In the recent Wall Street Journal article, “What Econ 101 Can Teach Us About Artificial Intelligence,” Brattle Academic Advisor Joshua Gans and economists Ajay Agrawal and Avi Goldfarb are featured for their research in artificial intelligence (AI) and machine learning, and how technological advances can often lead to more jobs for humans, not fewer.

The WSJ article references Drs. Gans, Agrawal, and Goldfarb’s article in the Harvard Business Review, “The Simple Economics of Machine Intelligence,” which emphasizes how the longstanding economic concept of lower costs for goods or services resulting in higher demand still applies today, despite the evolving digital economy.

The same lens can be applied when considering machine intelligence, a prediction technology. The authors believe the economic shift will occur with the drop in the cost of prediction, resulting in a rise in the value of other things that complement prediction, such as human judgment-related skills. When considering the impact on jobs, one must assess whether the technology competes with or complements the role. While AI is likely to create “winners and losers” within certain industries and occupations, the authors argue that the aggregate effects will be positive.

The full article can be read here.