Across the public and private sectors, organizations are rapidly exploring ways to reap the benefits of AI advancements in hopes of enhancing a range of complex domains, including child welfare, human trafficking detection, healthcare, and more. However, designing AI systems that truly bring value to impacted community members has proven to be an immense challenge. There is a growing recognition that decisions regarding AI system design should start with understanding domain-specific community needs, ethical concerns, and social challenges. Yet, translating these priorities to on-the-ground research and design practices brings forth new questions
What does it mean to design “community-driven AI”? What are common pitfalls to doing “community-driven AI” work, and how can our field move towards a more responsible, accessible, and reliable collective practice for “community-driven AI”?
This workshop will bring together a diverse group of researchers, practitioners, policymakers, and community stakeholders to explore these questions. By creating a space for interdisciplinary discussions, this workshop will foster the exchange of ideas, techniques, and best practices to address the challenges and opportunities that arise in community settings when AI and data-driven systems are employed.
We invite researchers, practitioners, policymakers, community partners, and other stakeholders with an interest in community-driven AI, to join us in this interactive virtual workshop. This one-day workshop aims to create a collaborative environment where participants can engage in interdisciplinary discussions, share their experiences, and contribute to the development of strategies and frameworks for harnessing the potential of AI in community settings.
Interested participants are asked to submit a brief statement of interest, demonstrating their alignment with the workshop goals. Submissions can take one of the following forms:
• A short bio with a statement of motivation/interest for attending the workshop.
• A 2-page position paper (includes figures; excludes references) discussing one or more of the workshop themes.
• A case study showcasing relevant work that contributes to the workshop themes.
We encourage submissions from individuals of diverse backgrounds, expertise, and experiences. Submissions should be in PDF format, following the ACM Primary Article Templates (single column). The submission should include author names (not anonymous submission). Each submission will undergo a peer review by two organizers, with acceptance based on the quality, relevance to the workshop themes, and the potential for meaningful contributions to the workshop discussions and goals.
How to Submit:
Please fill out this form.
Important Dates:
We will conduct two rounds of reviews to coordinate with the early registration deadline (September 8th) and other conference deadlines such as CHI (September 14th).
First round:
1. Submission deadline: September 1st, 2023
2. Notification of workshop acceptance: September 6th, 2023
Second round:
1. Submission deadline: September 22nd, 2023
2. Notification of workshop acceptance: September 29th, 2023
3. Workshop date (virtual): October 13th, 2023
Please contact organizers Ruyuan Wan at rwan@nd.edu, Karla Badillo-Urquiola at kbadill3@nd.edu.