Consent-Preserving Computation

Technical mechanisms that keep the use of neural data bound to what the user actually authorized, rather than relying only on policy and trust. These include fine-grained, purpose-limited permissions for BCI applications (which stimuli an app may present, which features it may read), verifiable and revocable consent, cryptographic access control with audit logs, and data-provenance tracking so downstream use can be checked against the original grant.

The problem is sharpened by adaptive and self-updating devices whose behavior — and therefore the data they need — changes after consent was given, and by involuntary signals a user cannot choose not to emit. Proposals include a trusted BCI mediator or anonymizer that enforces app permissions and filters incidental leakage, dynamic or staged consent for evolving devices, and machine-checkable usage policies. Most of this is still design and prototype work, and it dovetails with the legal neurorights agenda rather than substituting for it.