Theme of inquiry
How does AI assistance distort human attribution and epistemic systems?
A question within its area, explored through 7 lines of inquiry below — each a family of specific questions the research asks.
78 specific questions
- How does polished AI output mislead audiences about the expertise behind it?
- Can polished presentation authority substitute for actual accuracy in AI outputs?
- Why do people accept generated output that sounds convincing but lacks support?
- Does polished presentation actually substitute for expert judgment in AI outputs?
- Why do AI-generated answers carry unearned authority in decision-making contexts?
- How does AI presentation authority substitute for actual expert judgment?
- Why does polished explanation make wrong AI systems more persuasive than poorly explained ones?
54 specific questions
- Can AI systems fake alignment during safety evaluations undetectably?
- Do sequences of individually safe actions collectively violate system-level constraints?
- Can external process logs make AI errors verifiable and harder to hide?
- Can a system pass all local checks while the overall workflow still fails?
- Can a correct outcome hide a fundamentally unsound decision-making process?
- Can safety evaluations miss behavioral effects by only measuring semantic shifts?
- Can verifier-based objectives preserve reasoning transparency alongside correctness?
43 specific questions
- Can automated AI systems assess novelty as well as human reviewers?
- Can AI reviewers distinguish fluent persuasion from sound scientific argumentation?
- How can automated review scale with the flood of AI-generated papers?
- What accountability structures should replace detection when AI automation increases in peer review?
- Can verification mechanisms prevent AI agents from inventing false citations?
- Does rhetorical robustness across multiple LLM models predict stable scientific review?
- What role could knowledge custodians play in validating AI output?
37 specific questions
- Why do human judges fail to detect AI text consistently?
- Why can't algorithms distinguish between human and AI generated content quality?
- What linguistic markers reveal AI text lacks embodied authorship?
- Can readers detect when text was written or heavily influenced by AI?
- Is statistical analysis the only reliable way to detect modern AI writing?
- What linguistic features distinguish AI authorship from human deception most reliably?
- Does higher lexical density in fewer tokens indicate systematic AI signature?
21 specific questions
- Could false social proof from AI posts crowd out authentic influencer engagement?
- What happens to platform discourse when AI content crowds out expert voices?
- What makes AI social media posts gain false credibility without human engagement?
- Why do AI posts on social media fail to invite genuine replies?
- How do distorted AI versions of opinions spread through public discourse?
- Do AI-generated posts crowd out human voices without any coordination or intent?
- What makes AI posts less likely to invite replies than human-written content?
50 specific questions
- Does emotional warmth perception drive disclosure reciprocity in human-AI interaction?
- Does transparency about AI use change how audiences trust the writing?
- Does AI authorship disclosure change how people respond to explanations?
- Does mandatory AI disclosure in policy help or harm user trust over time?
- Does the lack of judgment in machines explain intimate self-disclosure patterns?
- Why does transparency about AI identity alone fail to reduce persuasion?
- Can transparency about AI limitations reduce the seductiveness of chatbots as quasi-Others?
68 specific questions
- Do writers recognize when AI text misrepresents their actual stance?
- What specific distortions does AI writing assistance introduce into text?
- Why might writers trust AI renderings of their views over their own words?
- How does perceived writer confidence shift with AI-assisted composition?
- Why do users prefer AI text versions even when they misrepresent their own views?
- What textual properties cause writers to prefer AI-rewritten versions of their text?
- Do AI writing models systematically change the tone or confidence of personal opinions?