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AI systems out-persuade expert humans

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AI systems out-persuade expert humans
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Computer Science > Computers and Society arXiv:2606.16475 (cs) [Submitted on 15 Jun 2026] Title:AI systems out-persuade expert humans Authors:Kobi Hackenburg, Caroline Wagner, Luke Hewitt, Ben M. Tappin, Ed Saunders, Hannah Rose Kirk, Helen Margetts, Christopher Summerfield View a PDF of the paper titled AI systems out-persuade expert humans, by Kobi Hackenburg and 7 other authors View PDF HTML (experimental) Abstract:Many societal decisions are settled by contests of persuasion. Conversational AI is a powerful new entrant in these contests, but whether it can out-persuade skilled and highly incentivized humans has remained unclear.

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arXiv.org
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Record

Original publisherarXiv.org
Canonical URLhttps://arxiv.org/abs/2606.16475
Publication timeWed, 29 Jul 2026 00:57:00 +0000
Retrieval time2026-07-29T01:16:12.774Z
Last seen2026-07-29T01:16:12.774Z
Headline sourcePublisher (no WeSearch rewrite)
Excerpt sourcepublisher body
Excerpt methodFirst ~120 words (~800 chars) of extracted publisher body, fair-use limited.
SummaryWeSearch · cerebras-chat (WeSearch summarizer)
Summary source textcontentText
Citation coverageSummary is a WeSearch-generated derivative; primary citation is the original publisher URL.
Cluster12ZOBUrLp27z · 1 stories
Cluster logicGrouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison.
Ranking reasonStory pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking.
Publisher visitYes — open original
Substitutes article?No — link-out required for full text

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Publisher-declared
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Machine-readable
No source-specific machine-readable restriction detected beyond the public feed.
WeSearch interpretation
WeSearch declared handling (basis: Derived from the published RSS/Atom feed). This is WeSearch policy, not a legal grant on the publisher's behalf.
Unknown
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WeSearch handling by dimension

Indexing May the item be indexed (stored, ranked, made findable)? Allowed
Snippet May a short excerpt of the publisher's text be shown? Allowed
AI summary May WeSearch generate its own short summary of the article? Limited
Retrieval / RAG May the content be exposed for third-party retrieval-augmented generation? Not asserted
Model training May the content be used to train AI models? Not asserted
Commercial reuse May the content be reused commercially? Not permitted

Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.

Opening excerpt (first ~120 words) tap to expand

Computer Science > Computers and Society arXiv:2606.16475 (cs) [Submitted on 15 Jun 2026] Title:AI systems out-persuade expert humans Authors:Kobi Hackenburg, Caroline Wagner, Luke Hewitt, Ben M. Tappin, Ed Saunders, Hannah Rose Kirk, Helen Margetts, Christopher Summerfield View a PDF of the paper titled AI systems out-persuade expert humans, by Kobi Hackenburg and 7 other authors View PDF HTML (experimental) Abstract:Many societal decisions are settled by contests of persuasion. Conversational AI is a powerful new entrant in these contests, but whether it can out-persuade skilled and highly incentivized humans has remained unclear.

Excerpt limited to ~120 words for fair-use compliance. The full article is at arXiv.org.

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