LMs systematically inflate expressed certainty during rewriting, affecting up to 75% of outputs with a 1.5-2x bias toward increasing rather than decreasing certainty, and the effect compounds over iterations.
The principles and limits of algorithm-in-the-loop decision making.Proceedings of the ACM on Human-Computer Interaction, 4(CSCW2):1–24
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Exploratory interview study with 17 developers identifies four forms of emergent oversight work for software agents and documents situated challenges and heuristics.
AI-authored goals produce higher SMART quality scores but lower psychological ownership, commitment, importance, and goal-directed behavior than self-authored goals, with ownership as the mediating mechanism.
The paper claims that alignment requires treating AI as part of the self through cognitive co-regulation, identifying risks like deskilling and automation bias while drawing on System 0 cognition theory.
MedMSA framework retrieves knowledge via language models then builds formal probabilistic models to produce uncertainty-weighted differential diagnoses from symptoms.
Recruiters perceive themselves as retaining agency over GenAI in hiring pipelines, yet GenAI invisibly architects core evaluation inputs, producing only marginal efficiency gains at the cost of deskilling.
An online experiment finds that showing users an overview of an AI's values reduces reliance on AI suggestions during writing tasks.
A literature review shows that constructs for appropriate reliance on AI are fragmented, presents three views on the topic, and calls for consensus on objective metrics to enable better comparisons across studies.
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Human oversight of agentic systems in practice: Examining the oversight work, challenges, and heuristics of developers using software agents
Exploratory interview study with 17 developers identifies four forms of emergent oversight work for software agents and documents situated challenges and heuristics.