Oversight strategy in computer-use agents shapes exposure to problematic actions more reliably than correction success, with plan-based approaches reducing occurrences but not uniformly improving interventions.
Humans and automation: Use, misuse, disuse, abuse.Human Factors, 39(2): 230–253
8 Pith papers cite this work. Polarity classification is still indexing.
8
Pith papers citing it
citation-role summary
background 4
citation-polarity summary
years
2026 8roles
background 4representative citing papers
World models enable efficient AI planning but create risks from adversarial corruption, goal misgeneralization, and human bias, demonstrated via attacks that amplify errors and reduce rewards on models like RSSM and DreamerV3.
Among novice programmers using AI code generators, trust did not predict compliance with suggestions, while performance correlated with both compliance and increased subsequent trust.
Navigating AI-generated 3D environments from non-human traces supports reflection-in-action in more-than-human design, with designers oscillating between treating outputs as generative provocations and authoritative representations.
Imbalanced user-AI relationships form a distinct front-end ethical failure in healthcare AI that design choices such as restricted inputs and suppressed uncertainty can undermine agency and that reciprocity offers a path to more balanced interactions.
AI integration in newsrooms drives internal deferral of judgment to LLMs and external shifts of power to platforms, making fairness, accountability, and transparency harder to sustain unless participatory mechanisms redistribute authority.
A university course design enables non-technical students across majors to reach the Create level of Bloom's taxonomy by repeatedly applying a problem-data-model-evaluation-reflection pipeline with concurrent ethics training and hands-on studios.
citing papers explorer
-
Comparing Human Oversight Strategies for Computer-Use Agents
Oversight strategy in computer-use agents shapes exposure to problematic actions more reliably than correction success, with plan-based approaches reducing occurrences but not uniformly improving interventions.
-
Safety, Security, and Cognitive Risks in World Models
World models enable efficient AI planning but create risks from adversarial corruption, goal misgeneralization, and human bias, demonstrated via attacks that amplify errors and reduce rewards on models like RSSM and DreamerV3.
-
Relationships Between Trust, Compliance, and Performance for Novice Programmers Using AI Code Generation
Among novice programmers using AI code generators, trust did not predict compliance with suggestions, while performance correlated with both compliance and increased subsequent trust.
-
AI-Generated 3D Environments as Speculative Mediators in More-Than-Human Design: An Exploratory Study
Navigating AI-generated 3D environments from non-human traces supports reflection-in-action in more-than-human design, with designers oscillating between treating outputs as generative provocations and authoritative representations.
-
The Imbalanced User-AI Relationships as an Ethical Failure of Front-End Design in Healthcare AI
Imbalanced user-AI relationships form a distinct front-end ethical failure in healthcare AI that design choices such as restricted inputs and suppressed uncertainty can undermine agency and that reciprocity offers a path to more balanced interactions.
-
FAccT-Checked: A Narrative Review of Authority Reconfigurations and Retention in AI-Mediated Journalism
AI integration in newsrooms drives internal deferral of judgment to LLMs and external shifts of power to platforms, making fairness, accountability, and transparency harder to sustain unless participatory mechanisms redistribute authority.
-
From Understanding to Creation: A Prerequisite-Free AI Literacy Course with Technical Depth Across Majors
A university course design enables non-technical students across majors to reach the Create level of Bloom's taxonomy by repeatedly applying a problem-data-model-evaluation-reflection pipeline with concurrent ethics training and hands-on studios.
- Beyond Explainable AI (XAI): An Overdue Paradigm Shift and Post-XAI Research Directions