Kate Crawford’s “Data” chapter from The Atlas of AI was an interesting read. One of the sections that stood out to me was the section on mug shots. Crawford discusses how the stories, context, and names behind these mugshots get lost or erased when they become data. The people whose mugshots are taken are reduced to data points which are often used in facial recognition training for machine learning systems. Crawford’s article reminds me of a section in Ruha Benjamin’s book Race After Technology, that I believe touches on how AI/Algorithms can be used to dehumanize an individual or their experiences.

The example shared is about a company called HireVue that employs an AI-powered program to analyze recorded interviews from prospective employees. To decide whom to flag as desirable hires and whom to reject, the program takes thousands of data points such as facial expression, posture, and vocal tone then compares the jobseekers’ scores to those of existing top-performing employees. Why would this be such a bad thing? Well, from an applicant’s perspective, the experience left much to be desired. The frustrating lack of human contact was one issue and a lack of transparency about how they were being evaluated or why they were rejected proved another. One job seeker expressed feeling a sense of worthlessness because “the company couldn’t even assign a person for a few minutes” (p.89) and shared how they questioned every small movement and micro-expression they made.

I think this demonstrates how important the human perspective is and how dangerous it could be to replace it with algorithms. Much like when a mug shot is taken and the individual is reduced to data, I believe the job seekers in the example weren’t seen as people by the AI program but rather as data to be read. I wouldn’t be surprised if the data captured from them was then used to train other similar models likely without these applicants being none the wiser.