Abstract
Advances in neuroimaging and brain-machine interfacing (BMI) increasingly enable the large-scale collection and further processing of neural data as well as the modulation of neural processes. In parallel, progresses in artificial intelligence (AI), especially in machine learning, create new possibilities for decoding and analysing neural data for various purposes including health monitoring, screening for disease, cognitive enhancement, and device control. This contribution discusses some major ethical, technical, and regulatory issues associated with neural data analytics and delineates a roadmap for responsible innovation in this sector. Moreover, this paper review a variety of themes including mind reading, mental privacy, cybersecurity in commercial BMI, and issues of neurotechnology governance. Finally, a framework for responsible innovation and governance is presented.
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