Pause the termination process. Treat the algorithm’s recommendation as a signal to investigate—not as proof that dismissal is justified. Verify the underlying information and criteria, assess discrimination and accommodation risks, hear the employee’s response, and make and document an accountable human decision under the laws that apply. A human review is a prudent safeguard, but there is no single review rule that applies to every employer and every automated tool.
Why an algorithm’s recommendation is not the decision
Employers use automated tools to inform decisions about who will be let go. The U.S. Equal Employment Opportunity Commission (EEOC) describes AI as potentially “influencing or deciding who will be let go.” That description recognizes a use case; it does not approve any particular tool or establish that a particular termination is lawful.
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Responsibility remains with the employer. U.S. federal nondiscrimination duties still apply when an employer relies on information in an employment decision, including information supplied or evaluated by a vendor. In the EU, separate safeguards may apply when a decision is made solely by automated means and has legal or similarly significant effects. Whether a person meaningfully reviewed the recommendation, what data shaped it, and where the worker is employed can change the legal analysis.
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How to review a recommendation before acting
Use the following as a practical decision process, not as a claim that every jurisdiction mandates the same steps or appeal procedure.
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Pause and assign an accountable decision-maker
Do not let a score or alert trigger dismissal automatically. Name the person responsible for the decision and ensure they have authority, relevant information, and time to disagree with the tool. A reviewer who merely approves the output without evaluating the case is not meaningful oversight.
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Verify the record and the system’s relevant inputs
Check that the recommendation concerns the right employee and that dates, attendance, performance records, and other inputs are complete and accurate. Look for missing context, stale information, data-entry mistakes, or mistaken identity matches. Ask the vendor or internal technical owner which inputs and criteria materially shaped the result, and whether those criteria relate to the actual job and the concern being assessed.
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Check for discrimination and disability-related barriers
Ask whether the data, scoring criteria, or proxies could disadvantage people because of a protected characteristic. For disability, examine whether the tool measures a relevant job skill or instead screens out a qualified worker because of disability-related traits or the way the tool is used. Consider whether a reasonable accommodation is needed and how the assessment can be made fairly.
Special offer. See more information about Outbyte and uninstall instructions. Please review EULA and Privacy policy.EEOC and Department of Justice guidance warns that employment software can screen out qualified people with disabilities and recommends an accommodation process and examination of tools before and during use. The ADA applies to employment decisions such as selection, testing, and promotion; using another company’s tool does not permit discriminatory use. The agencies’ May 12, 2022 release quotes EEOC Chair Charlotte A. Burrows: “New technologies should not become new ways to discriminate.”
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Identify the legal trigger for the data and the workplace
Determine whether the recommendation relied on a third-party consumer report, whether the worker is in the EU, and whether state, local, collective-agreement, public-sector, or sector-specific rules apply. These questions are not interchangeable: a general performance signal, a disability-related measure, and a consumer report can raise different obligations.
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Explain the concern and hear the employee’s response
Tell the employee what factual concerns are under review in terms they can understand. Invite them to correct errors and provide relevant context, including information the system could not capture. Consider whether support, accommodation, a different corrective action, or no action is appropriate. In places where applicable law gives a route to human intervention or challenge, provide it; do not assume that every worker everywhere has the same formal appeal right.
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Make and record an independent decision
Decide based on verified evidence and applicable workplace rules, not on the existence of an algorithmic score. Record the relevant evidence, criteria, the employee’s response, any accommodation considered, the reviewer’s reasoning, and why the outcome follows. The explanation should be understandable to the employee; this is sound practice, not a claim that one identical notice is legally required everywhere.
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Respond to patterns, not just the individual case
If review exposes recurring errors, biased outcomes, or inappropriate inputs, restrict or suspend reliance while investigating. Correct records and the model or process as warranted, then monitor use and outcomes. The sources cited here do not establish a universal audit metric or threshold for every employer.
Additional requirements to check in the United States
Federal nondiscrimination rules still apply
EEOC and Federal Trade Commission background-check guidance says federal nondiscrimination laws apply whenever an employer uses background information to make an employment decision. A vendor’s role does not make discriminatory use permissible. The guidance also explains that it clarifies existing requirements and does not itself have the force and effect of law.
Consumer reports can trigger FCRA steps
If a third-party company that compiles background information supplied a consumer report used in the decision, check the Fair Credit Reporting Act (FCRA) process. The federal guidance describes written disclosure and authorization before obtaining the report. Before taking adverse action based on it, the employer must provide the required pre-adverse notice, a copy of the report, and a summary of rights; after the action, it must provide the specified notice. Verify the report’s accuracy and check applicable state and local rules as well. An internal performance algorithm alone does not, on the facts given here, establish that the FCRA applies.
Additional safeguards to assess for EU workers
The European Commission describes a GDPR protection against decisions based solely on automated processing when they produce legal effects or similarly significantly affect a person, subject to exceptions and safeguards. The safeguards described include human intervention, the ability to express a point of view, and the ability to challenge the decision. A nominal human sign-off is not necessarily meaningful intervention: the reviewer must actually evaluate the case.
The EU AI Act identifies specified AI uses in employment and worker management as high-risk. The Commission’s AI Act Service Desk notes that a system may fall within that category when scores influence employment outcomes even if a human retains discretion. Classification and obligations depend on the system’s purpose and influence, the parties’ roles, and the applicable implementation timeline. Check the current rules for the specific system and employer rather than assuming every workplace tool is covered in the same way.
What to tell the employee
Give a clear account of the concern, the relevant evidence, and the role the tool played without presenting its output as an unquestionable verdict. Explain how the employee can raise factual corrections or provide context, and what happens next. A transparent explanation makes it possible to address errors and helps show that the final decision rests on evidence and human reasoning. The exact notice and challenge rights depend on the law that applies.
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