( neuro - sighing - fits )

I recently attended a symposium held by Columbia University entitled, “ Brain Computer Interfaces: Innovation, Security, and Society ”, in which attendees were gathered to discuss the social implications of neurotechnology -- a growing genre of tech which reads from and writes to one’s nervous system. The purpose of neurotech ranges from clinical to entertainment applications, and much of it is available today, direct to consumer or client. The social implications vary according to the application. Frequent neuroethics discussions center around issues of agency or enhancement, but I see more immediate concerns in issues that are common to other data-centric technologies like facial recognition and fitness trackers: data misuse.  The symposium covered a wide spectrum of the state of neurotechnology, and speakers were a mix of neuroscientists, engineers, and bio / neuro / AI ethicists, from both academia and industry. The “Innovation” aspect of the symposium was covered well, with many o

With the fast-paced acceptance of AI technology into business and healthcare, the demand for personal physical data is greater than ever. Information about one’s health, emotions, and psychological states and traits is increasingly valued for constructing marketable digital profiles (Schmidt et al., 2019; Stark, 2018), and the ways these data are extracted is expanding beyond fitness trackers and facial recognition into perhaps the deepest intimate space: the brain. Brain-machine-interfaces (BMI) allow for direct translation of the brain’s electrical activity into signals which can indicate one’s perceptions and intentions. And as BMIs have become more mobile and accessible, there is a growing market for direct-to-consumer (DTC) neurotechnology devices, software applications, and online services. With that also comes growing concerns about how the data will be used. As of 2018, there were over 8000 active patents in neurotechnology, and a worldwide market of $8.4 billion, with products