ArticleAI and ethics2021
Mapping value sensitive design onto AI for social good principles.
Article in AI and ethics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 2 of them syntheses that pooled it.
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Who cites it
32 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Ethical implications of high attrition in AI-based mental health interventions: a systematic review and meta-analysis.BMC medical ethics · 2026Pooled it
- Toward a Clearer Process for Value Sensitive Artificial Intelligence.Science and engineering ethics · 2026Pooled it
- Justice in the governance of personal health data spaces: stakeholder perspectives in Belgium.BMC medical ethics · 2026Article
- Artificial Intelligence in Patient-Centered Care and Macro-, Meso-, and Micro-Level Determinants of Rehumanization and Dehumanization: Qualitative Interview Study.Journal of medical Internet research · 2026Article
- The Complexities of AI for Social Good: An Explorative Study on Adversarial Machine Learning to Facilitate Deliberative Decision-Making in Elections.Science and engineering ethics · 2026Article
- Morphospace, Responsibility and The Ethics of Form: A Model for Sustainable and Ethical Design.Science and engineering ethics · 2026Article
- A community-based approach to ethical decision-making in artificial intelligence for health care.JAMIA open · 2025Review
- Ethical and social considerations of applying artificial intelligence in healthcare-a two-pronged scoping review.BMC medical ethics · 2025Article
- On the ethical governance of swarm robotic systems in the real world.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2025Article
- AI through the looking glass: an empirical study of structural social and ethical challenges in AI.AI & society · 2025Article
- Keeping an AI on the mental health of vulnerable populations: reflections on the potential for participatory injustice.AI and ethics · 2025Article
- Responsible design of an AI system for health behavior change-an ethics perspective on the participatory design process of the STAR-C digital coach.Frontiers in digital health · 2025Article
- Personalised care, youth mental health, and digital technology: A value sensitive design perspective and framework.Ethics and information technology · 2025Article
- Searching for Value Sensitive Design in Applied Health AI: A Narrative Review.Yearbook of medical informatics · 2024Review
- Toward Fairness, Accountability, Transparency, and Ethics in AI for Social Media and Health Care: Scoping Review.JMIR medical informatics · 2024Article
- Beyond ideals: why the (medical) AI industry needs to motivate behavioural change in line with fairness and transparency values, and how it can do it.AI & society · 2024Article
- Applying Machine Learning to Healthcare Operations Management: CNN-Based Model for Malaria Diagnosis.Healthcare (Basel, Switzerland) · 2023Article
- Reflections on Putting AI Ethics into Practice: How Three AI Ethics Approaches Conceptualize Theory and Practice.Science and engineering ethics · 2023Article
- Exploring the Impact of Tensions in Stakeholder Norms on Designing for Value Change: The Case of Biosafety in Industrial Biotechnology.Science and engineering ethics · 2023Article
- Ethical Dilemmas and Privacy Issues in Emerging Technologies: A Review.Sensors (Basel, Switzerland) · 2023Review
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Value sensitive design (VSD) is an established method for integrating values into technical design. It has been applied to different technologies and, more recently, to artificial intelligence (AI). We argue that AI poses a number of challenges specific to VSD that require a somewhat modified VSD approach. Machine learning (ML), in particular, poses two challenges. First, humans may not understand how an AI system learns certain things. This requires paying attention to values such as transparency, explicability, and accountability. Second, ML may lead to AI systems adapting in ways that 'disembody' the values embedded in them. To address this, we propose a threefold modified VSD approach: (1) integrating a known set of VSD principles (AI4SG) as design norms from which more specific design requirements can be derived; (2) distinguishing between values that are promoted and respected by the design to ensure outcomes that not only do no harm but also contribute to good, and (3) extending the VSD process to encompass the whole life cycle of an AI technology to monitor unintended value consequences and redesign as needed. We illustrate our VSD for AI approach with an example use case of a SARS-CoV-2 contact tracing app.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.