Core to DTAIS fellowship, the Trustworthy AI seminar series explores socio-technical issues in AI/ML learning and decision-systems and their interaction in the context of trust and trustworthiness. Format mixes “advanced intro” lectures, external speakers, and student-led sessions on contemporary issues in TAI.

• This is a PhD seminar class, with priority given to the students required to take the course. However, the first hour is open to GW TAI community members who wish to listen via Zoom, while the second hour of in-person participation in the follow-on discussions is available to PhD students and postdocs who want to commit to the sequence. Please reach out to gwtai@gwu.edu to express interest in this mode of participation. 
• The final seminar guest lecturer of the semester will be on the Monday, December 1st session, where  Dr. Ali Rahnavard, of GW's Milken Institute School of Public Health, will be presenting a lecture entitled "Compact Genomic Language Models to Decode Sequencing Data."