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No—not on the evidence described in the report. A University of Pennsylvania study was reported to associate AI-estimated personality traits from LinkedIn headshots with career outcomes among MBA graduates. That is not the same as showing that a face scan can reliably judge an individual applicant or tell an employer whether to hire them.
What the reported study actually examined
In a November 9, 2025 article, Futurism reported that researchers used a system based on earlier face-and-personality research to estimate the Big Five traits—openness, conscientiousness, extraversion, agreeableness and neuroticism—from LinkedIn profile photographs of 96,000 MBA graduates. The researchers then compared those estimates with career outcomes, according to the article.
Futurism said estimated extraversion had the strongest positive association with compensation, while estimated openness was associated with lower pay. Those are findings as reported by Futurism, not independently verified estimates. The underlying paper linked in the article was not accessible for review, so its methods, effect sizes, validation design and demographic results cannot be confirmed here. Read Futurism’s account.
Why that does not establish who should be hired
An association between estimated traits and career outcomes in a selected group does not demonstrate that facial appearance causes those outcomes. Nor does it show that a model can predict how a particular applicant will perform in a particular job. The reported study, as described, looked backward at estimates and career outcomes among MBA graduates; it was not described as a prospective hiring test or a comparison of job performance across occupations.
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For an employer to use an assessment responsibly, it must be shown to predict relevant work outcomes accurately and consistently in the setting where it will be used. The Society for Industrial and Organizational Psychology recommends that AI-based employment assessments be job-related, fair, and documented well enough for verification and auditing. A general fairness audit, by itself, does not prove that a score predicts success in a specific role. SIOP’s recommendations provide a useful framework for evaluating such claims.
What facial analysis in hiring can put at risk
Uneven accuracy and unsupported emotion claims
Facial, voice and speech analysis can raise disparate-accuracy and accessibility concerns. UK government guidance warns that systems may be less accurate for protected groups and notes there is little scientific consensus on inferring emotion from facial expressions. It advises employers to assess bias and monitor for degraded performance, rather than assuming a supplier’s results will transfer to their own workforce or recruitment context. UK guidance on responsible AI in recruitment.
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Disability access and accommodation
In the United States, the Department of Justice says the ADA applies throughout employment, including selection and testing. Its guidance warns that facial or voice analysis could screen out qualified people with disabilities—for example, applicants with autism or speech impairments. Employers remain responsible when they use a vendor’s tool, and should evaluate it before and during use and provide reasonable accommodations where required. DOJ guidance on AI and disability discrimination in hiring.
Questions to ask before trusting an AI hiring score
A headline or vendor demonstration cannot establish that a facial-analysis tool is valid for a real hiring decision. Employers evaluating one should ask for evidence specific to the role and deployment, including:
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- What job-related outcome is the score intended to predict, and how was that connection validated?
- Were applicants similar to the employer’s actual candidate pool included in validation, and are results reported for relevant demographic and disability groups?
- Can the vendor document how the model was developed, how scores are interpreted, and how performance is checked over time?
- Can candidates complete the process through an accessible alternative or with a reasonable accommodation?
- Will the employer pilot and monitor the tool in its own context, and have a process for investigating inaccurate or adverse outcomes?
UK guidance recommends bias assessment, monitoring and consideration of impact and data-protection assessments as appropriate. It also cautions that supplier data may not represent an employer’s own context; differences can become apparent during a pilot. US DOJ guidance likewise places responsibility on employers to examine tools before and while using them. These are jurisdiction-specific resources, not a determination of the legality of any particular product or deployment.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Legal rules depend on where and how a tool is used
The European Union’s AI Act lists certain workplace uses of AI to infer emotion among prohibited practices, with an exception for medical or safety reasons. The available legal text does not, by itself, resolve the status of this reported study or every hiring assessment; application depends on the use and relevant legal details. EU AI Act consolidated text.
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