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Whom to Trust, How and Why: Untangling Artificial Intelligence Ethics Principles, Trustworthiness, and Trust
11 references·2 citing·47 second hop
Whom to Trust, How and Why: Untangling Artificial Intelligence Ethics Principles, Trustworthiness, and Trust (2023)Whom to Trust, How and Why: Untangling Ar…Trust and trustworthiness in AI ethics (2022)Trust and trustworthiness in …Ethics in human–AI teaming: principles and perspectives (2022)Ethics in human–AI teaming: p…A Systematic Literature Review of User Trust in AI-Enabled Systems: An HCI Perspective (2022)A Systematic Literature Revie…Principled Artificial Intelligence: Mapping Consensus in Ethical and Rights-Based Approaches to Principles for AI (2020)Principled Artificial Intelli…A Survey on Ethical Principles of AI and Implementations (2020)A Survey on Ethical Principle…Principles alone cannot guarantee ethical AI (2019)Principles alone cannot guara…The fallacy of inscrutability (2018)The fallacy of inscrutabilityAI, agency and responsibility: the VW fraud case and beyond (2018)AI, agency and responsibility…Trust in a specific technology (2011)Trust in a specific technologyTrust in Automation: Designing for Appropriate Reliance (2004)Trust in Automation: Designin…An Integrative Model of Organizational Trust (1995)An Integrative Model of Organ…POTDAI: A Tool to Evaluate the Perceived Operational Trust Degree in Artificial Intelligence Systems (2024)POTDAI: A Tool to Evaluate th…From insight to innovation: Harnessing artificial intelligence for dynamic literature reviews (2024)From insight to innovation: H…Evaluating Structural Equation Models with Unobservable Variables and Measurement Error (1981)Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives (1999)Common method biases in behavioral research: A critical review of the literature and recommended remedies. (2003)Algorithmic bias: review, synthesis, and future research directions (2021)My Chatbot Companion - a Study of Human-Chatbot Relationships (2021)Trust in AI and Its Role in the Acceptance of AI Technologies (2022)Big Data's Disparate Impact (2014)The Black Box Society (2015)How the machine ‘thinks’: Understanding opacity in machine learning algorithms (2016)From What to How: An Initial Review of Publicly Available AI Ethics Tools, Methods and Research to Translate Principles into Practices (2021)Operationalising AI Governance through Ethics-Based Auditing: An Industry Case Study (2022)Technology, Megatrends and Work: Thoughts on the Future of Business Ethics (2022)Ethical Decision Making by Individuals in Organizations: An Issue-Contingent Model (1991)AI4People—An Ethical Framework for a Good AI Society: Opportunities, Risks, Principles, and Recommendations (2018)The global landscape of AI ethics guidelines (2019)Artificial Intelligence, Values, and Alignment (2020)The Ethics of AI Ethics: An Evaluation of Guidelines (2020)Ethics of AI-Enabled Recruiting and Selection: A Review and Research Agenda (2022)A Unified Framework of Five Principles for AI in Society (2019)Model Cards for Model Reporting (2019)AI ethics: from principles to practice (2022)An exploratory qualitative analysis of AI ethics guidelines (2022)Artificial intelligence in governance: recent trends, risks, challenges, innovative frameworks and future directions (2025)Epistemic Injustice (2007)Ethics, transparency, and explainability in generative ai decision-making systems: a comprehensive bibliometric study (2024)Evaluating Trustworthiness in AI: Risks, Metrics, and Applications Across Industries (2025)Standards, frameworks, and legislation for artificial intelligence (AI) transparency (2025)Complacency and Bias in Human Use of Automation: An Attentional Integration (2010)A Meta-Analysis of Factors Affecting Trust in Human-Robot Interaction (2011)Algorithm Aversion: People Erroneously Avoid Algorithms after Seeing Them Err (2014)Embedding AI in society: ethics, policy, governance, and impacts (2023)Revisiting the role of HR in the age of AI: bringing humans and machines closer together in the workplace (2024)Machine learning and artificial intelligence methods and applications for post-crisis supply chain resiliency and recovery (2025)An Integrative Model Of Organizational Trust (1995)Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement (2009)Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement (2010)ChatGPT: More Than a “Weapon of Mass Deception” Ethical Challenges and Responses from the Human-Centered Artificial Intelligence (HCAI) Perspective (2023)AI-teaming: Redefining collaboration in the digital era (2024)Unveiling trust in AI: the interplay of antecedents, consequences, and cultural dynamics (2025)Bridging the Gap Between Ethics and Practice (2020)Artificial intelligence, systemic risks, and sustainability (2021)Responsible artificial intelligence governance: A review and research framework (2025)Trust in Automation (2014)Human Trust in Artificial Intelligence: Review of Empirical Research (2020)Developing and Validating Trust Measures for e-Commerce: An Integrative Typology (2002)Trust in leadership: Meta-analytic findings and implications for research and practice. (2002)Trust and TAM in Online Shopping: An Integrated Model1 (2003)
this work references cited by second hop

References

  • 1995An Integrative Model of Organizational Trust10,705 cited
  • 2004Trust in Automation: Designing for Appropriate Reliance6,548 cited
  • 2019Principles alone cannot guarantee ethical AI1,869 cited
  • 2011Trust in a specific technology1,179 cited
  • 2020Principled Artificial Intelligence: Mapping Consensus in Ethical and Rights-Based Approaches to Principles for AI998 cited
  • 2022A Systematic Literature Review of User Trust in AI-Enabled Systems: An HCI Perspective386 cited
  • 2018The fallacy of inscrutability131 cited
  • 2022Trust and trustworthiness in AI ethics128 cited
  • 2020A Survey on Ethical Principles of AI and Implementations99 cited
  • 2022Ethics in human–AI teaming: principles and perspectives93 cited
  • 2018AI, agency and responsibility: the VW fraud case and beyond79 cited

Cited by

  • 2024From insight to innovation: Harnessing artificial intelligence for dynamic literature reviews21 cited
  • 2024POTDAI: A Tool to Evaluate the Perceived Operational Trust Degree in Artificial Intelligence Systems9 cited

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