korrents

← People and their mental models

Yoshua Bengio's mental models

2 claims Yoshua Bengio made fit 2 mental models. Most often: Incentives, Margin of safety. Everything they said here.

Models we see in what they say

Our reading: their claim applies the idea without naming it. The claim is theirs; filing it here is ours.

Incentives

Look at what people are rewarded for; it explains more behaviour than what they say, your own included.

Used by 84 others

Competition between AI companies and countries is pushing accelerated AI development without sufficient caution, risking loss of control.

  1. Yoshua Bengio Deep-learning researcher and Turing Award laureate the risk of losing control is all too real, but competition between companies and countries incentivizes them to accelerate without sufficient caution. Introducing LawZeroyoshuabengio.org · 3 Jun 2025All korrents from this piece
    Their wordsthe risk of losing control is all too real, but competition between companies and countries incentivizes them to accelerate without sufficient caution.

    ↗Introducing LawZeroyoshuabengio.org

    3 Jun 2025

Margin of safety

Leave room for being wrong, because sometimes you will be.

Used by 25 others

Frontier AI systems cannot be presumed safe unless proven unsafe; developers must bear the burden of proof that risks stay within acceptable limits.

  1. Yoshua Bengio Deep-learning researcher and Turing Award laureate Despite evaluations, we cannot consider coming powerful frontier AI systems "safe unless proven unsafe". With current testing methodologies, issues can easily be missed. Additionally, it is unclear if governments can quickly build the immense expertise needed for reliable technical evaluations of AI capabilities and societal-scale risks. Given this, developers of frontier AI should carry the burden of proof to demonstrate that their plans keep risks within acceptable limits. Managing extreme AI risks amid rapid progress (with 24 co-authors)arxiv.org · 26 Oct 2023All korrents from this piece
    Their wordsDespite evaluations, we cannot consider coming powerful frontier AI systems "safe unless proven unsafe". With current testing methodologies, issues can easily be missed. Additionally, it is unclear if governments can quickly build the immense expertise needed for reliable technical evaluations of AI capabilities and societal-scale risks. Given this, developers of frontier AI should carry the burden of proof to demonstrate that their plans keep risks within acceptable limits.

    ↗Managing extreme AI risks amid rapid progress (with 24 co-authors)arxiv.org

    26 Oct 2023