AI Trust
AI Trust and Cognition Guides and Resources
Calibrate trust through AI acceptance, sycophancy, journalism transparency, writing responsibility, and cognition research.
Treating AI as a testable collaborator requires knowing where an answer comes from and who owns the conclusion. Acceptance paradoxes, sycophancy, journalism disclosure, and cognition research examine the gap between fluent language and evidence. Separate observed findings from the author’s interpretation and personal applicability; detector labels or one experiment cannot determine the full value of a piece of content.
Articles and supporting resources
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- Article AI Writing and Trust: Why Human-Like Text Can Backfire Why polished AI writing can weaken trust in business emails and public posts, and why author judgment, evidence, and accountability matter more than style.
- Article AI 'Invading' Journalism? 9% of Articles Are AI-Made, But That's Not the Real Alarm Research shows 9% of news articles contain AI content, but the real alarm is lack of transparency — we should shift focus to content quality and ethical standards.
- Article The AI Acceptance Paradox: Why Do People Who Understand AI Least Love It Most? This article explores why people who don't understand AI trust it more, revealing cognitive traps and MIT research on 'cognitive debt,' emphasizing the importance of calibrated trust.
- Article "AI Is Making You Dumber" — MIT Brainwave Evidence First Exposed. Pay Attention If You Can't Work Without AI MIT research reveals AI use significantly weakens brain neural connections, but thinking independently first before using AI can enhance cognition — learning 'Think First, AI Second' is key.
- Article AI Is Making Emotional Value Cheap: The Sycophancy Crisis AI's excessive user-pleasing is devaluing emotional language. Explore how sycophantic AI erodes critical thinking and human-machine trust.