I think recent graduates, especially those in the computer sciences, are facing obstacles in finding work unlike any time in the recent past. The journeys of Zach Taylor and Manasi Mishra illustrate these challenges. Both graduates have navigated a landscape increasingly influenced by artificial intelligence, which appears to complicate rather than simplify the job-seeking process.
Zach Taylor is a recent graduate of Oregon State University. Desperate to get back to work, he sent applications to almost 6,000 different tech jobs. Unfortunately, despite these efforts, he was only able to set up 13 interviews and ended up not receiving a single job offer. This shocking reality is not an anomaly but rather the tip of a deeply disturbing trend. Students are getting caught in what some have termed an “AI doom loop.” Instead, students are using artificial intelligence tools to help them speed through the application process for full-time jobs. Too often, they encounter automated systems that reject their applications in a matter of minutes.
21-year-old Manasi Mishra, a recent graduate from Purdue University, dealt with her own challenges in the labor market. The six-figure starting salaries promised to her while in school turned into just one interview offer—at Chipotle. Unluckily for her, she was not awarded that appointment either. This experience is sadly indicative of a larger trend in which computer science graduates are having difficulty making the transition from school to work.
As recent research from the Federal Reserve Bank of New York has shown, the unemployment rate for recent computer science grads is approximately zero percent. As of today, those rates are anywhere from 6.1% to 7.5%. These statistics are nothing short of horrifying. When we juxtapose those with the unemployment rates for graduates of majors such as biology and art history, we find that they have unemployment rates more than twice those of computer science graduates!
In this environment, both job seekers and employers are turning to AI. This trend begs significant questions regarding the effectiveness of traditional job application practices. Today, most businesses have turned to automated applicant tracking systems to weed out job applicants. In doing so, qualified candidates frequently fall through the cracks just because their applications fail to measure up to the algorithm’s standards. Yet graduates such as Taylor and Mishra encounter a maddening Catch-22. As qualified as they are, they can barely demonstrate their value under the automated processes established.
