Karen Hao argues in MIT Technology Review that AI’s development reflects human choices

Karen Hao argues in MIT Technology Review that AI’s development reflects human choices

Published July 9, 2025, MIT Technology Review presents a conversation in which AI journalist and author Karen Hao argues that the AI industry functions like an empire. She connects OpenAI’s choice to advance AI by scaling existing techniques—using more data and larger supercomputers—to competition with Google and Sam Altman’s ability to raise capital. Hao says this path produced technical progress, but carries substantial costs, including energy and freshwater use, pollution, exploited labor and entrenched inequities. She argues that the idea of artificial general intelligence (AGI) can justify continued consumption and concentrated control, despite no shared agreement on what AGI is or whether it is possible. Her alternative is not to abandon AI: she advocates task-specific systems, community consent and greater public accountability. Hao points to a Māori community’s speech-recognition project as an example of community involvement in deciding whether to build a tool and how to use its data. She ends by urging people to turn public attention into action and says regulation should increase transparency across AI’s supply chain. The conversation does not establish how widespread the described harms are or whether her proposed alternatives can deliver comparable benefits.

Publication: 79cbdbf1-b521-bb8d-6f76-70ff42f29350

attribution — pass: The reading attributes the arguments to Karen Hao, speaking in an MIT Technology Review Roundtables conversation about her book. Her claims are framed as her arguments rather than established facts. The 'human choices' framing was raised by Niall Firth, but Hao explicitly endorses it.

So that is ultimately how you can see that technology is a product of human choices and human perspectives.

summary — pass: Accurately conveys Hao's main arguments: the empire framing, OpenAI's bet on scaling, its costs, AGI as a shifting justification, and her alternatives (task-specific AI, community consent, accountability, transparency). Scaling is explained in plain language, and AGI is defined on the page. One small imprecision: 'She ends by' is slightly off, because the conversation actually closes with her blunt question to Altman. This does not distort meaning. The question follows from the stated limitation.

What degree of harm do you need to see in order to realize that you should take a different path?

date — pass: The originalPublished instant of 2025-07-09 matches the stated July 9, 2025 date at day precision. The page modification came one second after publication, so it is not a substantive later edit. Sidebar items such as the AlphaGo ten-year piece are later additions to the page, but the reading does not use them. There is no hindsight framing, and this is a publisher page, so no archive disclosure is needed.

support — pass: Each claim is source-stated with matching excerpts, covering scaling, Google competition, Altman's fundraising, costs, the AGI vacuum, task-specific AI, the Māori project and transparency. The limitations appropriately note that the harms and the alternatives' benefits are not independently established. No unsupported benefits or costs are implied.

So if there were one major intervention that regulators could have, it should be to dramatically increase the amount of transparency along the supply chain.

media — pass: No media is selected and no verified media candidates were supplied, so nothing is misidentified.