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Ethical Considerations in AI Development
16 references·0 citing·55 second hopsampled
Ethical Considerations in AI Development (2024)Ethical Considerations in AI DevelopmentEthical principles for artificial intelligence in education (2022)Ethical principles for artifi…A Unified Framework of Five Principles for AI in Society (2022)A Unified Framework of Five P…Human-centered artificial intelligence in education: Seeing the invisible through the visible (2021)Human-centered artificial int…Algorithmic bias: review, synthesis, and future research directions (2021)Algorithmic bias: review, syn…Algorithmic Bias in Education (2021)Algorithmic Bias in EducationAlgorithmic bias in data-driven innovation in the age of AI (2021)Algorithmic bias in data-driv…Addressing bias in big data and AI for health care: A call for open science (2021)Addressing bias in big data a…A Survey on Bias and Fairness in Machine Learning (2021)A Survey on Bias and Fairness…The Dark Sides of Artificial Intelligence: An Integrated AI Governance Framework for Public Administration (2020)The Dark Sides of Artificial …Statistical and machine learning models in credit scoring: A systematic literature survey (2020)Statistical and machine learn…Mitigating bias in algorithmic hiring (2020)Mitigating bias in algorithmi…Legal and human rights issues of AI: Gaps, challenges and vulnerabilities (2020)Legal and human rights issues…Co-Designing Checklists to Understand Organizational Challenges and Opportunities around Fairness in AI (2020)Co-Designing Checklists to Un…Closing the AI accountability gap (2020)Closing the AI accountability…Bias in data‐driven artificial intelligence systems—An introductory survey (2020)Bias in data‐driven artificia…From What to How: An Initial Review of Publicly Available AI Ethics Tools, Methods and Research to Translate Principles into Practices (2019)From What to How: An Initial …Fairness through awareness (2012)Semantics derived automatically from language corpora contain human-like biases (2017)Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification (2018)Connecting the dots in trustworthy Artificial Intelligence: From AI principles, ethics, and key requirements to responsible AI systems and regulation (2023)Fairness and Bias in Artificial Intelligence: A Brief Survey of Sources, Impacts, and Mitigation Strategies (2023)The structural transformation of the public sphere: an inquiry into a category of bourgeois society (1990)Cybernetics or Control and Communication in the Animal and the Machine (2019)The global landscape of AI ethics guidelines (2019)Education for AI, not AI for Education: The Role of Education and Ethics in National AI Policy Strategies (2021)Ethical framework for Artificial Intelligence and Digital technologies (2021)AI adoption and diffusion in public administration: A systematic literature review and future research agenda (2022)PRODUCT DEVELOPMENT: PAST RESEARCH, PRESENT FINDINGS, AND FUTURE DIRECTIONS (1995)How the machine ‘thinks’: Understanding opacity in machine learning algorithms (2016)Model Cards for Model Reporting (2019)Bridging the Gap Between Ethics and Practice (2020)Trustworthy AI: From Principles to Practices (2022)Trustworthy Artificial Intelligence: A Review (2022)CRITICAL QUESTIONS FOR BIG DATA (2012)A Framework of Potential Sources of Harm Throughout the Machine Learning Life Cycle (2021)Re-Thinking Data Strategy and Integration for Artificial Intelligence: Concepts, Opportunities, and Challenges (2023)Six Human-Centered Artificial Intelligence Grand Challenges (2023)Seeing without knowing: Limitations of the transparency ideal and its application to algorithmic accountability (2016)The Black Box Society: The Secret Algorithms That Control Money and Information (2016)The ethics of algorithms: Mapping the debate (2016)Digital Ageism: Challenges and Opportunities in Artificial Intelligence for Older Adults (2021)An Overview of Artificial Intelligence Ethics (2022)Your robot therapist is not your therapist: understanding the role of AI-powered mental health chatbots (2023)Attitude-behavior relations: A theoretical analysis and review of empirical research. (1977)The Measurement of Observer Agreement for Categorical Data (1977)Consumer Acceptance and Use of Information Technology: Extending the Unified Theory of Acceptance and Use of Technology1 (2012)Corporate Digital Responsibility in Service Firms and Their Ecosystems (2022)Thinking responsibly about responsible AI and ‘the dark side’ of AI (2022)Bias and Unfairness in Machine Learning Models: A Systematic Review on Datasets, Tools, Fairness Metrics, and Identification and Mitigation Methods (2023)The weirdest people in the world? (2010)WEIRD languages have misled us, too [Comment on Henrich et al.] (2010)Dissecting racial bias in an algorithm used to manage the health of populations (2019)Bias in artificial intelligence algorithms and recommendations for mitigation (2023)From human writing to artificial intelligence generated text: examining the prospects and potential threats of ChatGPT in academic writing (2023)The dark side of generative artificial intelligence: A critical analysis of controversies and risks of ChatGPT (2023)Mapping the Margins: Intersectionality, Identity Politics, and Violence against Women of Color (1991)The Ethics of Artificial Intelligence in Education (2022)Fairness, Accountability, Transparency, and Ethics (FATE) in Artificial Intelligence (AI) and higher education: A systematic review (2023)8 Decolonizing Methodologies: Research and Indigenous Peoples (2024)The impact of generative artificial intelligence on socioeconomic inequalities and policy making (2024)Toward an adequate taxonomy of personality attributes: Replicated factor structure in peer nomination personality ratings. (1963)Big Data's Disparate Impact (2014)Certifying and Removing Disparate Impact (2015)Discriminated by an algorithm: a systematic review of discrimination and fairness by algorithmic decision-making in the context of HR recruitment and HR development (2020)Fairness in Machine Learning: A Survey (2023)The "What" and "Why" of Goal Pursuits: Human Needs and the Self-Determination of Behavior (2000)Thematic analysis. (2012)Qualitative Research & Evaluation Methods: Integrating Theory and Practice (2014)A critical review of GenAI policies in higher education assessment: a call to reconsider the “originality” of students’ work (2024)Navigating the ethical terrain of AI in education: A systematic review on framing responsible human-centered AI practices (2024)Understanding students’ adoption of the ChatGPT chatbot in higher education: the role of anthropomorphism, trust, design novelty and institutional policy (2024)
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References

  • 2021A Survey on Bias and Fairness in Machine Learning5,798 cited
  • 2020Closing the AI accountability gap1,445 cited
  • 2022Ethical principles for artificial intelligence in education1,218 cited
  • 2020Bias in data‐driven artificial intelligence systems—An introductory survey1,040 cited
  • 2021Algorithmic Bias in Education988 cited
  • 2021Addressing bias in big data and AI for health care: A call for open science902 cited
  • 2019From What to How: An Initial Review of Publicly Available AI Ethics Tools, Methods and Research to Translate Principles into Practices879 cited
  • 2020Mitigating bias in algorithmic hiring830 cited
  • 2021Algorithmic bias: review, synthesis, and future research directions767 cited
  • 2020Legal and human rights issues of AI: Gaps, challenges and vulnerabilities493 cited
  • 2021Algorithmic bias in data-driven innovation in the age of AI438 cited
  • 2020Co-Designing Checklists to Understand Organizational Challenges and Opportunities around Fairness in AI435 cited
  • 2020Statistical and machine learning models in credit scoring: A systematic literature survey410 cited
  • 2020The Dark Sides of Artificial Intelligence: An Integrated AI Governance Framework for Public Administration396 cited
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A Unified Framework of Five Principles for AI in Society
379 cited
  • 2021Human-centered artificial intelligence in education: Seeing the invisible through the visible377 cited
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