Michael I. Jordan
Machine Learning Researcher
The Berkeley professor often ranked the most influential computer scientist alive, who champions machine learning as a new engineering discipline while rejecting the “AGI” framing as hype.
In his words
Let’s broaden our scope, tone down the hype and recognize the serious challenges ahead.
For the foreseeable future, computers will not be able to match humans in their ability to reason abstractly about real-world situations.
Biography
Michael I. Jordan (born 1956) is a professor at UC Berkeley who bridged statistics and computer science to help create modern machine learning. A 2016 Science analysis ranked him the most influential computer scientist in the world, and his students and postdocs — including Andrew Ng — populate the field’s leadership. His work on graphical models, variational inference and distributed optimization underlies much of the machinery now marketed as AI.
The revolution that hasn’t happened
Jordan’s 2018 essay “Artificial Intelligence — The Revolution Hasn’t Happened Yet” became the canonical statement of the anti-hype, pro-technology position. The current boom, he argued, is not human-imitative AI at all but a new branch of engineering built on data and statistics — and calling it “AI” blinds the public to both its limits and its real promise. He warned that the classical dream of human-level reasoning remains unsolved, and urged the field to conceive of “a human-centric engineering discipline” focused on systems that demonstrably improve lives: medical pipelines, markets, logistics.
He has kept up the drumbeat since — telling IEEE Spectrum in 2021 to “stop calling everything AI” — while remaining among the technology’s deepest optimists about what well-engineered learning systems can do for human welfare. His quarrel is with the framing and the grandiosity, never with the mathematics or its deployment.
Where they stand in the war
Who backs them up
Sources & further reading
Canonical record: https://battlelines.ai/topic/michael-i-jordan