Accountability
Who is answerable for an automated system's decisions and harms.
10 papers carry this themeView in grid →
In these papers
- 01It ’ s just distributed computing: Rethinking AI governanceIndia (TRAI · 2025A framework for rethinking AI governance.
- 02Designing Safe and Engaginf AI Experiences for Children - Towards the Definition of Best Practices in UIUX designGrazia Ragone, Paolo Buono, Rosa Lanzilotti · 2024Measuring safety, trustworthiness, and reliability for children.
- 03Educating Artificial Intelligence following the Child Learning Development Trajectories2024Notes lack of transparency and accountability in algorithms.
- 04Farsighted-Fostering Responsable AI awarness during AI application prototypingWang · 2024Fosters Responsible-AI awareness about potential harms during prototyping.
- 05Inevitable challenges of autonomy: ethical concerns in personalized algorithmic decision-makingWencheng Lu · 2024Raises ethical concerns of personalized algorithmic decisions.
- 06Unpacking Human-AI Interaction in Safety-Critical Industries: A Systematic Literature ReviewTita A.Bach · 2024Poor interaction can cause catastrophic consequences.
- 07Designing Responsible AI: Adaptations of UX Practice to Meet Responsible AI ChallengesQiaosi Wang∗ · 2023Responds to efforts to audit and regulate AI systems.
- 08UX designers pushing AI in the enterprise: a case for adaptive UIsJohn Zimmerman · 2020AUIs raise new ethical questions in the enterprise.
- 09Explanations as Mechanisms for Supporting Algorithmic TransparencyEmilee Rader · 2018Transparency to judge an algorithmic decision system's consequences.
- 10Understanding perception of algorithmic decisions: Fairness, trust, and emotion in response to algorithmic managementMin Kyung Lee · 2013Algorithms taking over decisions people used to make.