be tension in the family. Now imagine replacing your role with an AI system that has gathered data from thousands of families in similar situations. By studying the consequence of allowance decisions on other families, it comes to the conclusion that one sibling should get the pocket money while the other sibling should not.
But the AI system cannot really explain the reasoning—other than to say that it weighed your child’s hair color, height, weight and all other attributes that it has access to in arriving at a decision that seems to work best for other families. How is that going to work?
The info is here.