Interview for the Argentinian El Cronista: “Do presidents dream of electric ministers?”

On August 26, 2019, Sebastiande de Toma published an article in the Argentinian business newspaper El Cronista based in part on an interview with Steve Omohundro. His article is titled “Suenan los presidentes con ministros electricos?” or “Do presidents dream of electric ministers?”:

https://www.cronista.com/columnistas/Suenan-los-presidentes-con-ministros-electricos-20190826-0057.html

He explores whether AI will help politicians make better economic decisions.

Steve suggested 4 levels of AI support for politicians:

  1. AI’s can build much better economic models from a much wider range of data than traditional econometric data. For example, an AI model might include video feeds from TV news, social media posts, video feeds from commerce hubs, audio from radio shows, etc. All of the data can inform much richer economic models. Monte Carlo simulations could then make much better predictions about the impact of policy interventions and repeated simulations can reveal how robust the response to an intervention might be.
  2. AI’s can help politicians recognize their cognitive biases and counteract them. The field of “behavioral economics” has identified a large number of biases, especially around small probability events and the different perceptions of gains and losses. AI’s can model the correct Bayesian responses and help a politician to counteract his intuitive biases.
  3. In addition to helping a politician simulate the effects of a policy intervention, AI’s can help to create policies with a desired impact. Economic models with policy knobs can be automatically optimized for the best predicted outcomes.
  4. Recently there have been advances in using AI to solve complex game theoretic problems (eg. the Libratus and Pluribus AI’s which recently beat expert human poker players). This kind of AI could be applied to the problem of new policy causing other parties to change their behavior. Well-designed policy should account for these responses and lead to desirable outcomes taking account of all participant’s likely behaviors.

Sebastiande’s wrote (as translated by Google Translate):

2019-08-27_182200

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