Watching the Generative AI Hype Bubble Deflate
AnonTechie writes:
As a part of the Allen Lab's Political Economy of AI Essay Collection, David Gray Widder and Mar Hicks draw on the history of tech hype cycles to warn against the harmful effects of the current generative AI bubble.
Only a few short months ago, generative AI was sold to us as inevitable by AI company leaders, their partners, and venture capitalists. Certain media outlets promoted these claims, fueling online discourse about what each new beta release could accomplish with a few simple prompts. As AI became a viral sensation, every business tried to become an AI business. Some even added "AI" to their names to juice their stock prices, and companies that mentioned "AI" in their earnings calls saw similar increases.
Investors and consultants urged businesses not to get left behind. Morgan Stanley positioned AI as key to a $6 trillion opportunity. McKinsey hailed generative AI as "the next productivity frontier" and estimated $2.6 to 4.4 trillion gains, comparable to the annual GDP of the United Kingdom or all the world's agricultural production. Conveniently, McKinsey also offers consulting services to help businesses "create unimagined opportunities in a constantly changing world." Readers of this piece can likely recall being exhorted by news media or their own industry leaders to "learn AI" while encountering targeted ads hawking AI "boot camps."
While some have long been wise to the hype, global financial institutions and venture capitalists are now beginning to ask if generative AI is overhyped. In this essay, we argue that even as the generative AI hype bubble slowly deflates, its harmful effects will last: carbon can't be put back in the ground, workers continue to face AI's disciplining pressures, and the poisonous effect on our information commons will be hard to undo.
An archival PDF of this essay can be found here.
[Source]: Harvard Kennedy School
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