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The methodology of studying fairness perceptions in Artificial Intelligence: Contrasting CHI and FAccT

  • Published:2023-02 Issue: Volume:170 Page:102954
  • ISSN:1071-5819
  • Container-title:International Journal of Human-Computer Studies
  • language:en
  • Short-container-title:International Journal of Human-Computer Studies

Author:

van Berkel NielsORCID,Sarsenbayeva Zhanna,Goncalves Jorge

Funder

Carlsbergfondet

Publisher

Elsevier BV

Subject

Hardware and Architecture,Human-Computer Interaction,General Engineering,Education,Human Factors and Ergonomics,Software

Reference288 articles.

1. Trends and trajectories for explainable, accountable and intelligible systems: An HCI research agenda;Abdul,2018

2. Artificial Knowing: Gender and the Thinking Machine;Adam,1998

3. Peer-to-peer in the workplace: A view from the road;Ahmed,2016

4. The value of crowdsourcing in public policymaking: epistemic, democratic and economic value;Aitamurto;Theory Pract. Legis.,2017

5. Exploring bystanders’ privacy concerns with smart homes in Jordan;Albayaydh,2022

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1. A systematic review of trustworthy artificial intelligence applications in natural disasters;Computers and Electrical Engineering;2024-09

2. Beyond Individual Accountability: (Re-)Asserting Democratic Control of AI;The 2024 ACM Conference on Fairness, Accountability, and Transparency;2024-06-03

3. Who Made That Decision and Why? Users’ Perceptions of Human Versus AI Decision-Making and the Power of Explainable-AI;International Journal of Human–Computer Interaction;2024-05-20

4. A Scoping Study of Evaluation Practices for Responsible AI Tools: Steps Towards Effectiveness Evaluations;Proceedings of the CHI Conference on Human Factors in Computing Systems;2024-05-11

5. I lose vs. I earn: Consumer perceived price fairness toward algorithmic (vs. human) price discrimination;Proceedings of the CHI Conference on Human Factors in Computing Systems;2024-05-11
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