Hello! I'm Alicia DeVrio.

My research investigates how AI systems perpetuate structural harm and advances approaches that aim to restore autonomy and control to the people most impacted by these technologies. In January 2027, I will start as a tenure-track assistant professor of digital media at Georgia Tech. I am recruiting a PhD student to start fall 2027.

I recently defended my PhD on understanding & supporting bottom-up resistance to harmful AI systems at Carnegie Mellon University’s Human-Computer Interaction Institute, advised by Ken Holstein. Previously, I also conducted research at Microsoft Research Montreal’s fairness, accountability, transparency, and ethics (FATE) team with Su Lin Blodgett and Alexandra Olteanu, where I explored impacts of and interventions for anthropomorphic AI design. My work has been published in top-tier computing venues including CHI, CSCW, FAccT, and ACL.

Before graduate school, I worked as a growth product manager at Noom and led digital product experimentation efforts for the Wall Street Journal and Barron’s at Dow Jones. I graduated from Brown University with an undergraduate degree in computer science and grew up in the Appalachian Mountains of Northeast Tennessee.

In my free time, I like to run, watch musicals, eat ice cream, and visit libraries. I also am a weaver who recently was artist-in-residence at Praxis Fiber Workshop’s Digital Weaving Lab and am currently regional artist-in-residence in the fibers studio at Contemporary Craft.


Semantic Scholar Google Scholar
Bluesky Mastodon Twitter
Research Ethos
adevos [at] cmu [dot] edu

HIGHLIGHTED PUBLICATIONS: (see more here)

Alicia DeVrio, Myra Cheng, Lisa Egede, Alexandra Olteanu, & Su Lin Blodgett. A Taxonomy of Linguistic Expressions That Contribute To Anthropomorphism of Language Technologies. CHI, 2025.
pdf video

Alicia DeVrio, Motahhare Eslami, & Kenneth Holstein. Building, Shifting, & Employing Power: A Taxonomy of Responses From Below to Algorithmic Harm. FAccT, 2024.
pdf video

Alicia DeVos, Aditi Dhabalia, Hong Shen, Kenneth Holstein, & Motahhare Eslami. Toward User-Driven Algorithm Auditing: Investigating users' strategies for uncovering harmful algorithmic behavior. CHI, 2022.
pdf video

Hong Shen*, Alicia DeVos*, Motahhare Eslami, & Kenneth Holstein. Everyday Algorithm Auditing: Understanding the power of everyday users in surfacing harmful algorithmic behaviors. CSCW, 2021.
pdf video