WATCH
MEASUREDActivity becomes data.FIELD GUIDE · WORK, MANAGEMENT & THE ALGORITHM
SHOULD AI BE ALLOWED TO FIRE YOU?
Software already schedules, monitors, scores, ranks, and filters workers. Termination is where a productivity tool turns into a question about power, explanation, discrimination, and appeal.
UPDATED 2026-09-22
THE PROBLEM
YOUR TERMINATION WAS GENERATED SUCCESSFULLY
The manager clicked approve. The score arrived first.
Algorithmic management is software that performs tasks managers used to do: assign work, monitor activity, evaluate performance, rank people, and recommend actions. A human may still click the final button, but the practical power can sit upstream in the data and score that shaped the decision.
SCORE
RANKEDA proxy becomes an evaluation.RECOMMEND
RED FLAGThe machine shapes attention.FIRE
WHO OWNS IT?A human signature does not answer the whole question.THE FIGHT
WHO FIRED YOU: THE BOSS OR THE SYSTEM?
Employment decisions determine income, insurance, immigration status, housing stability, reputation, and careers. Automation can make management faster and more consistent, but it can also turn bad proxies into policy at scale and make it difficult for workers to know what evidence actually cost them a job.
THE MANAGEMENT CASE
DATA CAN HELP MANAGERS MAKE MORE CONSISTENT DECISIONS
Algorithmic tools can surface patterns, reduce repetitive supervision, allocate work, and support faster decisions across large organizations. OECD survey data shows managers who use these systems often report more information and faster decision-making.
A dashboard can reveal what one manager cannot personally observe.
THE WORKER CASE
HIGH-IMPACT DECISIONS NEED EXPLANATION AND ACCOUNTABILITY
Automated evaluation can rely on incomplete proxies, reproduce historical patterns, or penalize circumstances the system does not understand. Employment law still applies, and current litigation is testing who is responsible when AI-driven tools allegedly produce discriminatory outcomes.
A spreadsheet does not become fair because nobody remembers who wrote the formula.
THE WEIRD SHIT
THE BOSS NOW HAS A DASHBOARD FOR YOUR EXISTENCE
ALGORITHMIC MANAGEMENT IS ALREADY WIDESPREAD
A 2025 OECD employer survey across six countries found widespread adoption of software that instructs, monitors, or evaluates workers, with especially high adoption reported in the United States.
This is not only a future-of-work scenario.MANAGERS THEMSELVES REPORT ACCOUNTABILITY CONCERNS
In the OECD survey, nearly two-thirds of managers using algorithmic management reported concerns about worker impacts; unclear accountability and inability to follow the logic of decisions were among the leading issues.
The people deploying the tools also see governance problems.A 2026 META LAWSUIT DIRECTLY CHALLENGES AI'S ROLE IN LAYOFFS
Twenty-six former Meta employees alleged that AI-powered systems disproportionately targeted workers with disabilities or medical leave in a mass layoff. Meta disputed the claims and said humans made the decisions; the merits remain contested.
The case illustrates the exact dispute: when is an AI-influenced termination legally and practically a human decision?AI EMPLOYMENT SCREENING IS ALREADY UNDER MAJOR LEGAL TEST
Workers in Mobley v. Workday allege AI-based screening produced discriminatory rejections. Workday denies wrongdoing, and the litigation is testing how liability should be allocated between software vendors and employers.
Automated employment decisions do not sit outside ordinary discrimination law.THE PEOPLE WITH A STAKE
WHO GETS TO APPEAL A NUMBER?
WORKERS
They bear the direct consequence of an incorrect score, opaque evaluation, or automated recommendation that shapes access to work.
MANAGERS
They gain scale and information but may become dependent on tools they cannot fully interrogate.
EMPLOYERS
They capture efficiency and remain exposed to legal and reputational consequences when automated decisions violate worker rights.
SOFTWARE VENDORS
Their models can become de facto decision infrastructure while courts and regulators debate how much responsibility travels with the tool.
THE UNANSWERED QUESTION
WHAT MUST A HUMAN ACTUALLY DO BEFORE A MACHINE-INFLUENCED FIRING?
- Audited evidence that automated performance systems predict job-relevant outcomes better than human management without creating protected-group disparities.
- Rules requiring workers to know when automated systems materially influence discipline, promotion, scheduling, or termination.
- Appeal mechanisms that let workers inspect and correct the data and assumptions behind consequential scores.
- Clear legal standards for responsibility among the employer, manager, and software vendor when automated recommendations cause unlawful harm.
TAKE THIS TO DINNER: The machine can produce a score. Someone still has to own the firing.
RECEIPTS
The lawsuit claims are contested. The management software is not imaginary.