John Lunsford

Bringing Infrastructure into Present and Future Considerations of AI Mistrust

The ride-for hire industry has been around for a long time. More than 800 years in fact. And some of its earliest iterations incorporated rudimentary algorithmic decision making into the activity of for-hire transit. Without discussions of fairness these systems went on to structure modern society’s unequal transportation environment, allowing fairness only to apply to those already in power. As we develop AI solutions to address problems of inequality in access, we have to consider how the promise of fairness is mediated by unfair systems that ai depends on to function. That interaction then becomes the foundation for trust- or mistrust - in AI’s deployment and ability to address problems of fairness in social, political, economic, & material systems. John will share ways to approach tracking, documenting, and building AI fairness practices into landscapes that were not always designed to accommodate them.

A User Experience Researcher in Safety, John earned his/their PhD in Communication from Cornell University in 2021, as well as an MS in Communication, an MA in Cultural anthropology, and BS in Political Science. A classical ethnographer by training, John has expanded an anthropological approach to encompass media studies, social physiology, political science, and urban design. It’s from that mixed vantage that John considers the effects on and of technology on social process and structures; documenting for his PhD the legacy of for hire transportations’ impact on the evolution of unequal access, its reflection of dominant societal priorities, and their impact on emerging rideshare and autonomous transportation systems. John’s current work in the realm of safety blends a passion for wicked problems with the demand of real-world complexities impacting the transportation landscape.

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