Bio

Connie W. Chau is a PhD Candidate in Technology & Social Behavior (a joint program in Computer Science and Communication) at Northwestern University and advised by Maia Jacobs. Connie’s research utilizes participatory and community-based methods to co-create technologies, especially those that improve support for frontline care work, and promote positive individual and public health outcomes.

She also explores digital safety, tech literacy, and tech-facilitated abuse in her on-the-ground role as a Technology Consultant for The Network, providing trainings and leading initiatives to build Illinois’ capacity to increase safety, trauma-informed care, and structural support within local communities. Website: https://www.conniewchau.me/

Co-Creating Technologies With and For AI-Skeptical Communities

Despite rapid advancements in AI, its benefits are unevenly distributed, and many populations remain excluded from shaping, understanding, or trusting these technologies. Thus, I explore and contribute community-based, participatory approaches to advancing the development, evaluation, and safety of AI technologies, particularly among non-technical, AI-skeptical communities. My work centers on understanding and addressing AI skepticism, literacy, and safety through longitudinal co-creation and real-world deployment of AI interventions that reflect peoples’ values and needs.

In particular, I focus on frontline workers (FLWs) who provide care and services to survivors of domestic violence (DV) and established an ongoing community-based participatory research (CBPR) partnership with The Network: Advocating Against Domestic Violence–a Chicago-based nonprofit that operates the Illinois State Domestic Violence Hotline and supports more than 40 organizations statewide that serve DV survivors. Not only are FLWs in DV at the forefront of responding to the real-world harms of generative AI technologies on survivors, they hold critical expertise in healthy interpersonal relationship dynamics, power and control, and trauma-informed care which are relevant to many tools for human-AI interaction.

Through this community-first approach, my work identified new opportunities for AI, specifically towards the co-development and real-world deployment of a novel predictive and adaptive AI-powered intervention to address secondary traumatic stress (STS), an occupational hazard prevalent in FLWs across diverse health and care work contexts. My research will contribute guidelines for measuring safety, transparency, and literacy in non-technical communities and how conscientiously centering AI-skeptical groups into design and evaluation can lead to safer, more equitable, and impactful AI technologies for all.