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Designing Fiduciary Artificial Intelligence

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arxiv 2308.02435 v1 pith:MHBR6AG4 submitted 2023-07-27 cs.CY cs.AI

Sebastian Benthall , David Shekman This is my paper · ORCID
classification cs.CYcs.AI
keywords fiduciaryartificialdesignerdesigningintelligenceinterestsprincipalsprocedure
verification ladder T0 review T1 audit T2 compute T3 formal

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A fiduciary is a trusted agent that has the legal duty to act with loyalty and care towards a principal that employs them. When fiduciary organizations interact with users through a digital interface, or otherwise automate their operations with artificial intelligence, they will need to design these AI systems to be compliant with their duties. This article synthesizes recent work in computer science and law to develop a procedure for designing and auditing Fiduciary AI. The designer of a Fiduciary AI should understand the context of the system, identify its principals, and assess the best interests of those principals. Then the designer must be loyal with respect to those interests, and careful in an contextually appropriate way. We connect the steps in this procedure to dimensions of Trustworthy AI, such as privacy and alignment. Fiduciary AI is a promising means to address the incompleteness of data subject's consent when interacting with complex technical systems.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. The Agentic Web Requires New Normative Infrastructure

    cs.CY 2026-06 unverdicted novelty 6.0 of 10

    The web's anti-bot regime should be replaced by a framework that presumptively lets user-authorized AI agents act for their principals, requires platforms to disclose access policies, and permits agent blocking only w...

  2. From Turing to Tomorrow: The UK's Approach to AI Regulation

    cs.CY 2025-07 conditional novelty 2.0 of 10

    The UK should establish a flexible, principles-based regulator for frontier AI development, plus defensive measures against biological risks and updated legal frameworks for copyright, discrimination, and AI agents.

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