A ChatGPT Plugin and DAO to Engage Marginalized Groups in AI


In this project, we set on developing a ChatGPT plugin that enables DAO (Decentralized Autonomous Organization) mechanisms to promote an ChatGPT-facilitated democratic decision process. This decentralized decision process will allow diverse marginalized populations, such as teenagers, people with disabilities, people of color, and people from the Global South, equal access to major decision makings and produce better decisions for communities and society at large.

High Level Questions

How far do you think personalization of AI assistants like ChatGPT to align with a user's tastes and preferences should go? What boundaries, if any, should exist in this process?

How to effectively engage vulnerable groups (e.g., teenegers, people with disabilities, people of color, and people from Global South) in making democratic decisions about AI?

We chose to focus on these questions mainly because they have direct, foreseeable impact on our target populations (i.e., teenagers, people with disabilities, people of color, and people from the Global South). We have worked closely with our target populations in past/ongoing research. We aim to include diverse voices in the decision-making process and ensure that AI rules are inclusive and equitable.

Our target populations are marginalized groups that could be disproportionally affected by these rules. Our broader goal is to inform AI developers, researchers and practitioners on how to navigate these thorny questions by considering inputs from these marginalized groups. Our expected results could also change how AI tools will be developed or at least configured so that our target marginalized groups will not be further marginalized because of AI


In our previous work, we conducted an empirical analysis of a diverse set of DAOs (100+) of various categories and smart contracts, leveraging onchain (e.g., voting results) and off-chain data (e.g., community discussions) as well as our interviews with practitioners. Specifically, we defined metrics to characterize key aspects of DAOs, such as the degrees of decentralization and autonomy for future DAO or related governance systems based on our findings. Building on the insights about DAO governance from our systematic analysis, we plan to develop mechanisms that can seamlessly integrate with AI (e.g.,ChatGPT) allowing users to actively participate in the democratic governance decision-making process. In particular, the DAO-like mechanisms will inform the development of AI system.


Yang Wang

Associate Professor at UIUC. Dr. Wang's interests focus on privacy and security, and public policy issues, especially regarding privacy. His current project involves Teaching High School Students about Cybersecurity and AI Ethics.

Yun Huang

Associate Professor at UIUC. Dr. Huang's interests include crowdsourcing systems, HCI, mobile applications and systems. One of her current project involves, advancing STEM Online Learning by Augmenting Accessibility and AI.

Tanusree Sharma

PhD Candidate at UIUC. She previously worked at Google, and Max Planck Institute on topic related Privacy/Security Risk Assessment Toolings. Her current work involves defining and evaluating decentralized governance metrics, in particularly in DAOs.

Dawn Song

Professor, Faculty co-Director of UC Berkeley Center on Responsible Decentralized Intelligence (RDI). Her work involves designing and developing new techniques and tools for Responsible AI.

Sunny Liu

Associate Director of the Stanford Social Media Lab. Her research involves designing and testing digital literacy interventions for older adults, adolescents, and rural residents.

Jeff Hancock

Harry and Norman Chandler Professor of Communication, founding director of the Stanford Social Media Lab, Stanford University. His work involves designing novel framework for AI-Mediated Communication.