When I read Anna Gu’s recent piece on UCLA’s new digital humanities major, I was struck by something the curriculum must emphasize.

This major is intended to prepare students to shape technology responsibly. If so, students should not only learn how to use emerging technologies but also how to evaluate the biases built into them.

[Related: UCLA launches digital humanities major, establishes standalone department]

Gu writes that UCLA’s digital humanities major, the first in the nation to be established as a standalone department, will integrate technology with the study of society.

While the program currently offers some courses that address data bias, such as Community Engagement and Social Change M121: “Race, Gender and Data,” courses training students to identify and address bias in technology should be a priority.

Facial recognition algorithms employed by police precincts often use mugshot databases to identify people, which can perpetuate racial disparities embedded in historical data.

Artificial intelligence screening tools used by employers may downgrade resumes from historically Black colleges and women’s colleges. These systems can reinforce barriers faced by communities that have historically faced barriers to white-collar employment.

Such examples demonstrate why students entering technology-related fields need formal training in recognizing and addressing algorithmic bias. UCLA should ensure digital humanities students take courses on bias in datasets and AI.

Hands-on exercises, such as completing a project evaluating an algorithm for potential sources of bias, would also improve students’ understanding of bias.

The major should not simply prepare students to work with technology. It should prepare them to shape technology responsibly.

Lavanya Sathyamurthy is a recent graduate of the School of Law, where she specialized in critical race studies.