AI has been hailed as a transformative technology with McKinsey estimating it could add $26 trillion to the global economy. While many investors have already jumped on the AI bandwagon, not everyone agrees.

Daron Acemoglu, Institute Professor at MIT and author of books including Why Nations Fail, takes a critical look at AI and explains why the economic and social benefits may have been overstated. He joins John Lee of Bloomberg Intelligence and Katia Dmitrieva of Bloomberg News on the Asia Centric podcast.

AI has been hailed as a transformative technology with McKinsey estimating it could add $26 trillion to the global economy. While many investors have already jumped on the AI bandwagon, not everyone agrees.
Daron Acemoglu, Institute Professor at MIT and author of books including Why Nations Fail, takes a critical look at AI and explains why the economic and social benefits may have been overstated. He joins John Lee of Bloomberg Intelligence and Katia Dmitrieva of Bloomberg News on the Asia Centric podcast.

For all its vastness and power, Asia remains a mystery to global investors. Bloomberg Intelligence talks with the experts who know Asia best, unspooling its riddles and peeling back its layers with fascinating stories and insights at the intersection of business, wealth, and power. Investors will come away with new understanding of the risks and opportunities that await in a region rife with complexity, yet teeming with ambition and potential.

For all its vastness and power, Asia remains a mystery to global investors. Bloomberg Intelligence talks with the experts who know Asia best, unspooling its riddles and peeling back its layers with fascinating stories and insights at the intersection of business, wealth, and power. Investors will come away with new understanding of the risks and opportunities that await in a region rife with complexity, yet teeming with ambition and potential.

Asia Centric by Bloomberg Intelligence

AI Economic Impact Overstated, Says MIT's Acemoglu

https://api.omny.fm/orgs/e73c998e-6e60-432f-8610-ae210140c5b1/clips/50b9a3bd-2d30-4a40-b77a-b1ee0091c70e/transcript

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