Neural Data and Neurotechnology

When a claim turns on what an EEG headset, an AI interview tool, or a workplace monitoring system says it can read from a person, the question is whether the signal can bear that inference: how it was collected, cleaned, and validated, and whether its accuracy holds outside the lab. Dr. Sawyer has worked on EEG and physiological measurement since 2014, including first-author work on detecting errors in single-electrode EEG.

The cases include privacy claims over consumer EEG headsets and earbuds, AI hiring and monitoring tools that claim to infer emotion or honesty, and disputes over what a device can actually measure. California, Colorado, Connecticut, and Montana already protect neural or neurotechnology data; Delaware and Vermont have enacted protections that take effect in 2027 and 2028; California will bar employers from using AI workplace tools that collect neural data or infer emotional state from 2027; and the EU AI Act bans emotion recognition at work and in schools except for medical or safety reasons. He addresses measurement, not medicine, and does not offer opinions on brain injury, clinical diagnosis, or implanted devices.

His first-author work tests what a single EEG electrode can detect when a person makes an error, and compares methods for cleaning EEG data, the steps that shape what a recording appears to show. He has also published on-road research measuring driver attention through electrodermal activity, a neurophysiological study of anger and risky driving decisions, and a paper on brain signals as intelligence others can collect. He founded and directed UCF’s Laboratory for Autonomy-Brain Exchange, was a Repperger Fellow with the Air Force’s 711th Human Performance Wing, and serves as a Review Editor for Neural Technology at Frontiers in Neuroscience. The methods are EEG, event-related potentials, and electrodermal and eye-movement measurement.