Tap a claim on the ring to put it at the centre.
← Identifying a harm in an AI system does not show that the system should not be deployed.
17 connected korrents · 17 moments from 10 Dec 2015 to 23 Sept 2026. Nearly all of them are about AI alignment .
Everything filed under LLMs
LLMs
Everything filed under neural networks
neural networks
Everything filed under education
education
Everything filed under open source
open source
Everything filed under AGI
AGI 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: Identifying a harm in an AI system does not show that the system should not be deployed. Identifying a harm in an AI system does not show that the system should not be deployed. Last stated 6 years ago
14 Dec 2020
AA
Amanda Askell — holds since 2020-12-14 — tap for who they are
Same subject: No company or country should be allowed to develop an AI system capable of causing large-scale harm. — tap to centre the map on it No company or country should be allowed to develop an AI system capable of causing large-scale harm. Last stated 3 weeks ago
23 Sept 2026
YB
Yoshua Bengio — holds since 2026-09-23 — tap for who they are
Same subject: AI should be deployed incrementally and in advance, because a system that does not yet exist is one almost nobody can imagine. — tap to centre the map on it AI should be deployed incrementally and in advance, because a system that does not yet exist is one almost nobody can imagine. Last stated 11 months ago
25 Nov 2025
IS
Ilya Sutskever — holds since 2025-11-25 — tap for who they are
Same subject: We do not control neural networks well enough to guarantee an AI will not harm humans, so we should be careful about what capabilities we give them. — tap to centre the map on it We do not control neural networks well enough to guarantee an AI will not harm humans, so we should be careful about what capabilities we give them. Last stated 4 years ago
17 Feb 2023
AR
Armin Ronacher — holds since 2023-02-17 — tap for who they are
Same subject: AI-developing companies cannot be trusted to protect the public from the dangers of their own systems — tap to centre the map on it AI-developing companies cannot be trusted to protect the public from the dangers of their own systems Last stated 3 weeks ago
17 Sept 2026
RS
Richard Stallman — holds since 2026-09-17 — tap for who they are
Same subject: Frontier AI systems cannot be presumed safe unless proven unsafe; developers must bear the burden of proof that risks stay within acceptable limits. — tap to centre the map on it Frontier AI systems cannot be presumed safe unless proven unsafe; developers must bear the burden of proof that risks stay within acceptable limits. Last stated 3 years ago
26 Oct 2023
YB
Yoshua Bengio — holds since 2023-10-26 — tap for who they are
Same subject: The AI safety community's fixation on a model escaping its box has pushed the other significant AI risks out of the discussion, with little progress to show for it. — tap to centre the map on it The AI safety community's fixation on a model escaping its box has pushed the other significant AI risks out of the discussion, with little progress to show for it. Last stated 3 years ago
18 Mar 2024
SA
Sam Altman — holds since 2024-03-18 — tap for who they are
Same subject: AI companies should not be the ones certifying their own safety and security practices — tap to centre the map on it AI companies should not be the ones certifying their own safety and security practices Last stated 9 months ago
15 Jan 2026
MB
Miles Brundage — holds since 2026-01-15 — tap for who they are
Same subject: The harmful behaviors of major AI companies -- training without consent, opaque code, no user control -- are choices, not unavoidable features of the technology. — tap to centre the map on it The harmful behaviors of major AI companies -- training without consent, opaque code, no user control -- are choices, not unavoidable features of the technology. Last stated 5 months ago
28 Apr 2026
AD
Anil Dash — holds since 2026-04-28 — tap for who they are
Same subject: A deep bidirectional model is strictly more powerful than a left-to-right model or a shallow concatenation of unidirectional models. — tap to centre the map on it A deep bidirectional model is strictly more powerful than a left-to-right model or a shallow concatenation of unidirectional models. Last stated 8 years ago
11 Oct 2018
KT
Kristina Toutanova — holds since 2018-10-11 — tap for who they are
MC
Ming-Wei Chang — holds since 2018-10-11 — tap for who they are
KL
Kenton Lee — holds since 2018-10-11 — tap for who they are
JD
Jacob Devlin — holds since 2018-10-11 — tap for who they are
Same subject: A layer should learn a residual with reference to its own input rather than an unreferenced function, which is what makes great depth trainable. — tap to centre the map on it A layer should learn a residual with reference to its own input rather than an unreferenced function, which is what makes great depth trainable. Last stated 11 years ago
10 Dec 2015
JS
Jian Sun — holds since 2015-12-10 — tap for who they are
KH
Kaiming He — holds since 2015-12-10 — tap for who they are
Same subject: A neural network's latent space is closer to an uncopyrightable syntax than to copyrightable expression. — tap to centre the map on it A neural network's latent space is closer to an uncopyrightable syntax than to copyrightable expression. Last stated a month ago
7 Sept 2026
KK
Kevin Kelly — holds since 2026-09-07 — tap for who they are
Same subject: A country outside the AI supply chain should just buy the index — which works only in the world where AI ends up commoditised rather than concentrated. — tap to centre the map on it A country outside the AI supply chain should just buy the index — which works only in the world where AI ends up commoditised rather than concentrated. Last stated 4 months ago
4 Jun 2026
AI
Alex Imas — holds since 2026-06-04 — tap for who they are
Same subject: A language model is no substitute for a well-specified conventional algorithm, so it cannot simply be dropped into a complex problem and trusted. — tap to centre the map on it A language model is no substitute for a well-specified conventional algorithm, so it cannot simply be dropped into a complex problem and trusted. Last stated a year ago
7 Jun 2025
GM
Gary Marcus — holds since 2025-06-07 — tap for who they are
Same subject: A model that could learn effectively from raw bitstrings or bytestrings would be extremely powerful, able to learn from any data modality — tap to centre the map on it A model that could learn effectively from raw bitstrings or bytestrings would be extremely powerful, able to learn from any data modality Last stated 3 years ago
10 Oct 2023
CH
Chip Huyen — holds since 2023-10-10 — tap for who they are
Same subject: A badly written AI outbound email is evidence of a bad vendor, not of a limit of AI. — tap to centre the map on it A badly written AI outbound email is evidence of a bad vendor, not of a limit of AI. Last stated 9 months ago
1 Jan 2026
JL
Jason Lemkin — holds since 2026-01-01 — tap for who they are
Same subject: A bigger context window does not give you a smarter model; the intelligence of the model is what decides how much of that window it can actually attend to. — tap to centre the map on it A bigger context window does not give you a smarter model; the intelligence of the model is what decides how much of that window it can actually attend to. Last stated 3 months ago
15 Jul 2026
DH
Dex Horthy — holds since 2026-07-15 — tap for who they are
Same subject: A body of publications is easy for AI models to consume via pretraining corpora but cumbersome for most humans due to CAPTCHAs, accounts, and paywalls. — tap to centre the map on it A body of publications is easy for AI models to consume via pretraining corpora but cumbersome for most humans due to CAPTCHAs, accounts, and paywalls. Last stated 3 weeks ago
17 Sept 2026
PC
Patrick Collison — holds since 2026-09-17 — tap for who they are
At the centre
Identifying a harm in an AI system does not show that the system should not be deployed.
Holds Read this korrent →
No company or country should be allowed to develop an AI system capable of causing large-scale harm.
Holds
AI should be deployed incrementally and in advance, because a system that does not yet exist is one almost nobody can imagine.
Holds
We do not control neural networks well enough to guarantee an AI will not harm humans, so we should be careful about what capabilities we give them.
Holds
AI-developing companies cannot be trusted to protect the public from the dangers of their own systems
Holds
Frontier AI systems cannot be presumed safe unless proven unsafe; developers must bear the burden of proof that risks stay within acceptable limits.
Holds
The AI safety community's fixation on a model escaping its box has pushed the other significant AI risks out of the discussion, with little progress to show for it.
Holds
AI companies should not be the ones certifying their own safety and security practices
Holds
The harmful behaviors of major AI companies -- training without consent, opaque code, no user control -- are choices, not unavoidable features of the technology.
Holds
A deep bidirectional model is strictly more powerful than a left-to-right model or a shallow concatenation of unidirectional models.
Holds
A layer should learn a residual with reference to its own input rather than an unreferenced function, which is what makes great depth trainable.
Holds
A neural network's latent space is closer to an uncopyrightable syntax than to copyrightable expression.
Holds
A country outside the AI supply chain should just buy the index — which works only in the world where AI ends up commoditised rather than concentrated.
Holds
A language model is no substitute for a well-specified conventional algorithm, so it cannot simply be dropped into a complex problem and trusted.
Holds
A model that could learn effectively from raw bitstrings or bytestrings would be extremely powerful, able to learn from any data modality
Holds
A badly written AI outbound email is evidence of a bad vendor, not of a limit of AI.
Holds
A bigger context window does not give you a smarter model; the intelligence of the model is what decides how much of that window it can actually attend to.
Holds
A body of publications is easy for AI models to consume via pretraining corpora but cumbersome for most humans due to CAPTCHAs, accounts, and paywalls.
Holds