492 citations
- University of OxfordGB138 papers
- University of CambridgeGB13 papers
- Centre National de la Recherche ScientifiqueFR11 papers
- Fermi National Accelerator LaboratoryUS9 papers
- Massachusetts Institute of TechnologyUS9 papers
- University of ManchesterGB9 papers
- Imperial College LondonGB7 papers
- Institute of High Energy PhysicsCN7 papers
- Ruhr University BochumDE7 papers
- The University of Texas at AustinUS7 papers
- Tsinghua UniversityCN7 papers
- University College LondonGB7 papers
4 papers · 2 filters
The Quiet Path from Seemingly Minor Design Errors to Workplace AI Incidents
Julia De Miguel Velázquez, Sanja Šćepanović, Andrés Gvirtz +1
Recent human-computer interaction (HCI) research has revealed a widespread misalignment between how developers design workplace artificial intelligence (AI) systems, and what worke…
When and How AI Should Assist Brainstorming for AI Impact Assessment
Jarod Govers, Sanja Šćepanović, Daniele Quercia
A key task in AI practice is to assess potential impacts to prevent harm. Current AI tools assisting AI impact assessment have not been designed or evaluated for collaborative team…
Learning from AVA: Early Lessons from a Curated and Trustworthy Generative AI for Policy and Development Research
Nimisha Karnatak, Mohamad Chatila, Daniel Alejandro Pinzón Hernández +3
General-purpose LLMs pose misinformation risks for development and policy experts, lacking epistemic humility for verifiable outputs. We present AVA (AI + Verified Analysis), a Gen…
To LLM, or Not to LLM: How Designers and Developers Navigate LLMs as Tools or Teammates
Varad Vishwarupe, Ivan Flechais, Nigel Shadbolt +1
Large language models (LLMs) are increasingly integrated into design and development workflows, yet decisions about their use are rarely binary or purely technical. We report findi…