Artificial Intelligence - Diversity, Belonging, Equity, and Inclusion (AIDBEI)

Description

This workshop is in the series and organized by Diverse In AI, an affinity group that aims to foster links between participants from underrepresented populations in the field of artificial intelligence. The organizers of this workshop strongly believe in bringing the diversity in our society, reflected in race, ethnicity, gender, age, religion, disability, sexual orientation, socioeconomic status and cultural background, into the field of AI (including autonomous agents and multiagent systems). Bringing this diversity in AI is extremely crucial as AI has and continues to shape our collective future, and therefore the representation of every aspect of society, especially the marginalized ones, is important to have an inclusive development of AI. Inspired by initiatives such as the Grace Hopper Conference which provides opportunities to technologists in understanding the needs of underserved populations, the organizers of this workshop also wish to bring together participants from underrepresented communities, help them via inter-disciplinary collaboration, dissemination of information regarding best practices in the field of AI and mentor students/future technologists from these communities.

Call for Participation

We invite original contributions that focus on best practices in AI research, education research pertinent to AI, challenges and opportunities for mentoring underserved populations, AI for Good and implications of AI on society. In keeping with the organizers' affiliations with WIML, Black in AI, LatinX in AI, and Queer in AI (whose early presence and development occurred at NeurIPS and ICML), technical areas emphasized will include machine learning with an emphasis on reinforcement learning, autonomous agents, multi-agent systems, and their relevant applications in the computer vision and natural language processing domains.

List of Topics

1. Demographic studies regarding AI applications and/or students' underserved populations
2. Reports of mentoring practice for AI students from underserved populations
3. Data science and analytics on surveys, assessments, demographics, and all other data regarding diversity and inclusion in AI
4. Survey work on potentially underserved populations, especially undergraduate students from such populations
5. Fielded systems incorporating AI and experimental results from underserved communities
6. Emerging technology and methodology for AI in underserved communities

Submission Guidelines

All papers must be original and not simultaneously submitted to another journal or conference. Submissions must follow the formatting guidelines for PMLR (one column style file). The following paper categories are welcome:

The following paper categories are welcome:

• Long papers (5 - 8 pages)
• Short papers and poster abstracts (2-4 pages)
• Contributed talks.

Invited Talks Contact Information

• Diversity Groups
  • Indigenous in AI
    • Current Contacts:
      • Michael Running Wolf   
      • Keoni Mahelona   
  • Black in AI
    • Current Contacts:
      • Sanmi Koyeji   
      • Gelyn Watkins  
  • Women in Machine Learning
    • Current Contacts:
      • Jessica Schrouff  
  • Queer in AI
    • Current Contacts:
      • William Agnew  
  • LatinX in AI
    • Current Contacts:
      • Omar Florez  
  • {Dis}Ability in AI
    • Current Contacts:
      • Maria Skoularidou  

Potential Permanent Organizing and Program Committee

• Organizing Committee
  • William Hsu  
• Program Committee
  • TBD

Publication

Workshop papers will be published in the Proceedings of Machine Learning Research (PMLR) alongside papers from AIDBEI at any AI conference that has been held. Submissions must follow the PMLR standards, and PDF versions should be submitted via EasyChair. Proceedings of the last AIDBEI Workshop can be viewed in this PMLR Issue.

Last updated by rotclanny on Apr 2, 2024