mlsanityData to 14 Oct 2026

Technology as uncharted territory: Contextual integrity and the notion of AI as new ethical ground

arXiv 2412.05130 ↗First posted 6 Dec 2024cs.AIcited by 0

Not on the map. Why?

Abstract (arXiv)

Recent research illustrates how AI can be developed and deployed in a manner detached from the concrete social context of application. By abstracting from the contexts of AI application, practitioners also disengage from the distinct normative structures that govern them. Building upon Helen Nissenbaum's framework of contextual integrity, I illustrate how disregard for contextual norms can threaten the integrity of a context with often decisive ethical implications. I argue that efforts to promote responsible and ethical AI can inadvertently contribute to and seemingly legitimize this disregard for established contextual norms. Echoing a persistent undercurrent in technology ethics of understanding emerging technologies as uncharted moral territory, certain approaches to AI ethics can promote a notion of AI as a novel and distinct realm for ethical deliberation, norm setting, and virtue cultivation. This narrative of AI as new ethical ground, however, can come at the expense of practitioners, policymakers and ethicists engaging with already established norms and virtues that were gradually cultivated to promote successful and responsible practice within concrete social contexts. In response, I question the current narrow prioritization in AI ethics of moral innovation over moral preservation. Engaging also with emerging foundation models, I advocate for a moderately conservative approach to the ethics of AI that prioritizes the responsible and considered integration of AI within established social contexts and their respective normative structures.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 14 of its 110 references that are in the map. First posted on arXiv 6 Dec 2024.

Builds on

14 of 110 references.

References · 14

  1. 2019Measurement and Fairnesscited by 308
  2. 2021The Values Encoded in Machine Learning Researchcited by 172
  3. 2019Principles alone cannot guarantee ethical AIcited by 135
  4. 2019The Ethics of AI Ethics -- An Evaluation of Guidelinescited by 129
  5. 2022Worldwide AI Ethics: a review of 200 guidelines and recommendations for AI governancecited by 28
  6. 2021A Sociotechnical View of Algorithmic Fairnesscited by 24
  7. 2024Deconstructing The Ethics of Large Language Models from Long-standing Issues to New-emerging Dilemmas: A Surveycited by 23
  8. 2021Trusted Artificial Intelligence: Towards Certification of Machine Learning Applicationscited by 13
  9. 2024The Responsible Foundation Model Development Cheatsheet: A Review of Tools & Resourcescited by 11
  10. 2020AI virtues -- The missing link in putting AI ethics into practicecited by 9
  11. 2024MoodCapture: Depression Detection Using In-the-Wild Smartphone Imagescited by 8
  12. 2021Toward a Theory of Justice for Artificial Intelligencecited by 7
2 more
  1. 2019Artificial Intelligence Governance and Ethics: Global Perspectivescited by 4
  2. 2024Catalog of General Ethical Requirements for AI Certificationcited by 1

Built on by

Not cited yet.