Organizations for diversity, equity, inclusion, and belonging often emphasize participants from underrepresented populations, which in artificial intelligence includes but is not limited to women, LGBT persons, and persons of color (e.g., Black in AI, LatinX in AI). Meanwhile, many service and outreach workshops, such as those devoted to AI for Social Good at AAAI and the Grace Hopper Conference sessions on technology transfer to rural communities, provide opportunities for technologists to learn about the needs of underserved populations and to in turn give back to some of these communities. Many participants, including the organizers of this workshop, attended both of these kinds of workshops and expressed a wish to find a way to link these communities.

Recognizing intrinsic links between students from underserved populations such as isolated, underprivileged, and underrepresented communities and the frequent incidence among these students of intersectional identity and a desire to help their communities, the AAAI community is organizing this workshop on Artificial Intelligence Diversity, Belonging, Equity, and Inclusion: Mentoring Students from Underserved Populations. be held on Friday, February 7, 2020. It will consist of a three-hour workshop and panel session on the first day of the AAAI 2020 conference.

Short papers (2-4 page abstracts, position papers) and long papers (5-8 page surveys, studies, and articles on outreach and education praxis) are invited. For this workshop, we are interested both on best practices and challenges and opportunities for mentoring students from populations that in the past and present have been underserved.

This workshop shall include online follow-up activities such as planning out a call for service to underserved populations in the workshop participants’ communities and allow participants to share their service experiences. The primary objective is to discuss work at the nexus of inclusive AI education, education research pertinent to AI and underrepresented groups of students, and AI for Good as applicable to underserved students’ own communities, and to help share the word about extant efforts to serve such students. This would form the nucleus of an article and/or journal special issue about such efforts and their impact and outcomes to date.