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AAAI 2022 Workshop on Diversity in Artificial Intelligence

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

Welcome to AIDBEI 2022!

The AAAI 2022 Workshop on Artificial Intelligence Diversity, Belonging, Equity, and Inclusion (AIDBEI) is a one-day virtual event at the International Conference of the Association for the Advancement of Artificial Intelligence. This workshop is the third in the series of workshops organized by Diverse In AI, an affinity group which aims to foster links between participants from underrepresented populations, which in artificial intelligence includes but is not limited to women, LGBTQ+ persons, and people of color. Diverse in AI was founded with the support and participation of our allies from Black in AI, WiML, LatinX in AI, Queer in AI, {Dis}Ability in AI, Indigenous in AI, and the Black in X Network.


Place: Virtual
Start Time: 7:30 AM Pacific Time (PT)
End Time: 1:30 PM Pacific Time (PT)
Date: Tuesday, March 1, 2022
PMLR proceedings from last year's workshop at AAAI 2021
Submission Deadline: Monday, February 21, 2022
Notification Due: Thursday, February 24, 2022
Preprint Due: Monday, February 28, 2022
Camera-Ready Copy Due for PMLR Proceedings: TBD

Call for Participation

This workshop is the third in the series of workshops organized by Diverse In AI, an affinity group which aims to foster links between participants from underrepresented populations, which in artificial intelligence includes but is not limited to women, LGBTQ+ persons, and people of color (e.g., Black in AI, WiML, LatinX in AI, Queer in AI). Meanwhile, many service and outreach workshops such as Grace Hopper Conference provide opportunities to technologists to understand the needs of underserved populations and in turn give back to these communities. The organizers of this workshop wish to bring together these communities to strive to achieve the intersecting goals through interdisciplinary collaborations. This shall help in the dissemination of benefits to all underserved communities in the field of AI and further help in mentoring students/future technologists belonging to isolated, underprivileged, and underrepresented communities.

We invite original contributions that focus on best practices, challenges and opportunities for mentoring from underserved populations, education research pertinent to AI, AI for Good as applicable to underserved students’ communities. 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 emphasis on natural language processing (NLP), computer vision (CV), and reinforcement learning (RL).

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 potential 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 should use the AAAI conference Author Kit.

The following paper categories are welcome:
  • Long papers (5 - 8 pages)
  • Short papers and poster abstracts (2-4 pages)
  • Contributed talks

Committees

Program Committee

  • Bethany Chamberlain, IT University of Copenhagen
  • Dr. Jessica Elmore, Council for Advancement and Support of Education (CASE)
  • Laverne Bitsie-Baldwin, Kansas State University
  • Dr. Shiri Dori-Hacohen, University of Connecticut
  • Veronika Cheplygina, IT University of Copenhagen
  • Yihong Theis, Kansas State University
  • Huichen Yang, Kansas State University

Organizing committee

  • Dr. William H. Hsu, Kansas State University
  • Huichen Yang, Kansas State University

Panelists

  • Hetvi Jethwani - Queer in AI, Indian institute of technology, Delhi, Indian
  • Maria Skoulidarou - Disability in AI, University of Cambridge, UK
  • Laura Montoya - LXAI, Accel AI Institute and LatinX in AI (LXAI)
  • Shawn Tsosie, Jeff Doctor - Indigenous in AI

Workshop Schedule

  • *All times are in PST (+3 EST, +8 UK, +9 CET)
  • 07:30 - 07:45 Workshop Opening
  • 07:45 - 08:45 Session 1
  • 07:45 - 08:15 Hello* - A Beginner's Guide to the Conference Galaxy - Bethany Chamberlain, Dovile Juodelyte and Veronika Cheplygina
  • 08:15 - 08:45 Responsible Research and Innovation for a Trustworthy AI: A Brief Report of Recent activities in Ethics and Gender - Francesca Alessandra Lisi
  • 08:45 - 09:15 Invited talk by Arjun Subramonian
    Arjun

    Title: Prioritizing Grassroots D&I Activism: Queer in AI

    Talk Abstract: I discuss how I got into the field of artificial intelligence (AI) and how feeling isolated as a queer, non-binary person of color and seeing harmful, queer-exclusionary AI around me motivated me to join the grassroots D&I organization Queer in AI. I overview what Queer in AI is, the mission of the organization, and the initiatives that Queer in AI runs, from community education and empowerment to policymaking and advocacy. Finally, I explain why Queer in AI is critical to making AI more queer-inclusive and envision a queer-inclusive machine learning pipeline. As an example of this, I discuss a recent project that would not have been possible without knowledge gained through Queer in AI: how English language technologies perpetuate harms such as misgendering and the cyclical erasure of non-binary gender identities, and related challenges that need to be acknowledged and addressed for language representations to equitably encode gender information.

  • 09:15 - 09:45 Invited talk by Maria Skoularidou
    Maria

    Title: On Equality, Diversity and Inclusivity in AI

  • 09:45 - 10:00 Break
  • 10:00 - 11:00 Panel Discussion on Mentoring: Higher Education, Industry, Allyship, Impact, and Resources
  • 11:00 - 11:30 Session 2
  • 11:00 - 11:30 Monitoring Diversity of AI Conferences: Lessons Learnt and Future Challenges in the DivinAI Project - Isabelle Hupont, Emilia Gómez, Songul Tolan, Lorenzo Porcaro and Ana Freire
  • 11:30 - 12:00 Invited talk by Laura Montoya and Jennafer Shae Roberts
    Laura Jennafer

    Title: Operationalizing Ethical AI
    Tal Abstract: Artificial Intelligence (AI) is quickly becoming prevalent in all aspects of life. As such, organizations that use, develop and deploy AI in their systems are now faced with ethical dilemmas as well as regulatory and legal risks they need to consider. This presentation will include a brief overview of the research being conducted at the Accel AI Institute and affiliated organizations including:
    - Ethical Frameworks for Technological Advancement
    - Universal and International Guidelines, Principles, and Declarations for AI
    - Case Studies of Applied Ethical AI Dilemmas
    - Reconciling Conflicts Between Ethics, Regulations, and Business Demands
    - Applying ethics at each stage of the AI development pipeline

  • 12:00 - 12:30 Affinity group introduction by Michael Running Wolf
    Michael

    Group name: Indigenous in AI

  • 13:00 - 13:15 Affinity group introduction by Timnit Gebru
    Timnit

    Group name: Distributed AI Research (DAIR) Institute

  • 12:30 - 1:30 Online social and call for mentoring program participants

Accepted Papers

  • Hello* - A Beginner's Guide to the Conference Galaxy - Bethany Chamberlain, Dovile Juodelyte and Veronika Cheplygina
  • Responsible Research and Innovation for a Trustworthy AI: A Brief Report of Recent activities in Ethics and Gender - Francesca Alessandra Lisi
  • Monitoring Diversity of AI Conferences: Lessons Learnt and Future Challenges in the DivinAI Project - Isabelle Hupont, Emilia Gómez, Songul Tolan, Lorenzo Porcaro and Ana Freire
  • Planning a Center for Standards and Ethics in Artificial Intelligence - Pablo Rivas, Jorge Ortiz, Daniel A. Diaz Pachon and Laura N. Montoya

Publication

Workshop papers will be published with the Proceedings of Machine Learning Research (PMLR). Submissions must follow the PMLR standards, and PDF versions should be submitted via EasyChair.

Contact Us

All questions about submissions should be emailed to huichen@ksu.edu and bhsu@ksu.edu.