Cognitive Digital Twins: Ethical Risks and Governance for AI Systems That Model the Mind
Read the original on arXiv Computation and Language →Cognitive Digital Twins (CDTs) are dynamic computational models that represent an individual’s cognition, continuously updated with behavioral, contextual, or physiological data to predict or simulate that person’s mental processes or act as a proxy for communication and decision‑making. The paper defines CDTs, distinguishes them from related systems, and introduces a 5A governance framework—authority, autonomy, access & control, accountability, and availability—to address their unique risks. It identifies specific threats such as misrepresentation, epistemic authority shifts, shadow twins, and proxy‑power asymmetries, and proposes governance requirements for high‑risk CDTs, including stronger consent, purpose limitation, validity, traceability, contestation, independent review, and model retirement.
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