PrivacyAkinator uses LLM-generated questions grounded in data-flow representations and a news-mined design space to help developers surface privacy decisions, yielding 47% more decisions identified in 73% less time than PRAM in a 24-person study.
You Always Get an Answer
7 Pith papers cite this work, alongside 69 external citations. Polarity classification is still indexing.
7
Pith papers citing it
69
external citations · OpenAlex
citation-role summary
background 3
method 1
citation-polarity summary
years
2026 7representative citing papers
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.
Chaplains view AI chatbots as unable to provide attuned pastoral care for non-clinical emotional needs, based on themes of listening, connecting, carrying, and wanting.
The paper introduces six design principles for embedding incidental learning into AI-assisted software development and presents SHIELD, a multi-agent system that surfaces contextual learning moments from AI coding agents' reasoning traces.
An experiment found LLM counterarguments improved group flexibility and satisfaction while AI mediation boosted minority participation but lowered psychological safety.
A collaborative VR workflow with GenAI lets users merge prompts and creatively repurpose outputs to co-create 3D artifacts that narrate shared cultural heritage experiences.
A within-participants study with design students found that sketch inputs to an AI ideation tool increased fluency but students still preferred text prompts, pointing to design choices that could better preserve reflective practice.
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.