Artificial Intelligence, Part I – Setting the Stage

Technological disruption is not new. After two industrial revolutions, the third one was about technology and digitization of society. And we are entering the fourth one, inspired by the arrival of “cyber-physical systems” according to the World Economic Forum. As most headlines focus on current applications of artificial intelligence (in its many forms) and dreams of AI-driven future, few tend to debate what policy adjustments are necessary to benefit from the rise of the machines. Depending on the methodology used, most commonly cited studies forecast that AI can potentially replace between 9% and 47% of all jobs in the next decade or two. Carl Frey and Michael Osbourne [1], using an occupation-based approach, estimate that 47% of all jobs in the US could be replaced. A study by OECD (Arntz, Gregory and Zierahn, 2016) [2], using a task-based approach, estimate that only 9% of jobs across 21 OECD countries face a high risk of automation. While these studies estimate only potential job losses to AI, meaning none might materialize, the scale of the issue should be obvious.

Despite that, there is little policy debate on the subject. Andrew Yang, running for the Democratic nomination, did elevate the issue but it remains outside the political mainstream. Solutions offered to date, be it Universal Basic Income (UBI) or government facilitated retraining programs, are inadequate. “Artificial Intelligence, Automation, and the Economy” report, published by the Obama administration at the end of his presidency, highlighted several policy responses. To sum up, the administration suggested 1) increased investment in AI research, 2) increased focus on education and training of the new generation, 3) strengthening the social safety net (through existing programs) and re-training the workforce. Assuming the best-case scenario where AI replaces 9% of jobs, as suggested by the OECD report, these policy recommendations might suffice. Taking such a wishful approach, however, is irresponsible.