mlsanityData to 7 Oct 2026

Human Perceptions on Moral Responsibility of AI: A Case Study in AI-Assisted Bail Decision-Making

arXiv 2102.00625 ↗First posted 1 Feb 2021cs.CY cs.AI cs.HCcited by 23

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Abstract (arXiv)

How to attribute responsibility for autonomous artificial intelligence (AI) systems' actions has been widely debated across the humanities and social science disciplines. This work presents two experiments (N=200 each) that measure people's perceptions of eight different notions of moral responsibility concerning AI and human agents in the context of bail decision-making. Using real-life adapted vignettes, our experiments show that AI agents are held causally responsible and blamed similarly to human agents for an identical task. However, there was a meaningful difference in how people perceived these agents' moral responsibility; human agents were ascribed to a higher degree of present-looking and forward-looking notions of responsibility than AI agents. We also found that people expect both AI and human decision-makers and advisors to justify their decisions regardless of their nature. We discuss policy and HCI implications of these findings, such as the need for explainable AI in high-stakes scenarios.

Key facts. Cited by 23 papers in the map (data through 7 Oct 2026). Builds on 15 of its 119 references that are in the map. First posted on arXiv 1 Feb 2021.

Builds on

15 of 119 references.

References · 15

  1. 2016The Mythos of Model Interpretabilitycited by 716
  2. 2018Explaining Explanations: An Overview of Interpretability of Machine Learningcited by 508
  3. 2017Fairness in Criminal Justice Risk Assessments: The State of the Artcited by 315
  4. 2019Principles alone cannot guarantee ethical AIcited by 134
  5. 2019Mathematical Notions vs. Human Perception of Fairness: A Descriptive Approach to Fairness for Machine Learningcited by 57
  6. 2018How Do Fairness Definitions Fare? Examining Public Attitudes Towards Algorithmic Definitions of Fairnesscited by 48
  7. 2015The social dilemma of autonomous vehiclescited by 47
  8. 2020Factors Influencing Perceived Fairness in Algorithmic Decision-Making: Algorithm Outcomes, Development Procedures, and Individual Differencescited by 41
  9. 2019Ask Not What AI Can Do, But What AI Should Do: Towards a Framework of Task Delegabilitycited by 36
  10. 2017Society-in-the-Loop: Programming the Algorithmic Social Contractcited by 35
  11. 2018Human Perceptions of Fairness in Algorithmic Decision Making: A Case Study of Criminal Risk Predictioncited by 35
  12. 2020Dimensions of Diversity in Human Perceptions of Algorithmic Fairnesscited by 13
3 more
  1. 2020Designing Fair AI for Managing Employees in Organizations: A Review, Critique, and Design Agendacited by 12
  2. 2017Demographics and discussion influence views on algorithmic fairnesscited by 4
  3. 2020Responsible AI and Its Stakeholderscited by 1

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Citing papers per year: 2021: 2; 2022: 2; 2023: 5; 2024: 4; 2025: 6; 2026: 4.

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  1. 2025Plan-Then-Execute: An Empirical Study of User Trust and Team Performance When Using LLM Agents As A Daily Assistantcited by 54
  2. 2024Position: Towards Bidirectional Human-AI Alignmentcited by 15
  3. 2024Perceptions of Sentient AI and Other Digital Minds: Evidence from the AI, Morality, and Sentience (AIMS) Surveycited by 15
  4. 2021On Blame Attribution for Accountable Multi-Agent Sequential Decision Makingcited by 13
  5. 2022The Conflict Between Explainable and Accountable Decision-Making Algorithmscited by 13
  6. 2021Software Engineering for Responsible AI: An Empirical Study and Operationalised Patternscited by 9
  7. 2022Towards a Roadmap on Software Engineering for Responsible AIcited by 9
  8. 2025Can AI Model the Complexities of Human Moral Decision-Making? A Qualitative Study of Kidney Allocation Decisionscited by 9
  9. 2023AI Reliance and Decision Quality: Fundamentals, Interdependence, and the Effects of Interventionscited by 8
  10. 2023A Critical Examination of the Ethics of AI-Mediated Peer Reviewcited by 8
  11. 2023A Systematic Literature Review of Human-Centered, Ethical, and Responsible AIcited by 5
  12. 2023Blaming Humans and Machines: What Shapes People's Reactions to Algorithmic Harmcited by 5
11 more
  1. 2024How Human-Centered Explainable AI Interface Are Designed and Evaluated: A Systematic Surveycited by 5
  2. 2024TwIPS: A Large Language Model Powered Texting Application to Simplify Conversational Nuances for Autistic Userscited by 5
  3. 2025Towards Uncertainty Aware Task Delegation and Human-AI Collaborative Decision-Makingcited by 4
  4. 2025Towards Cognitively-Faithful Decision-Making Models to Improve AI Alignmentcited by 2
  5. 2023Mindful Explanations: Prevalence and Impact of Mind Attribution in XAI Researchcited by 1
  6. 2025AI Ethics and Social Norms: Exploring ChatGPT's Capabilities From What to Howcited by 0
  7. 2025Does AI and Human Advice Mitigate Punishment for Selfish Behavior? An Experiment on AI ethics From a Psychological Perspectivecited by 0
  8. 2026Confronting Label Indeterminacy in Automated Bail Decisionscited by 0
  9. 2026RuleEdit: Failure-Guided Human-AI Model Editing with Prospective Impact Previewcited by 0
  10. 2026Why Sampling Is Not Choosing: Intentionality, Agency, and Moral Responsibility in Large Language Modelscited by 0
  11. 2026Method, Mind, and Morality: How People Make Sense of Artificial Intelligencecited by 0