AI Alignment and Fiduciary Obligation

[2608.02660] AI Alignment and Fiduciary Obligation Skip to main content Search Submit Donate Log in Computer Science > Computers and Society arXiv:2608.02660 (cs) [Submitted on 1 Aug 2026 ( v1 ), last revised 12 Oct 2026 (this version, v3)] Title: AI Alignment and Fiduciary Obligation Authors: Benjamin Lange View PDF HTML (experimental) Abstract: Advanced AI assistants engage users in extended interactions across a widening range of roles, including advice, decision support, collaboration, learning, emotional support, and companionship among others. Current alignment efforts consider what alignment criteria should govern these relationships, drawing on moral traditions developed for human relationships such as bioethics, virtue ethics, care ethics, and relationship science. This paper considers AI alignment criteria in the user-AI-developer triad, since every user-AI interaction is mediated by a developer who exercises discretionary control over a system's behaviour, memory, and engagement parameters. Drawing on business ethics and legal scholarship, I argue that fiduciary theory applies to extended AI assistant deployment. On this basis, the four canonical fiduciary duties of loyalty, care, good faith, and candour can generate alignment criteria for the developer-user relationship. I map four user-side risks of extended AI assistant deployment to the four duties and specify institutional measures that follow from discharging each duty. The discussion complements existing approaches by grounding alignment criteria in obligations the developer owes the user, rather than in values the user-AI interaction should promote, and by showing that those obligations hold independently of any de facto harm to users. Comments: 10 pages, 1 table. Published in the Proceedings of the 9th AAAI/ACM Conference on AI, Ethics, and Society (AIES 2026) Subjects: Computers and Society (cs.CY) ; Artificial Intelligence (cs.AI); Human-Computer Interaction (cs.HC) Cite as: arXiv:2608.02660 [cs.CY] (or arXiv:2608.02660v3 [cs.CY] for this version) https://doi.org/10.48550/arXiv.2608.02660 Focus to learn more arXiv-issued DOI via DataCite Journal reference: Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 9(3), 1603-1615 (2026) Related DOI : https://doi.org/10.1609/aies.v9i3.43251 Focus to learn more DOI(s) linking to related resources Submission history From: Benjamin Lange [ view email ] [v1] Sat, 1 Aug 2026 14:18:36 UTC (38 KB) [v2] Sat, 22 Aug 2026 07:45:11 UTC (38 KB) [v3] Mon, 12 Oct 2026 05:57:29 UTC (38 KB) Full-text links: Access Paper: View PDF HTML (experimental) TeX Source view license Additional Features Audio Summary Current browse context: cs.CY < prev | next > new | recent | 2026-08 Change to browse by: cs cs.AI cs.HC References & Citations SciX Google Scholar Semantic Scholar export BibTeX citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer ( What is the Explorer? ) Connected Papers Toggle Connected Papers ( What is Connected Papers? ) Litmaps Toggle Litmaps ( What is Litmaps? ) scite.ai Toggle scite Smart Citations ( What are Smart Citations? ) Code, Data, Media Code, Data and Media Associated with this Article alphaXiv Toggle alphaXiv ( What is alphaXiv? ) Links to Code Toggle CatalyzeX Code Finder for Papers ( What is CatalyzeX? ) DagsHub Toggle DagsHub ( What is DagsHub? ) GotitPub Toggle Gotit.pub ( What is GotitPub? ) Huggingface Toggle Hugging Face ( What is Huggingface? ) ScienceCast Toggle ScienceCast ( What is ScienceCast? ) Demos Demos Replicate Toggle Replicate ( What is Replicate? ) Spaces Toggle Hugging Face Spaces ( What is Spaces? ) Spaces Toggle TXYZ.AI ( What is TXYZ.AI? ) Related Papers Recommenders and Search Tools Link to Influence Flower Influence Flower ( What are Influence Flowers? ) Core recommender toggle CORE Recommender ( What is CORE? ) Author Venue Institution Topic About arXivLabs arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs . Which authors of this paper are endorsers? | Disable MathJax ( What is MathJax? ) We gratefully acknowledge support from our major funders , member institutions , and all contributors. About · Help · Contact · Subscribe · Copyright · Privacy · Accessibility · Operational Status (opens in new tab) Major funding support from (opens in new tab) (opens in new tab) (opens in new tab)

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