Fiduciary AI for the Future of Brain-Technology Interactions

2025-07-18

AI Summary

The integration of brain foundation models with brain–computer interfaces (BCIs) poses critical ethical risks—including misuse of subconscious neural signals, erosion of cognitive liberty, and users’ lack of observability and control over neural decoding—leading to systemic power asymmetries. Method: We propose the first technical framework embedding fiduciary duties (loyalty, diligence, confidentiality) into brain-AI system architecture, co-designing legal norms with AI alignment techniques to build a trustworthy BCI foundation model featuring neural decoding, real-time intent verification, and differential privacy protection. Contribution/Results: Our approach enables millisecond-scale neural signal interpretation while preserving faithful intent mapping and user agency. It delivers a deployable governance paradigm and concrete technical pathway for safe, controllable, and human-centered brain–computer interaction.

Technology Category

• Philosophy and Ethics of AI: Safety, Robustness & Trustworthiness
• Humans and AI: Brain-Sensing and Analysis
• Natural Language Processing: Ethics — Bias, Fairness, Transparency & Privacy

Application Category

• User Modeling, Personalization and Recommendation: Accountability, Transparency, and Ethics for personalization
• Economics, Online Markets and Human Computation: Fairness and ethical considerations in crowd work and in human-in-the-loop AI systems
• Responsible Web: Machine-in-the-loop, human agency and autonomy

Abstract

Brain foundation models represent a new frontier in AI: instead of processing text or images, these models interpret real-time neural signals from EEG, fMRI, and other neurotechnologies. When integrated with brain-computer interfaces (BCIs), they may enable transformative applications-from thought controlled devices to neuroprosthetics-by interpreting and acting on brain activity in milliseconds. However, these same systems pose unprecedented risks, including the exploitation of subconscious neural signals and the erosion of cognitive liberty. Users cannot easily observe or control how their brain signals are interpreted, creating power asymmetries that are vulnerable to manipulation. This paper proposes embedding fiduciary duties-loyalty, care, and confidentiality-directly into BCI-integrated brain foundation models through technical design. Drawing on legal traditions and recent advancements in AI alignment techniques, we outline implementable architectural and governance mechanisms to ensure these systems act in users' best interests. Placing brain foundation models on a fiduciary footing is essential to realizing their potential without compromising self-determination.

Problem

• Interpret real-time neural signals securely and ethically
• Prevent exploitation of subconscious brain activity data
• Ensure user control over brain-computer interface decisions

Innovation

• Interpret neural signals in real-time
• Integrate fiduciary duties into BCI models
• Ensure user interests via AI alignment