There’s a growing trend in Social, Behavioral, and Education Research (SBER)–machine learning–in which investigators often request to obtain, through direct interaction and intervention, various sets of data on human subjects, including their physiological (i.e., data obtained from either invasive or non-invasive means) and/or biometric data (e.g., audio/visual recordings). The research as originally conceived may or may not have been considered human subjects research, but its ultimate purpose is to teach machines how to think, draw conclusions, and process information in much the same way humans do. Read more