Hello! I'm Alicia DeVrio.

I'm a PhD student advised by Ken Holstein at Carnegie Mellon University's Human-Computer Interaction Institute. My work explores ways to reduce harm by shifting power to those who use & are most affected by algorithmic systems.

adevos [at] cmu [dot] edu

Previously, I

• Experimented on Noom's sign-up survey as a growth product manager
• Led product testing efforts for wsj.com & barrons.com at Dow Jones
• Graduated from Brown University with a computer science degree (where I also completed significant writing coursework)

I like to run & read for fun, but not simultaneously. My free time is spent watching musicals, eating ice cream, & figuring out how to pronounce "apropos". My favorite color is red, my favorite software application is InDesign, & my favorite punctuation marks are the en dash & the interrobang.

LATEST UPDATES:

October 2023 - excited to attend 2 workshops at CSCW, one on labor & one on community-collaborative approaches

January 2023 - paper on user-driven algorithm auditing in industry practice accepted to CHI 2023

May 2022 - presented paper on users' strategies for uncovering harmful algorithmic behavior at CHI 2022

February 2022 - paper on users' strategies for uncovering harmful algorithmic behavior accepted to CHI 2022

October 2021 - presented everyday algorithm auditing paper at CSCW 2021

July 2021 - paper on everyday algorithm auditing accepted to CSCW 2021

August 2020 - started human-computer interaction PhD at Carnegie Mellon University

PUBLICATIONS:

Alicia DeVrio, Motahhare Eslami, Kenneth Holstein. Building, Shifting, & Empolying Power: A Taxonomy of Responses From Below to Algorithmic Harm. To Appear at FAccT, 2024.

Wesley Hanwen Deng, Bill Boyuan Guo, Alicia DeVrio, Hong Shen, Motahhare Eslami, Kenneth Holstein. Understanding Practices, Challenges, and Opportunities for User-Driven Algorithm Auditing in Industry Practice. Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems. (CHI), 2023.
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. Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems. (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. Proceedings of the ACM on Human-Computer Interaction. (CSCW2), 2021.
pdf video