Ajay Agrawal, Joshua S. Gans, and Avi Goldfarb: Artificial Intelligence: The Ambiguous Labor Market Impact of Automating Prediction: "Artificial intelligence does not fit easily into existing analyses of the effect of automation on labor markets. The reasons are threefold. First, prediction is always strictly complementary to other tasks—namely decision-related tasks. Those tasks can be existing or newly possible because of better prediction. Second, better prediction improves decisions—whether taken by labor or capital—by enabling more nuanced decisions through the reduction of uncertainty. Finally, it is not yet possible to say whether the net impact on decision tasks—whether existing or new— is likely to favor labor or capital. We have found important examples of both, and there is no obvious reason for a particular bias to emerge. Thus, we caution on drawing broad inferences from the research on factory automation (for example, Acemoglu and Restrepo 2017; Autor and Salomons 2018) in forecasting the net near-term consequences of artificial intelligence for labor markets...
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