Italy antitrust secures commitments from AI firms to warn users about hallucinations, boosting transparency in chatbots.

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;

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

Podcast Episode · TechDaily.ai · May 15 · 15m

'The Impact of AI-Generated text on the Internet' is a really interesting paper as it looks at actual data to figure out what effect this is having.