PhD Student in Information Science at University of Colorado Boulder
I am a PhD student researching identity representations in technical infrastructures.
Broadly, I am interested in identity theory, infrastructure studies, AI ethics, and digital identity.
I focus primarily on machine learning infrastructures that operationalize human identity characteristics, like gender and race.
In particular, I explore the real-world implications of machine learning for those with historically marginalized identities.
I am advised by Jed Brubaker in the Identity Lab.
PDFs of my work can be found on my Research page. Non-publication specific projects can be found under the Projects tab. This includes the HCI Gender Guidelines and my Prelim Reading List documentation.
- How We’ve Taught Algorithms to See Identity: Constructing Race and Gender in Image Databases for Facial Analysis. Morgan Klaus Scheuerman, Kandrea Wade, Caitlin Lustig, Jed R. Brubaker. Proc. ACM Hum.-Comput. Interact. 4, CSCW1, Article 58. May 2020. Best Paper Award. Recognition for Diversity and Inclusion.
- How Computers See Gender: An Evaluation of Gender Classification in Commercial Facial Analysis and Image Labeling Services. Morgan Klaus Scheuerman, Jacob M. Paul, Jed R. Brubaker. ACM Hum.-Comput. Interact. 3, CSCW, Article 144. November 2019. Best Paper Award.
- Safe Spaces and Safe Places: Unpacking Technology-Mediated Experiences of Safety and Harm with Transgender People. Morgan Klaus Scheuerman, Stacy M Branham, Foad Hamidi. 2018. PACMHCI. Volume 2, CSCW Issue. In Proceedings of the ACM on Human-Computer Interaction,, Vol. 2, CSCW, Article 155. November 2018. Recognition for Diversity and Inclusion.
- Gender Recognition or Gender Reductionism? The Social Implications of Automatic Gender Recognition Systems.” Foad Hamidi, Morgan Klaus Scheuerman, Stacy M Branham. In Proceedings of the ACM SIGCHI Conference on Human Factors in Computing Systems (CHI ’18). April 2018. Best Paper Award.
October 13 2020Extremely excited to announce that our CSCW 2020 paper, How We’ve Taught Algorithms to See Identity: Constructing Race and Gender in Image Databases for Facial Analysis., was awarded both a Best Paper Award and a Recognitions for Contribution to Diversity & Inclusion.
August 27 2020Two announcements: I will be working with Ethical AI at Google as a Student Research Fellow for the Fall 2020 term. And I have been honored by the CU Boulder Information Science Outstanding Research Award.
August 19 2020I gave a talk on How Computers See Gender at the Stanford HCI Group summer seminar series.
April 24 2020Excited to be working on the Ethical AI team at Google this summer!
Dec 3 2019Catch me at NeurIPS for the Queer in AI panel December 9th!
Nov 21 2019I was featured in several popular press articles discussing the ethics of facial analysis technology, including CNN, the Verge, and Quartz.
Oct 10 2019Check out my video interview with CU Boulder Today on gender in facial analysis technology.
Sept 27 2019I am honored to have received a Best Paper award from CSCW 2019 for our paper, How Computers See Gender: An Evaluation of Gender Classification in Commercial Facial Analysis and Image Labeling Services.