Nobel laureate talks about artificial intelligence at seminar


The Department of Economics at Emory University organized a Event on the impact of artificial intelligence on growth, jobs and inequalities on October 27. The event featured Thomas Sargent, 2011 Nobel Laureate in Economics and William Berkley Professor of Economics at New York University.

Sargent defined artificial intelligence as two distinct expressions: artificial, meaning non-human, and intelligence, meaning human. He explained that human intelligence is characterized by pattern recognition, decision making, and awareness of time and space.

During the event, Sargent identified Steven Pinker, a world-renowned psychologist, as a notable contributor to his knowledge. Namely, Sargent said that humans “did not evolve to know” biology, statistics and economics, yet these subjects are used to create artificial intelligence.

Photo courtesy of Peking University

Extending beyond contemporary figures, Sargent’s intellectual influences also include Galileo Galilei and Charles Darwin. He explained that both used economic tools to generalize conceptions about the world.

“Artificial intelligence and machine learning are descendants of the methods first used by Galileo,” Sargent said.

Machine learning is “building a model of the world and using the model to make decisions,” Sargent said. This makes machine learning a key facet of artificial intelligence, as it is part of what provides artificial intelligence tools with access to data to make predictions.

Sargent listed economic topics such as statistics, calculus, linear algebra, optimization, and linear programming as fundamental tools of artificial intelligence.

“A lot of ideas from economics have been imported into artificial intelligence,” Sargent said.

Multi-agent decision theory is an important aspect of economics, which can produce research on a realistic approach to modeling social structure, modeling the market and predicting an appropriate response to a real crisis. This theory has been computerized into a form of artificial intelligence that can help economists make predictions.

Sargent shared two great related triumphs involving the intersection of machine learning and economics: An infamous game of chess. meet and one Game of Go.

In a 1997 chess match, the world’s highest ranked chess player Garry Kasparov played against a supercomputer called Deep Blue, and / or the first time artificial intelligence beat a human. It was a monumental feat and helped people start to see a future for this field.

In 2017, Google’s DeepMind artificial intelligence defeated the world’s No.1 Go player, Ke Jie. Go is considered one of the more complex game strategy board games, so Sargent said the victory marked a new frontier for artificial intelligence.

A question-and-answer period followed Sargent’s talk, and attendees expressed concerns that artificial intelligence could replace work done by humans.

Sargent responded that while there have been many jobs where artificial intelligence has supplanted humans, there is a plethora of new jobs being created to manage the technology.

“One thing you can do in education is not to get stuck. Plan for flexibility and some robustness, ”said Sargent. “I think there are a lot of jobs that are going to get better with artificial intelligence and machine learning.”

Another participant asked about the real applications of artificial intelligence. Sargent explained that a form of artificial intelligence is used for second-price auctions to quickly assign ads. He noted that even the IRS uses machine learning to fight tax filing lobbies.

Closing the seminar, a participant asked Sargent for advice on pursuing a career in economics. He advised the students to follow “linear algebra, calculus, and statistics”, but more importantly, suggested that they “persist”.

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