Implicit bias (IB) negatively impacts the medical care and health outcomes of Black patients. Physician IB compromises the quality of patient-physician communication, eroding trust and confidence, impairing treatment decisions and adherence, and causing patient harm. Studies show that non-Black physicians, on average, have moderate levels of IB toward Black patients. Since most Black patients see non-Black physicians, this means that most Black patients see physicians with IB towards them. The main way in which IB is communicated and reinforced is via paraverbal behaviors (i.e., how people deliver speech, such as tone, pitch, volume) and non- verbal behaviors (i.e., how people use their body, such as eye gaze, hand gestures, and body leaning), as opposed to verbal behaviors (i.e., what people say) during interactions. Current IB training is ineffective because they rely on relatively brief interventions that seek only to in- crease physicians’ awareness about their having IB. While this is a necessary first step, by itself it is insufficient. IB training must also show learners the behaviors they unwittingly display due to their IB, and teach them concrete remediation strategies. MCI’s work under this grant will produce the first-ever effective IB training system. MPathic- IBCH is a new AI-based technology that will enhance two-way communication using adaptable virtual human (VH) interactions, and present detailed, actionable, personalized feedback on learners’ unwitting display of negative nonverbal and paraverbal behaviors. To recognize se- lected facial expressions associated with learner IB, MCI will implement a proprietary system based on the Emotion Facial Action Coding System (EMFACS) which analyzes combinations of facial action units for real-time emotional state analysis. We will further enhance the responsive- ness of VHs with an EMFACS-based facial rigging design that parallels the detection design. This SBIR FastTrack will accomplish this by: (Ph1-1) Identifying key paraverbal and nonver- bal communication behaviors systematically associated with pro-White/anti-Black IB. (PH1-2) Developing and evaluating an MPathic-IBCH prototype to capture a key communication behav- ior identified in prior research and to differentiate medical students based on their race IB levels; (Ph2-1) Developing and integrating MPathic-IBCH into a blended IB/Cultural Humility curricu- lum; (Ph2-2) Building MPathic-IBCH into a fully-featured, web-deployable application with im- proved nonverbal and speech prosody detection, AI, 3 full scenarios, and integrating it into a learning environment; and, (Ph2-3) Deploying blended curriculum with MPathic-IBCH and evalu- ating the effects on student learning, communication behaviors, and attitudes as measured by SP performance ratings, scores within MPathic-IBCH, and self-reflections and experiences.