Anthropic Forms Council to Explore AI’s Economic Implications
Anthropic has created a council to examine the economic implications of artificial intelligence (AI) development.
The startup’s Economic Advisory Council, announced Monday (April 28), is composed of “distinguished economists” who will advise the company on AI’s effect on labor markets, economic growth and wider socioeconomic systems.
“As AI capabilities continue to advance, it has never been more critical to understand the opportunities and challenges this evolution presents to jobs and how we work,” the company said in its announcement. “The Council will provide important input on areas where we can expand our research for the Economic Index. The Council members’ deep domain expertise will help guide our research on the changes AI will bring to the global economy.”
The members of the council include: Dr. Tyler Cowen of George Mason University, Dr. Oeindrila Dube of the University of Chicago, and Dr. John Horton, MIT Sloan School of Management.
Joining them are Dr. Anton Korinek of the University of Virginia’s Department of Economics and Darden School of Business, Dr. John List of the University of Chicago, and Dr. Ioana Marinescu, of the University of Pennsylvania School of Social Policy and Practice.
Also on the council are Dr. Tomas J. Philipson, former member and acting chairman of the White House Council of Economic Advisers, and Dr. Silvana Tenreyro of the London School of Economics.
The effort comes as today’s companies are looking for AI that delivers more than it dazzles, as PYMNTS wrote last week.
The newest PYMNTS Intelligence data from the April edition of the CAIO Report, done in collaboration with Coupa, found that more than over 80% of U.S. chief financial officers (CFOs) at large enterprises are either using AI in their accounts payable (AP) processes or are weighing its adoption.
“Specifically, the report found that CFOs are demanding tools that can offer real-time visibility into expenditures, sharpen vendor negotiations and guide more strategic budget optimization,” PYMNTS wrote. “With margins tightening and pressure mounting to do more with less, these three capabilities have become non-negotiable for finance teams operating with innovation.”
As that report added, since its machine learning and data analysis era, enterprise AI has promised to change how businesses operate by streamlining operations, forecasting with precision and automating decision-making at scale. But for finance chiefs, the hype has often outstripped reality.
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