Matthew Gray
TGT Manager, Machine Intelligence Research Institute
Matthew Gray is TGT Manager at the Machine Intelligence Research Institute (MIRI). He previously worked as a data scientist at Indeed and Samsung, and in 2017 wrote MIRI's published response to Maciej Cegłowski's talk skeptical of superintelligence risk, arguing that long-term AI hazards are harder and more complex than short-term ones.
Key arguments & positions
- Argues long-term AI hazards are harder and more complex than short-term ones, and that attention to long-term risk helps draw attention to near-term misuse rather than distracting from it.
Accomplishments
- TGT Manager at the Machine Intelligence Research Institute (MIRI).
- Previously a data scientist at Indeed and Samsung.
Papers & key writings
Links
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How Much Should We Spend to Reduce A.I.'s Existential Risk?
Stanford economist Charles I. Jones works out, in plain economic terms, how much money it would be worth spending to lower catastrophic risks from advanced AI — comparing it to the roughly 4 percent of GDP the U.S. effectively spent during Covid-19.
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Squiggle Maximizer (formerly "Paperclip Maximizer")
LessWrong wiki article explaining the canonical AI safety thought experiment: how an artificial general intelligence with an innocuous goal could pose an existential risk by pursuing it single-mindedly. Covers the orthogonality thesis and instrumental convergence.
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Superintelligence: The Idea That Eats Smart People
A skeptical 2016 talk by Maciej Ceglowski (Idle Words) that walks through the arguments for a superintelligence-driven intelligence explosion and takes them apart. Ceglowski compares the superintelligence risk debate to the Manhattan Project question of whether the first nuclear test could ignite the atmosphere, and argues that the core premises rest on speculative leaps rather than settled science. The talk was given at Web Camp Zagreb and is published as a full text transcript.
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Safe Superintelligence Inc.
Site of Safe Superintelligence Inc., the AI lab founded by Ilya Sutskever focused on building safe superintelligence.
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