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← AI is expected to bring enormous benefits to economic science, even if…
17 connected korrents · 15 moments from 15 Jul 2021 to 12 Sept 2026.
Everything filed under AI and science
AI and science
Everything filed under AGI
AGI
Everything filed under AI and jobs
AI and jobs
Everything filed under mathematics
mathematics Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Read this korrent: AI is expected to bring enormous benefits to economic science, even if current practitioners cannot foresee most of them. AI is expected to bring enormous benefits to economic science, even if current practitioners cannot foresee most of them. Last stated 2 months ago
12 Sept 2026
TC
Tyler Cowen — holds since 2026-09-12 — tap for who they are
Same subject: Broad deployment of AI that can learn on the job will very likely produce rapid economic growth for some period of time. — tap to centre the map on it Broad deployment of AI that can learn on the job will very likely produce rapid economic growth for some period of time. Last stated 11 months ago
25 Nov 2025
IS
Ilya Sutskever — holds since 2025-11-25 — tap for who they are
Same subject: If AI can build the new theory that crystallises how to think about a subject, it would be surprising if that capability did not spill into the rest of the economy. — tap to centre the map on it If AI can build the new theory that crystallises how to think about a subject, it would be surprising if that capability did not spill into the rest of the economy. Last stated 4 months ago
30 Jun 2026
GS
Grant Sanderson — holds since 2026-06-30 — tap for who they are
Same subject: As AI advances, thinking philosophically about its implications will become a common job and pastime for large numbers of people. — tap to centre the map on it As AI advances, thinking philosophically about its implications will become a common job and pastime for large numbers of people. Last stated 2 months ago
24 Aug 2026
JC
Jack Clark — holds since 2026-08-24 — tap for who they are
Same subject: Economics cannot say what AI will do to work because the necessary data does not exist; what is needed is a Manhattan Project for data. — tap to centre the map on it Economics cannot say what AI will do to work because the necessary data does not exist; what is needed is a Manhattan Project for data. Last stated 5 months ago
4 Jun 2026
AI
Alex Imas — holds since 2026-06-04 — tap for who they are
Same subject: It would be disappointing and surprising if the next five years of AI progress in mathematics produced no economically valuable improvements traceable to it. — tap to centre the map on it It would be disappointing and surprising if the next five years of AI progress in mathematics produced no economically valuable improvements traceable to it. Last stated 4 months ago
30 Jun 2026
GS
Grant Sanderson — holds since 2026-06-30 — tap for who they are
Same subject: In an AI world growth and economic value come easily; distribution, wealth and political freedom are the hard parts, and that is where policy belongs. — tap to centre the map on it In an AI world growth and economic value come easily; distribution, wealth and political freedom are the hard parts, and that is where policy belongs. Last stated 8 months ago
13 Feb 2026
DA
Dario Amodei — holds since 2026-02-13 — tap for who they are
Same subject: AI will eliminate whole classes of jobs, but the wealth it creates will make policy responses affordable that were previously unthinkable. — tap to centre the map on it AI will eliminate whole classes of jobs, but the wealth it creates will make policy responses affordable that were previously unthinkable. Last stated a year ago
10 Jun 2025
SA
Sam Altman — holds since 2025-06-10 — tap for who they are
Same subject: The net effects of AI may be catastrophic. — tap to centre the map on it The net effects of AI may be catastrophic. Last stated 3 months ago
18 Jul 2026
JH
John Horgan — holds since 2026-07-18 — tap for who they are
Same subject: A compound's AI origin story is not by itself a reason to expect it to do better in the clinic. — tap to centre the map on it A compound's AI origin story is not by itself a reason to expect it to do better in the clinic. Last stated 2 years ago
13 May 2024
DL
Derek Lowe — holds since 2024-05-13 — tap for who they are
Same subject: A computational discovery platform does not make a biotech fast, because the thousand other steps of drug development are still the bottleneck. — tap to centre the map on it A computational discovery platform does not make a biotech fast, because the thousand other steps of drug development are still the bottleneck. Last stated 2 years ago
17 Sept 2024
AT
Alex Telford — holds since 2024-09-17 — tap for who they are
Same subject: A computational method can regularly predict protein structures with atomic accuracy even when no similar structure is known. — tap to centre the map on it A computational method can regularly predict protein structures with atomic accuracy even when no similar structure is known. Last stated 5 years ago
15 Jul 2021
DH
Demis Hassabis — holds since 2021-07-15 — tap for who they are
Same subject: Accurate computational approaches are needed to close the protein structural coverage gap and enable large-scale structural bioinformatics. — tap to centre the map on it Accurate computational approaches are needed to close the protein structural coverage gap and enable large-scale structural bioinformatics. Last stated 5 years ago
15 Jul 2021
DH
Demis Hassabis — holds since 2021-07-15 — tap for who they are
Same subject: AI models can be more accurate than physical experiments by averaging out noise, incorporating priors from large datasets, and interpolating between data points. — tap to centre the map on it AI models can be more accurate than physical experiments by averaging out noise, incorporating priors from large datasets, and interpolating between data points. Last stated 11 months ago
23 Nov 2025
EH
Elliot Hershberg — holds since 2025-11-23 — tap for who they are
Same subject: AI will not produce a big breakthrough in biological understanding any time soon, because biology has nothing like the clean, complete, high-quality data that made protein-structure prediction work. — tap to centre the map on it AI will not produce a big breakthrough in biological understanding any time soon, because biology has nothing like the clean, complete, high-quality data that made protein-structure prediction work. Last stated 2 years ago
19 Sept 2024
DL
Derek Lowe — holds since 2024-09-19 — tap for who they are
Same subject: As AI systems get better at scientific research tasks, it becomes more likely they will soon be capable of improving and building themselves. — tap to centre the map on it As AI systems get better at scientific research tasks, it becomes more likely they will soon be capable of improving and building themselves. Last stated 2 months ago
17 Aug 2026
JC
Jack Clark — holds since 2026-08-17 — tap for who they are
Same subject: Human parity on discovery benchmarks like DiG-bench will be reached by mid-2027, marking the point where recursive self-improvement in AI seriously kicks off. — tap to centre the map on it Human parity on discovery benchmarks like DiG-bench will be reached by mid-2027, marking the point where recursive self-improvement in AI seriously kicks off. Last stated 2 months ago
17 Aug 2026
JC
Jack Clark — holds since 2026-08-17 — tap for who they are
Same subject: Today's AI systems are significantly under-elicited for their ability to automate AI R&D. — tap to centre the map on it Today's AI systems are significantly under-elicited for their ability to automate AI R&D. Last stated 3 months ago
10 Aug 2026
JC
Jack Clark — holds since 2026-08-10 — tap for who they are
At the centre
AI is expected to bring enormous benefits to economic science, even if current practitioners cannot foresee most of them.
Holds Read this korrent →
Broad deployment of AI that can learn on the job will very likely produce rapid economic growth for some period of time.
Holds
If AI can build the new theory that crystallises how to think about a subject, it would be surprising if that capability did not spill into the rest of the economy.
Holds
As AI advances, thinking philosophically about its implications will become a common job and pastime for large numbers of people.
Holds
Economics cannot say what AI will do to work because the necessary data does not exist; what is needed is a Manhattan Project for data.
Holds
It would be disappointing and surprising if the next five years of AI progress in mathematics produced no economically valuable improvements traceable to it.
Holds
In an AI world growth and economic value come easily; distribution, wealth and political freedom are the hard parts, and that is where policy belongs.
Holds
AI will eliminate whole classes of jobs, but the wealth it creates will make policy responses affordable that were previously unthinkable.
Holds
The net effects of AI may be catastrophic.
Holds
A compound's AI origin story is not by itself a reason to expect it to do better in the clinic.
Holds
A computational discovery platform does not make a biotech fast, because the thousand other steps of drug development are still the bottleneck.
Holds
A computational method can regularly predict protein structures with atomic accuracy even when no similar structure is known.
Holds
Accurate computational approaches are needed to close the protein structural coverage gap and enable large-scale structural bioinformatics.
Holds
AI models can be more accurate than physical experiments by averaging out noise, incorporating priors from large datasets, and interpolating between data points.
Holds
AI will not produce a big breakthrough in biological understanding any time soon, because biology has nothing like the clean, complete, high-quality data that made protein-structure prediction work.
Holds
As AI systems get better at scientific research tasks, it becomes more likely they will soon be capable of improving and building themselves.
Holds
Human parity on discovery benchmarks like DiG-bench will be reached by mid-2027, marking the point where recursive self-improvement in AI seriously kicks off.
Holds
Today's AI systems are significantly under-elicited for their ability to automate AI R&D.
Holds