“Race, Gender, Class, & Computing”
Every discipline will eventually succumb to this progressive agenda. At what point does it overshadow the actual subject being studied?
The College Fix reports:
Duke computer science department offers new class on race and gender
Duke University this fall semester is offering a new class to its students titled: “Race, Gender, Class, & Computing.”
The course “explores the diversity, equity, and inclusion (DEI) challenges in computing,” according to the Computer Science department’s website. It will do so “through an introduction to and analysis of various social constructs and their impact on not only computing departments and organizations,” according to the course description.
The class is taught by Nicki Washington, a new instructor in the department. Washington designed the course, according to the department.
Washington did not respond to multiple emailed requests for comment in the past week and a half from The College Fix seeking comment on the desired goals for the course and a copy of the course syllabus and its reading list.
The school’s media relations office did not respond to multiple emailed requests for comment in the past week and a half seeking the same information.
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According to the student paper The Chronicle, the first part of the class will cover topics surrounding “race, ethnicity, gender, sexuality, class, ability, and religion, designed to help students form a foundational understanding of identity.”
Washington gave the student paper an example on a topic the course explored.
The professor said her class discussed “how people with darker skin tones are not properly recognized” by “facial recognition technology.”
In the short term, if I walk in front of a sensor, it may not sense me. If I’m on camera, then there’s a high likelihood that the image of me will be inaccurate. What does this mean? This means there’s a likelihood I could be falsely accused of committing a crime. We look at examples in the news where we see Black men who have been falsely arrested due to inaccurate facial recognition technology.
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