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1Scan for outdated or missing drivers - takes under a minute2Repair Windows errors before they cause bigger problems3Fix the driver behind crashes, sound loss and screen glitchesYes, often—but not without limits. Employers may use software that ranks résumés, conducts video interviews, or recommends candidates, yet the tool remains subject to employment-discrimination, disability-accessibility, privacy, notice, consent, and local artificial-intelligence laws. Whether a particular use is lawful depends on where the job is located, what the system actually does, how much it influences the decision, and whether the employer tests and supervises it.
An algorithm cannot be used as a legal shield. The employer is generally responsible for a discriminatory selection process even when a third-party vendor supplied the model. Applicants should ask what was evaluated, seek an accommodation when needed, and keep records of notices, consent requests, interview failures, and rejection dates.
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What “AI hiring” can mean legally
“AI interview” describes several different activities. A scheduling chatbot that merely offers appointment times presents a different legal question from a model that scores a candidate’s answers and automatically removes the lowest-scoring applicants. Legal risk rises when software filters, ranks, classifies, recommends, or replaces a human’s discretionary judgment.
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Common functions and their significance
- Administrative tools: scheduling, reminders, or transcription may have limited effect on selection, but they still must not create disability barriers or mishandle personal data.
- Screening and ranking: résumé parsers and “fit” scores can become employment selection procedures when they decide who advances.
- Video or voice analysis: systems may evaluate answers, speech, facial movement, or other signals. Employers need evidence that any evaluated characteristic is necessary and job-related; a proxy can create disparate impact even if the model never receives a protected-class field.
- Recommendation or rejection: a human label does not cure an automated process if the recommendation substantially determines the outcome or receives no meaningful review.
Ask the employer whether the system only organizes information or whether it influences who is interviewed, hired, rejected, or promoted. That distinction helps identify which rules apply.
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Federal U.S. baseline: discrimination laws still apply
The Equal Employment Opportunity Commission treats employment tests and selection procedures covered by Title VII of the Civil Rights Act, the Americans with Disabilities Act (ADA), and the Age Discrimination in Employment Act (ADEA) as subject to the same anti-discrimination principles whether a person or an algorithm administers them. A procedure that disproportionately excludes people because of a protected characteristic can violate federal law unless the employer satisfies the applicable legal justification.
Disparate treatment and disparate impact
Disparate treatment occurs when a tool or its operator intentionally treats applicants differently because of race, sex, religion, national origin, age, disability, or another protected status covered by law. Disparate impact can arise when a seemingly neutral score or cutoff disproportionately screens out a protected group. An employer should be able to show that the measure is related to the job and consistent with business necessity, and should consider less discriminatory alternatives when the law requires it.
Using a vendor does not transfer that responsibility. Employers need a documented description of the model, the data and features it uses, validation evidence, subgroup results, and a process for investigating an unexpected pattern of rejection. A contract that says the vendor is responsible is not a defense to an applicant’s discrimination claim.
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Disability access is a central legal issue
The ADA requires employers to avoid screening out qualified disabled applicants who can perform essential job functions with or without reasonable accommodation. Employers should examine a hiring tool before deployment and at regular intervals while it is operating. Testing should include applicants with different disabilities and should look for barriers created by timing, interface design, speech or vision analysis, and required hardware.
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Examples of barriers
- A one-way video interview may be unusable with a screen reader, keyboard-only navigation, captions, or a speech-generating device.
- A timed game can penalize an applicant whose disability affects processing speed even when speed is not an essential job function.
- Voice, eye-contact, facial-expression, or movement analysis can mistake a disability-related trait for low “engagement.”
When an online interview does not work with a blind applicant’s screen reader, an accessible version or another reasonable accommodation may be required unless providing it would cause undue hardship. Employers should offer a clear, non-punitive way to request an accommodation and should not force an applicant to disclose more medical information than is necessary to arrange it.
What an applicant can request
Explain the barrier and ask for an alternative interview format, extra time, captioning, screen-reader compatibility, a human review, or another effective accommodation. Make the request before the deadline when possible, but a late request should still be considered. Save the request and the employer’s response. A rejection immediately after an accommodation request, or a refusal to provide any accessible route, can be important evidence.
New York City: Local Law 144 and automated employment decision tools
New York City Local Law 144 applies to a qualifying automated employment decision tool (AEDT). The Administrative Code defines an AEDT as “any computational process, derived from machine learning, statistical modeling, data analytics, or artificial intelligence, that issues simplified output, including a score, classification, or recommendation, that is used to substantially assist or replace discretionary decision making for making employment decisions that impact natural persons.” Screening candidates for employment or employees for promotion is within the covered employment decisions.
Core duties for covered use
- Bias audit: the employer or employment agency generally needs a bias audit completed within the required one-year window.
- Public information: specified information about the audit must be made publicly available.
- Candidate or employee notice: people must receive notice about the tool and the job qualifications or characteristics it assesses.
Coverage depends on the tool’s actual output, the decision it influences, and the employment relationship. A system that only schedules interviews may fall outside the AEDT definition, while a ranking model that substantially determines who advances may fall inside it. Check the current New York City Administrative Code and Department of Consumer and Worker Protection (DCWP) guidance for the particular deployment.
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A December 2025 New York State Comptroller release reported that, in a test of complaint-routing calls, 3 of 12 calls (25%) were correctly transferred to DCWP, 8 of 12 (67%) were misdirected, and 1 call was returned to the employer. Those figures describe routing performance, not whether an AI hiring tool was lawful or accurate. They do show why a complainant should document the employer, tool, work location, and dates when seeking help.
Illinois: special rules for AI-analyzed video interviews
Illinois has a specific Artificial Intelligence Video Interview Act. It applies when an employer asks an applicant to record a video interview and uses artificial intelligence to analyze it.
Notice and consent before the interview
Before requesting the interview, the employer must:
- Notify the applicant that artificial intelligence may analyze the video and consider the applicant’s fitness for the position.
- Explain, in plain language, how the AI works and the general characteristics it evaluates.
- Obtain the applicant’s consent.
The statute states that an employer may not use artificial intelligence to evaluate applicants who have not consented. Consent should be meaningful; a vague reference to “technology” does not explain what the system evaluates.
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Sharing and deletion
The employer may share applicant videos only with people whose expertise or technology is necessary to evaluate them. If an applicant requests deletion, the employer must delete the interview and instruct recipients to delete their copies, including electronic backups, within 30 days. Keep a dated copy of the request and any confirmation. The law concerns the recorded interview and copies; it does not give an employer permission to retain or repurpose the material indefinitely.
European Union: recruitment systems are generally high-risk
The EU Artificial Intelligence Act lists AI intended for recruitment or selection in Annex III as a high-risk employment use case. The list includes systems that place targeted job advertisements, analyze and filter applications, or evaluate candidates.
The European Commission gives automated job matching and ranking as an example. A system that analyzes résumés, skills, education, competencies, or historical hiring data and produces scores, rankings, or fit categories can fall into the high-risk category. High-risk classification brings governance, documentation, risk-management, data-quality, transparency, and human-oversight obligations for the actors covered by the Act.
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The Act is risk-based and has exceptions and phased application dates. A narrow procedural or preparatory function may be treated differently under Article 6, while profiling or material influence on a hiring decision can affect classification. Employers operating across the EU should use the current regulation and Commission implementation guidance to determine the applicable date, whether the system is in scope, and which obligations fall on the employer, provider, or another operator.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How to tell whether an employer’s use is likely covered
- Identify the location: use the job’s work location and the jurisdiction where the hiring decision occurs. A remote role can involve more than one legal regime.
- Identify the function: ask whether the system schedules, transcribes, filters, scores, ranks, recommends, or rejects.
- Measure influence: determine whether a human independently reviews the underlying application or simply accepts the automated result.
- Check the data: ask what characteristics are evaluated and whether voice, face, expression, accent, school, postcode, career gap, or other proxies could reproduce protected-group disparities.
- Check safeguards: look for notice, consent where required, an accommodation channel, human reconsideration, retention limits, and a way to correct errors.
What employers should do before and during deployment
1. Define the decision and document job-relatedness
Write down the essential functions of the role, the competencies being measured, the cutoff or ranking rule, and why each feature is necessary. Remove facial-expression, voice, or other proxy signals that lack validated necessity. A general claim that a model measures “culture fit” is not a substitute for a job-related criterion.
2. Validate for adverse impact and accessibility
Test before launch and at regular intervals. Preserve the tested population, sample limitations, methodology, thresholds, subgroup results, accommodation tests, and corrective actions. A small or unrepresentative validation set cannot establish that a tool works fairly for every applicant.
3. Give understandable notice and obtain required consent
Tell applicants what the tool does, what general characteristics it evaluates, and whether a human will review the result. Follow special rules such as Illinois’s advance disclosure and consent requirement. In New York City, provide the AEDT notice and the assessed qualifications or characteristics when the law applies.
4. Provide accommodation and meaningful human review
Offer an accessible route without penalizing the applicant. Train reviewers to consider the underlying qualifications rather than treating an automated score as conclusive. Create a documented process to correct a data error, reconsider a recommendation, and explain who made the final decision.
5. Control vendors and records
Contracts should specify permitted data use, access controls, sharing, retention, deletion, security, audit cooperation, and incident reporting. Keep records of model versions, validation, notices, consent, accommodation requests, human overrides, complaints, and retention or deletion actions. In Illinois, the deletion workflow must reach recipients and electronic backups within 30 days after a valid request.
What candidates can do if an AI process seems unfair
- Ask what technology was used, what it evaluated, and whether a human reviewed your application.
- Request a reasonable accommodation or accessible alternative as soon as you identify a barrier.
- For an Illinois video interview, ask when consent was obtained and request deletion if you no longer want the interview retained.
- Save the job posting, instructions, notices, consent screen, interview invitation, error messages, accommodation correspondence, and rejection notice.
- Ask for reconsideration by a person and identify a specific factual error, inaccessible step, or job requirement the tool appears to have mismeasured.
- Contact the relevant enforcement agency or an employment lawyer. In New York City, determine whether the employer or agency used a covered AEDT and whether the required audit and notice information was available.
An adverse result alone does not prove unlawful discrimination. Stronger evidence includes a pattern affecting a protected group, a tool that evaluates traits unrelated to essential duties, refusal of an effective accommodation, missing legally required notice or consent, or a human process that automatically adopts the model’s recommendation without review.
Quick jurisdiction comparison
| Jurisdiction | Covered use | Notice or consent | Testing, oversight, or data duties |
|---|---|---|---|
| United States federal law | Employment tests and selection procedures under Title VII, ADA, and ADEA | Requirements vary by law and facts; ADA accommodation may be required | Employer remains accountable for discriminatory disparate treatment or disparate impact; accessibility and validation should be examined before and during use |
| New York City Local Law 144 | Qualifying AEDTs that substantially assist or replace discretionary decisions, including candidate screening | Notice about the tool and assessed qualifications or characteristics | Bias audit within the required one-year window and public audit information |
| Illinois AI Video Interview Act | Recorded video interviews analyzed by AI | Advance disclosure, plain explanation, and consent; no AI evaluation without consent | Limit sharing; delete the interview and instruct recipients to delete copies, including backups, within 30 days of a request |
| European Union AI Act | Recruitment and selection systems, including targeted advertising, application filtering, and candidate evaluation | Obligations depend on the system, role, and applicable phase of the Act | High-risk governance requirements may apply; scope exceptions and Article 6 classification must be assessed |
Bottom line for applicants and employers
AI hiring is not automatically illegal, but it is never outside ordinary employment law merely because a machine produced the score. Employers need job-related criteria, adverse-impact and accessibility checks, clear notices, legally valid consent where required, accommodation routes, human oversight, and disciplined data retention. Applicants can ask how the tool affected the decision, request an accessible alternative, preserve evidence, and use the jurisdiction’s enforcement or legal channels when the process appears discriminatory or fails to meet notice, consent, audit, or deletion rules.
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