Will AI give you the job? Automated hiring tools spark discrimination and secrecy lawsuits
A growing wave of US lawsuits is challenging the use of artificial intelligence in hiring and firing decisions, with critics arguing the technology enables discrimination while operating without transparency or accountability. Product manager Erin Kistler is leading a class action against Eightfold AI, a hiring software maker used by hundreds of companies including PayPal, Microsoft and Netflix, after applying to thousands of roles over four years without ever landing an interview. Her lawyers argue that automated screening effectively creates undisclosed applicant dossiers that rank candidates without allowing them to see or contest the results, and separate cases against Meta and IBM allege AI systems were used to target workers for layoffs or discriminate against older employees.
The scale of AI adoption in recruitment is significant: a World Economic Forum report found 90% of employers used some form of hiring automation last year, ranging from basic degree-requirement filters to AI-driven skills assessments and even initial phone interviews. Eightfold, which describes itself as holding data on over a billion workers drawn from résumés, LinkedIn and social media profiles, scores applicants from 0 to 5 to predict job performance, a rating that can determine who gets interviewed. Legal experts, including Emory University's Ifeoma Ajunwa, note that no US law currently requires employers to disclose when AI is used to evaluate candidates, and lawyers such as Rachel Dempsey argue job seekers deserve the same transparency rights over these assessments that already apply to credit reports.
- Lawsuits accuse AI hiring tools like Eightfold of bias and secrecy.
- 90% of US employers now use hiring automation, WEF reports.
- No US law requires firms to disclose AI use in hiring decisions.
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Employers use automated tools to sort applications, assess candidates and, in some cases, make decisions about staff layoffs. The systems range from simple filters, such as checking for a required degree, to software that scores applicants using information from CVs and online profiles.
Hiring software firms supply these tools to employers, while job applicants and workers are affected by the decisions they help shape. US lawsuits have raised questions about whether such systems can disadvantage people because of age or other factors, and whether individuals can find out what information was used to assess them.
The issue matters because automated assessments can influence who gets an interview or keeps a job, often without people knowing how the decision was made. There is no general US requirement for employers to tell applicants when AI evaluates them, leaving courts to consider questions of fairness, disclosure and accountability.
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The strongest fair case each way — we don't pick a winner.
The case for
Supporters of AI hiring systems argue that they improve efficiency and consistency by processing thousands of applications that would overwhelm human recruiters, whilst well-designed algorithmic assessments can reduce unconscious bias inherent in subjective human judgment. They contend that data-driven evaluations based on objective performance metrics and skills provide fairer, more meritocratic hiring than the alternative of gut impressions, networking, and informal decision-making that has historically disadvantaged many candidates.
The case against
Critics argue that AI hiring systems operate as unaccountable black boxes, ranking candidates without disclosure and preventing applicants from seeing or contesting results that determine employment prospects. They contend these systems risk perpetuating historical discrimination, since algorithms trained on past hiring patterns may encode existing biases, whilst the secrecy surrounding their operation prevents the external scrutiny necessary to identify such problems and the legal protections that should apply to employment decisions affecting people's livelihoods.