AI and the economy

Everything you needed to know about AI and the economy

As AI-related activity has increased exponentially Furman and Seamans review the latest research on: a) AI derived productivity gains; b) effect of AI on labor markets; c) impact of AI on industry concentration; d) AI related policies and regulations.

AI and the Economy
Authors: Jason Furman, Robert Seamans
From: Harvard University, New York University

Has AI hit a limit?

[…] the benefits of the new technologies are being enjoyed by a relatively small fraction of the economy, but the technologies’ narrowly scoped and rivalrous nature creates wasteful “gold rush”-type activities. Both those seeking to be one of the few beneficiaries, as well as those who have attained some gains and seek to block access to others, engage in these dissipative efforts, destroying many of the benefits of the new technologies.

Artificial Intelligence and the Modern Productivity Paradox: A Clash of Expectations and Statistics
Authors: Erik Brynjolfsson, Daniel Rock, and Chad Syverson
From: MIT, University of Chicago

A high level explanation of the science behind AI

The difference between machine learning (ML) and AI:
ML is basically limited to predicting a future that looks mostly like the past. These are tools for pattern recognition. In contrast, an AI system is able to solve complex problems that have been previously reserved for humans. It does this by breaking these problems into a bunch of simple prediction tasks, each of which can be attacked by a ‘dumb’ ML algorithm.

Just as Big Data led to Data Science, a new discipline combining Statistics and Computer Science, AI will require interdisciplinary pioneers who can combine Economics, Statistics, and Machine Learning.

The Technological Elements of Artificial Intelligence
Author: Matt Taddy
From: University of Chicago