Good Afternoon Everyone,

This week's Change Seminar Speaker will be Chinasa T. Okolo. Chinasa's talk
is titled "Navigating the Limits of AI Explainability: Designing for Novice
Technology Users in Low-Resource Settings''.

*Abstract*
As researchers and technology companies rush to develop artificial
intelligence (AI) applications that aid the health of marginalized
communities, it is critical to consider the needs of the community health
workers (CHWs) who will be increasingly expected to operate tools that
incorporate these technologies. My previous work has shown that these users
have low levels of AI knowledge, form incorrect mental models about how AI
works, and at times, may trust algorithmic decisions more than their own.
This is concerning, given that AI applications targeting the work of CHWs
are already in active development and early deployments in low-resource
healthcare settings have already reported failures that created additional
workflow inefficiencies and inconvenienced patients.

Explainable AI (XAI) can help avoid such pitfalls, but nearly all prior
work has focused on users that live in relatively resource-rich settings
(e.g., the US and Europe) and that arguably have substantially more
experience with digital technologies such as AI. My research works to
develop XAI for people with low levels of formal education and technical
literacy, with a focus on healthcare in low-resource domains. This work
involves demoing interactive prototypes with CHWs to understand what
aspects of model decision-making need to be explained and how they can be
explained most effectively, with the goal of improving how current XAI
methods target novice technology users.


*Seminar Details*
*Location*: Tuesdays from 12-1pm in 271 CSE2 (The Bill and Melinda Gates
Center)

*Present Bio*
Chinasa T. Okolo is a fifth-year Ph.D. Candidate in the Department of
Computer Science at Cornell University. Before coming to Cornell, she
graduated from Pomona College with a degree in Computer Science. Her
research interests include explainable AI, human-AI interaction, global
health, and information & communication technologies for development
(ICTD). Within these fields, she works on projects to understand how
frontline healthcare workers in rural India perceive and value artificial
intelligence and examines how explainability can be best leveraged in
AI-enabled technologies deployed throughout the Global South.

Best,
UW Change Seminar Organizers
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