Neuroethics at the interface of machine learning and schizophrenia
Jacob McFarlane, Judy Illes
Abstract
Ethical discourse around machine learning analysis of free speech for the detection of schizophrenia has largely focused on consent and personal privacy. We focus here on additional ethics concerns and principles that must be addressed to move the pendulum of risk over to benefit and propose solutions to achieve that shift.
Topics & Concepts
NeuroethicsSchizophrenia (object-oriented programming)Focus (optics)Interface (matter)Computer scienceInformed consentHuman–computer interactionArtificial intelligenceEngineering ethicsPsychologyEngineeringPsychiatryMedicineAlternative medicineBubbleMaximum bubble pressure methodOpticsPhysicsPathologyParallel computingNeuroethics, Human Enhancement, Biomedical InnovationsHealthcare Decision-Making and RestraintsMental Health and Psychiatry