Meta’s and OpenAI’s new agents can streamline your life. Artificial intelligence researchers helped me test how far to trust them

AI Verifiers Trust Corrupted Rationales Over Evidence

Background: In clinical settings, clinicians’ context-specific trust in AI is associated with individual factors. This is particularly relevant in autism spectrum disorder (ASD) screening, where diagnostic criteria are complex, heterogeneous, and inherently uncertain. Although some AI systems demonstrate high sensitivity, clinicians are not always convinced of their utility. Therefore, examining potential biases in context-specific trust and achieving well-calibrated trust are critical. Objective: This study aimed to examine the individual factors associated with professionals’ context-specific trust in AI-assisted ASD screening systems. Methods: Fifty-five professionals involved in ASD assessment participated in the study. We used an AI-based ASD screening method based on a geometric shape-drawing task that assesses children’s motor function and has demonstrated high sensitivity for identifying children with ASD. Expert clinicians selected 2 ambiguous screening scenarios for evaluation. Participants made independent judgments while considering the AI output and rated their context-specific trust in each decision on a 7-point Likert scale. A linear mixed model (LMM) examined the associations between context-specific trust in AI decisions and participant characteristics while accounting for the nested data structure. Results: LMM analysis revealed significant between-participant variability in context-specific trust. Years of professional experience (=−2.20; =.03) and the length of education required to obtain professional credentials (=−2.67; =.01) were significantly and negatively associated with context-specific trust in AI-based screening. Dispositional trust in AI was significantly and positively associated with context-specific trust (=2.78; =.008). Confidence in participants’ own assessments was significantly and positively associated with context-specific trust (=5.67;

AI Systems That Admit Uncertainty Transform Enterprise Trust

AI is powerful… but can you trust it? 🤖 Dr. Sam and Silicon Valley leader Ramesh break down AI Trust, Bias & Governance in this must-watch Tech Chai episode. Trust. Verify. Govern. Watch video: https...

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Survey data covering 1,323 respondents shows 97% of Gen Z research restaurants before spending, while written reviews outrank influencer picks by 19 points.

A Cloaked survey of 1,009 U.S. adults finds just 18% trust AI to secure personal data. Meta AI users top the comfort rankings, ahead of Claude and Grok users.

Yelp and Morning Consult surveyed 2,202 U.S. adults and found only 15% trust AI search platforms "a lot," with 51% describing results as a "walled garden."

Yelp and Morning Consult surveyed 2,202 U.S. adults and found only 15% trust AI search platforms "a lot," with 51% describing results as a "walled garden."

Gracenote's 2026 study of 4,003 U.S. users finds AI chatbots gaining ground fast in TV content discovery, but 75% of all users still verify chatbot results.

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