Erin Kistler filed a class-action lawsuit against Eightfold AI in a California court in January, alleging that its hiring software ranks job applicants without providing them access to the scores. The lawsuit says the software functions as an undisclosed consumer report or applicant dossier, ranking candidates on their likelihood of success without allowing them to view or contest the results, Kistler’s legal team says. The case is one of several recent legal challenges involving AI in employment decisions. Workers have also sued Meta over an internal AI system that allegedly targeted them for layoffs after parental or medical leave. A separate lawsuit against IBM claims that its AI tools discriminated against older workers. A World Economic Forum report found that 90% of US employers used some form of automation in hiring last year. Eightfold AI says it maintains a database of résumés, LinkedIn profiles and social media information for more than a billion workers. The company uses AI to assign each applicant a score from zero to five, predicting how well they would perform in a given role. The score can prioritize certain candidates for interview consideration. Kistler’s attorney Rachel Dempsey said applicants deserve the same transparency as credit reports, allowing them to dispute inaccuracies. She noted that without visibility into the algorithmic evaluation, candidates cannot determine whether bias is present. Ifeoma Ajunwa, a law professor at Emory University, said there is no legal requirement for companies to disclose the use of AI hiring systems. Eightfold AI responded in a statement that the claims are without merit and that it will defend itself vigorously. Meta declined to comment on its lawsuit, and IBM said it does not use AI to automatically screen out candidates and does not condone discrimination. Experts say AI can replicate or amplify existing hiring biases. For example, Amazon discontinued an AI tool that downranked women’s résumés after identifying the bias. Research by Ajunwa found that AI systems sometimes score applicants with southern accents lower during voice interviews. Xuechunzi Bai, an assistant professor at the University of Chicago, said the magnitude of bias in AI can be stronger than in human hiring decisions. In a study co-authored by Bai, AI models assigned hiring decisions to fictional demographic groups based on stereotypes rather than qualifications. The study found newer and more advanced AI models produced greater bias than earlier versions. Ajunwa explained that algorithmic decisions can be applied repeatedly across companies, effectively blackballing a candidate. Katie Creel, co-author of a study on algorithmic monoculture in hiring, warned that widespread use of the same AI models could limit job opportunities for many applicants. New York City law requiring annual bias audits and prior notice to candidates took effect in 2023, but it applies only to software that substantially assists or replaces human decision‑making. Illinois and Colorado have enacted statutes prohibiting AI tools that result in unlawful discrimination. Jenny Yang, a partner at the law firm representing the plaintiffs, said early notification about AI use helps identify potential problems. She added that growing worker concern about opaque algorithmic dossiers underscores the need for greater transparency. The outcome of these lawsuits could shape future hiring practices, regulatory standards and the level of transparency candidates receive. Whether AI can be responsibly integrated into hiring remains an open question.