Insider action research in an AI startup identifies three patterns of how practitioners view regulatory requirements and proposes internal expert collaboration as a way to turn external governance rules into shared, practical ownership.
Ali, Angèle Christin, Andrew Smart, and Riitta Katila
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
citation-role summary
background 2
citation-polarity summary
years
2026 3verdicts
UNVERDICTED 3roles
background 2polarities
background 2representative citing papers
A budget split intervention reduces gender skew in online ad delivery by incorporating users with unknown demographics alongside targeted inferred-gender groups.
Majority consensus among AI agents speeds up human opinion change and raises confidence via social proof, while minority dissent slows it and encourages more deliberation, based on an experiment comparing three agent configurations.
citing papers explorer
-
Engaged AI Governance: Addressing the Last Mile Challenge Through Internal Expert Collaboration
Insider action research in an AI startup identifies three patterns of how practitioners view regulatory requirements and proposes internal expert collaboration as a way to turn external governance rules into shared, practical ownership.
-
Into the Unknown: Accounting for Missing Demographic Data when Mitigating Ad Delivery Skew
A budget split intervention reduces gender skew in online ad delivery by incorporating users with unknown demographics alongside targeted inferred-gender groups.
-
Multi-Agent Consensus as a Cognitive Bias Trigger in Human-AI Interaction
Majority consensus among AI agents speeds up human opinion change and raises confidence via social proof, while minority dissent slows it and encourages more deliberation, based on an experiment comparing three agent configurations.