AI SNAKE OIL

Two academics in the burgeoning field of AI survey the landscape and present an accessible state-of-the-union report.

Like it or not, AI is widespread. The present challenge involves strategies to use it properly, comprehend its limitations, and ask the right questions of the entrepreneurs promoting it as a cure for every social ill. The experienced authors bring a wealth of knowledge to their subject: Narayanan is a professor of computer science at Princeton and director of its Center for Information Technology Policy, and Kapoor is a doctoral candidate with hands-on experience of AI. They walk through the background of AI development and explain the difference between generative and predictive AI. They see great advantages in generative AI, which can provide, collate, and communicate massive amounts of information. Developers and regulators must take strict precautions in areas such as academic cheating, but overall, the advantages outweigh the problems. Predictive AI, however, is another matter. It seeks to apply generalized information to specific cases, and there are plenty of horror stories about people being denied benefits, having reputations ruined, or losing jobs due to the opaque decision of an AI system. The authors argue convincingly that when individuals are affected, there should always be human oversight, even if it means additional costs. In addition, the authors show how the claims of AI developers are often overoptimistic (to say the least), and it pays to look at their records as well as have a plan for regular review. Written in language that even nontechnical readers can understand, the text provides plenty of practical suggestions that can benefit creators and users alike. It’s also worth noting that Narayanan and Kapoor write a regular newsletter to update their points.

Highly useful advice for those who work with or are affected by AI—i.e., nearly everyone.