In early June, Amanda Claypool encountered a frustrating obstacle while searching for a job at a fast-food restaurant in Asheville, North Carolina. The problem she faced was glitchy chatbot recruiters. For instance, McDonald's chatbot recruiter "Olivia" initially approved Claypool for an in-person interview but failed to schedule it due to technical issues. A Wendy's bot managed to schedule her for an interview, but unfortunately, it was for a job she was unable to do. Then, a Hardees chatbot sent her to interview with a store manager who was on leave, resulting in confusion at the restaurant. Claypool ultimately found a job elsewhere but described the experience as unnecessarily complicated. Healthcare, retail, and restaurant industries increasingly rely on HR chatbots, like the ones Claypool encountered, to sift through applicants and schedule interviews with potential candidates. Companies such as McDonald's, Wendy's, CVS Health, and Lowes utilize Olivia, a chatbot developed by a $1. 5 billion AI startup called Paradox. Similarly, L'Oreal relies on Mya, an AI chatbot developed by a San Francisco-based startup with the same name. While these hiring chatbots primarily screen for high-volume job positions like cashiers, warehouse associates, and customer service assistants, Claypool's experience highlights their occasional glitches and lack of human support when issues arise. Additionally, the straightforward answers that many of these chatbots require might lead to the automatic rejection of qualified candidates who may not respond in the way the language model expects. This can pose challenges for individuals with disabilities, those with limited English proficiency, and older job applicants.

Experts worry that chatbots like Olivia and Mya may not provide reasonable accommodations or alternatives for job availability or roles for people with disabilities or medical conditions. The utilization of biased data during AI training also raises concerns about potential discrimination. For example, if chatbots analyze response times, grammar, or sentence complexity, they may introduce bias into their decision-making process. However, detecting such bias becomes challenging when companies do not disclose the reasons for candidate rejection. To address these issues, legislative measures have been introduced to monitor and regulate automation in hiring tools. For instance, New York City recently implemented a law that requires employers using automated tools like resume scanners and chatbot interviews to audit for gender and racial bias. Furthermore, some companies have turned to personality tests as screening methods, which may not be directly related to the job itself. These tests can result in candidates being rejected based on qualities like gratitude and personality rather than job-related skills. Despite the concerns, AI screening agents offer an attractive option for companies seeking to streamline their recruitment processes and reduce costs. By leveraging AI-powered technologies, HR departments can handle larger candidate pools more efficiently. However, it is important to note that many experts caution against solely relying on AI for hiring decisions. While chatbots offer benefits, they still have a long way to go in terms of evaluating candidates accurately and fairly.