19 citations
- University of OxfordGB13 papers
- Politecnico di TorinoIT3 papers
- Rutherford Appleton LaboratoryGB3 papers
- University of CambridgeGB3 papers
- Daresbury LaboratoryGB2 papers
- Deutsches Elektronen-Synchrotron DESYDE2 papers
- ETH ZurichCH2 papers
- European Organization for Nuclear ResearchCH2 papers
- Imperial College LondonGB2 papers
- Manchester UniversityUS2 papers
- Technion – Israel Institute of TechnologyIL2 papers
- The University of MelbourneAU2 papers
4 papers · 1 filter
The Quiet Path from Seemingly Minor Design Errors to Workplace AI Incidents
Julia De Miguel Velázquez, Sanja Å ÄepanoviÄ, 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 Å ÄepanoviÄ, 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…