The curtain of anonymity can produce amusing results. But there is a downside in the age of AI. (Photo illustration by Alexander Castro/Rhode Island Current)
My name is a catfish. Or, so I’ve been told. When you hear the name Jamie Jung, you might wonder if the face behind this article is a Korean girl or the great-grandson of Swiss psychiatrist Carl Jung. A name so mysterious, perhaps even AI would struggle to decipher my identity in my job application.
When the pandemic pivoted classrooms to Zoom, I hid behind a faceless black square, only two words revealing my name.. When calling attendance, many of my teachers would pronounce my last name with a German J as “Yoong” or refer to me with the pronouns “he” or “him.” Others would sound my name out phonetically “Jung” and refer to me as “she” or “her.”
As much as I enjoyed the curtain of anonymity, I have come to recognize there is a downside.
Companies such as Microsoft and Amazon delegate resume screening to AI tools in order to sift through countless applications from job-seekers. AI tools continue to evolve but there should be more attention on the flaws in algorithmic analysis, such as oversimplification and evaluation bias.
In 2014, Amazon attempted to automate its hiring process by building a computer program that would review applicants’ resumes and spit out a list of the top candidates. The computers were trained to assess applicants by observing resumes submitted to the company over a 10-year period. The problem? A majority of the applicants were men, which unintentionally taught the algorithm that male candidates were superior.
The impact of algorithmic bias is not limited to gender. A 2024 study from the University of Washington reported computer models favored white-associated names in 85.1% of cases and female-associated names in only 11.1% of cases. In 2017, the University of Toronto released a study that revealed applicants with Asian names had a 28% reduced likelihood of receiving interviews compared to applicants with Anglo names.
This pattern of discrimination even within a recruitment process solely managed by humans establishes a foundation already tainted with bias. Despite the growing diversity of the American workforce, the lack of leadership opportunities given to underrepresented communities serves as evidence of the lasting effects of systemic discrimination. According to the National Library of Medicine, although 74% of health care professionals are women, only 33% of management positions were filled by women. Similarly, while Black employees comprise 14% of all U.S. employees, only 7% of managers are Black.
When you hear the name Jamie Jung, you might wonder if the face behind this article is a Korean girl or the great-grandson of Swiss psychiatrist Carl Jung.
AI has the potential to revolutionize the workplace. Automating monotonous tasks within the hiring process allows employees to maximize productivity, and many human resource managers have recognized these benefits.
But by analyzing existing demographics of the workforce, algorithms can deduce that “‘top”’ applicants who fit the standard are white men. As long as this foundation remains skewed, AI will continue to exclude talented applicants based on an outdated algorithm.
A survey by CareerBuilder states 55% of HR managers say AI will become a regular part of HR in the next five years. Although the prospects of an efficient recruitment process are appealing, managers must evaluate the current state of their workforce before integrating AI algorithms in order to provide a fair opportunity for all applicants.
By prioritizing equal representation even before implementing AI, companies will be able to utilize algorithms with less worries about bias. The innovation of AI begins with human reflection and revision.
AI assumes that I am only what my name allows me to be, ignoring the scope of my accomplishments. I only started going by Jamie in my freshman year of high school, and I thrived under this new ambiguous identity: that year, I became the social media manager of two clubs, was selected to present a TEDx Talk, and was awarded “Freshman Writer of the Year” by my conservatory’s director. When I introduced myself in person the next school year, I was amused by the look of surprise on many of my teachers’ and classmates’ faces. It was clear I was not who they expected me to be.
What’s in a name? According to AI algorithms, a name is the reflection of our identities and the face behind these words. I wonder if I had introduced myself as Jaehee Jung, or if I had turned on my camera to reveal my true identity, would I have had the opportunities I did?
Maybe. My name is a gift I gave myself in search of belonging. Now I am searching to make this name my own. Not with recognition or achievements, but with the person I am behind the black square. And only I hold the power to decide when to turn it on or off.
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