Companies cite AI for layoffs in Michigan, but it's not so simple - The Detroit News

TEXT START: Across Michigan, companies are citing artificial intelligence as a driver behind workforce reductions — from a Grand Rapids insurance and fintech giant cutting thousands of jobs to a broader wave of technology sector layoffs nationally that experts say is only partly about AI itself.

The Dissection

The article correctly identifies “AI washing”: companies attaching an attractive future-facing explanation to layoffs also caused by weak sales, over-hiring, outsourcing, or restructuring. But it then turns that valid observation into a false reassurance. It reports the early dismemberment of jobs and labels the body alive because no single occupation has vanished whole.

Acrisure shows AI investment, offshoring, and conventional cost reduction operating together. Scripps shows software compressing newsroom production while leaving a smaller number of visible specialists. GM shows old technical roles being removed while a narrower AI-oriented layer is hired. Ford shows augmentation during the transition phase, when AI increases the output controlled by fewer skilled workers. None of this refutes displacement. It describes task decomposition, labor arbitrage, and the first repricing of human work.

The Core Fallacy

The article assumes that AI must perfectly replace an entire job before it can destroy its economic value. That is the wrong threshold. If AI removes enough tasks, increases each remaining worker’s span of control, or lets one team produce what previously required several, the firm can cut headcount without possessing a perfect human substitute.

“AI washing” may explain the rhetoric. It does not explain away the competitive mechanics. A company can cite AI dishonestly while still using automation to reduce the labor required per unit of output. Other firms then face pressure to match the lower cost. The label can be fraudulent while the repricing is real.

The article also treats current unemployment data, rehiring, and AI-linked hiring as evidence against structural collapse. That confuses the transition with the endpoint. The Discontinuity Thesis does not require immediate total job extinction. It requires durable superiority in cognitive task production, institutional inability to preserve human-only economic domains, and the gradual loss of economically necessary labor for the majority.

Hidden Assumptions

• Whole-job substitution is the relevant measure of obsolescence.
• New AI-related roles will appear in comparable volume, pay, geography, and accessibility.
• Displaced workers can reskill quickly enough to outrun falling labor demand.
• Firms will distribute productivity gains through wages instead of capturing them through lower headcount, higher margins, or greater capital returns.
• Human traits such as trust, empathy, judgment, and relationship management will remain scarce and economically indispensable rather than becoming narrower premium niches or increasingly automated interfaces.
• Temporary augmentation proves long-term complementarity.
• A “people-first” reskilling program can solve an ownership problem. It cannot. Workers may learn to operate systems whose gains and control belong to someone else.

Social Function

Classification: partial truth serving as transition management and ideological anesthetic, with a layer of elite self-exoneration.

The article gives managers a respectable vocabulary for mass reductions and gives workers a familiar remedy—become more adaptable, more AI-literate, and more “human.” That advice may improve an individual’s odds, but it does not preserve the wage-to-consumption circuit. It shifts responsibility for systemic repricing onto the people being repriced.

The piece is not crude propaganda. Its reporting on offshoring, task substitution, failed automation, and AI washing is useful. Its anesthetic effect comes from treating those facts as proof that the old labor order remains fundamentally intact.

The Verdict

The article is accurate about immediate causes and wrong about systemic meaning. AI washing is real, but it is also a decoy. Layoffs caused today by outsourcing, fiscal trimming, or over-hiring can coexist with the construction of systems that make tomorrow’s labor less necessary.

The reported cases are lag defenses, not counterexamples: augmentation before replacement, hiring at a higher altitude while deleting routine work, and reskilling a shrinking control layer. The post-WWII employment-wage-consumption circuit is not disproven because AI has not yet swallowed every job. It is being hollowed out task by task. The article mistakes the remaining scaffolding for a functioning building.