Treat neural data as risk-bearing data
Identify privacy risk controls for neural data across collection, use, sharing, retention, and deletion.
The principle: neural data becomes risky when context can be linked back to a person or used beyond the original promise. Identify the data path Map raw signal, derived features, labels, clinical notes, timing data, video, audio, device logs, and model artifacts. Privacy work starts by knowing what exists and where it moves. Govern the promise A consent form is not a data strategy. Decide who can approve reuse, what purposes are allowed, what counts as de-identification, and how exceptions are reviewed. Control, communicate, protect Limit access, set retention, document withdrawal, and communicate uses in plain language. For a BCI,…
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