AI Epistemic Risks: Emerging Mechanisms & Evidence
<p>Advances in artificial intelligence pose risks to humanity's collective capacity to form accurate beliefs, reason well, and maintain a healthy information en
AI Epistemic Risks: Emerging Mechanisms & Evidence
<p>Advances in artificial intelligence pose risks to humanity's collective capacity to form accurate beliefs, reason well, and maintain a healthy information en
AI False Claims Monitor
As the domain experts in data reliability in the topic of news and information, NewsGuard provides the leading red-teaming analysis for information reliability. AI models continue to face significant challenges in ensuring their models provide safe, accurate responses to prompts instead of spreading false claims on the internet or refusing to respond to topics in the news.
What It Now Takes to Establish a Fact
Hilke Schellmann & Mihir Kshirsagar from Princeton CITP on findings from a convening on information integrity, authentication and verification in the age of AI.
People are not friction
The Gell-Mann Amnesia Effect of AI is a pretty well documented phenomenon: The Gell-Mann amnesia effect is a cognitive bias describing the tendency of individuals to critically assess media reports in a domain they are knowledgeable about, yet continue to trust reporting in other areas despite recognizing similar potential inaccuracies.
FLF’s Epistemic Case Study Competition: Results — LessWrong
This summer, FLF ran a contest which asked entrants to help us “find the best workflows and methodologies for using AI to produce reliable, trustwort…
Epistemological Fault Lines Between Human and Artificial Intelligence
Large language models (LLMs) are widely described as artificial intelligence, yet their epistemic profile diverges sharply from human cognition. Here we show that the apparent alignment between...
We're not taking the fact-checking powers of AI seriously enough. It's past time to start.
Some notes on the Nobel Prize hallucination that wasn't
Reify This
The authors contend that contemporary efforts to render AI systems interpretable rest on a mistake: reification, the process of treating abstractions and statistical artifacts as if they were concrete realities.…
Mathematician catches AI-generated research error by OpenAI president | Benjamin Golub posted on the topic | LinkedIn
In case you think the problem of science slop is hypothetical, here's something that happened on X yesterday: The president of OpenAI sharing wrong science slop as proud evidence of the power of mathematical AI. Within a day, the mathematician Tony Feng found a gap that undercut the paper's central argument; the author conceded, and (to his credit!) Brockman deleted the tweet as soon as he became aware. Feng was a hero to catch this. The author of the refuted claim is a mathematician but a self-described outsider to this area, with a prior big claim posted and quickly withdrawn. Greg Brockman is not an expert, either. Neither could check what they were amplifying. Heroes catching errors one at a time won't hold against the volume of AI-generated research now coming. We need an automated, independent verification layer for knowledge work, which is what we're building at Refine (refine.ink). Passing such verification should become a necessary step before big claims, especially outside one's own expertise. A link to a bigger-picture post on this is in the comments. | 23 comments on LinkedIn
LinkedTrust — Deep Tech. Human Trust.
Verified trust systems, civic tech platforms, and AI-powered tools. Real projects, real impact.
Deepfakes, Elections, and Shrinking the Liar’s Dividend
Heightened public awareness of the power of generative AI could give politicians an incentive to lie about the authenticity of real content.
Trusting your own judgement on ‘AI’ is a huge risk
Writing at the end of the world, from Hveragerði, Iceland
Our AI Philosophy | Typefully
Social media runs on an implicit contract: I write something, you follow me, you read it, and you trust it came from a human mind. AI writing is curr…
Guest Post — AI Can Find the Article. Can It Tell Which Version It Used? - The Scholarly Kitchen
In this AI era, establishing trust and validating article versions with persistent identifiers (PIDs) is more important than ever.
Compare CIRIS: Verifiable Ethical AI vs the Alternatives, With Receipts
How CIRIS's signed, on-device, checkable ethical AI stacks up against the alternatives — the safety case, with receipts.
Collection
Updated 1mo
Knowledge systems: architecture, practice, persistence, strategy.