Participatory AI & Community Engagement - Alex Tveit & Norman Valdez
5th July
In this meeting, key members of the Transformations Community invited speakers and other participants discussed AI’s role in addressing social-ecological challenges. The session, moderated by Bruce Goldstein (Transformations Community) and Nick Graham (Transformations Community), featured presentations from Alex Tveit (Sustainable Impact), Norman Valdez (Community Foundations of Canada), Jessica Parker (Moxie), and Kimberley Becker (Moxie), covering a wide range of topics from participatory AI to collaborative technology development.
Recording:
Slides:
Alex Tveit
Co-founder and CEO of Sustainable Impact Foundation also leads Tech and AI Stewardship at MaRS Discovery District. He leverages systems thinking and community-centric approaches to promote ethical tech innovation and social change.
Norman Valdez
Director of Technology and Design at CERIC enhances social impact through data-driven and community-focused tech strategies. As an Emerging Technology Fellow, he advocates for responsible AI use and explores leveraging emerging technologies for equitable outcomes.
Kimberly Becker
Ph.D., Co-Founder & COO, is an applied linguist specializing in disciplinary academic writing and English for research publication purposes.
Jessica L. Parker
Co-Founder & CEO is a health sciences educator and interdisciplinary researcher, who explores the potential of generative AI in revolutionizing research, teaching, and learning.
Invitations:
Join the Emerging Technology Fellowship: Get involved in shaping the future of AI and social impact. Learn more and join the Emerging Technology Fellowship.
Participate in Beta Testing: Test the new collaborative platform and provide feedback to help refine the technology. Contact us to get involved at Moxie Beta Testing.
Summary:
Topics:
AI Literacy Framework
Functional: Tools, prompting, limitations
Critical: Accuracy, bias, ethics
Rhetorical: Patterns, style, human-AI writing
Bias and "Weirdness"
Bias from training data (Western, educated)
Complexity of neural networks
Racial and gender bias examples
Environmental Impacts
Energy/resource consumption
Monitoring token usage, reducing waste
Sustainability through education
Collaborative Platforms
Community-based, discipline-specific platforms
AI integration with databases like Semantic Scholar
Addressing biases in academic databases