After 'coding error' triggers firings, top NIH scientists called back to work

Skepticism about the “coding error” explanation

• Many commenters doubt that a genuine software bug caused the NIH firings; “coding error” is seen as a euphemism for leadership mistakes or political targeting.
• Several stress that “software doesn’t fire people, people fire people”: at best someone blindly trusted a tool without human review, at worst they’re retroactively calling a deliberate query an “error.”
• The fact that some staff were reinstated within 24 hours is read either as proof it was easy to undo a bad list, or as a tactical retreat under backlash, not an innocent glitch.

Incompetence, malice, or deliberate purge?

• A recurring theme is that the current administration and DOGE are engaged in a broad ideological purge of the civil service, intending to traumatize and demoralize “bureaucrats.”
• Commenters invoke “starve the beast”: deliberately make government dysfunctional, then cite that dysfunction as proof government can’t work and must be cut or privatized.
• Some argue serial incompetence without regard for consequences is indistinguishable from malice; others say both are clearly present.

Impact on science and biomedical research

• Many see this as part of a wider attack on NIH, CDC, USAID, and other science/health institutions, with potentially irreversible damage to research programs and public-health work.
• One subthread claims parts of biomedical research were already “sinking” due to fraud and perverse incentives; others vehemently counter that, despite flaws, public science is overwhelmingly life‑saving and must be reformed, not “burned down.”

Government vs business, efficiency, and employment

• Strong pushback against treating government like a cost-cutting corporation: money isn’t the primary goal; total social benefit is.
• Mass firings are criticized as inhumane and economically irrational, destroying the government’s reputation as a stable employer and making future recruitment more expensive and difficult.
• Debate arises over whether “stable job seekers” are desirable in government; many argue stability is precisely what complex, long-lived public systems need.

Technology, legacy systems, and AI scapegoating

• Jokes about PHP/Tcl/Rust and “select * from employees” mask serious concern about DOGE’s ambitions to rewrite Social Security and IRS systems without understanding decades of accumulated edge cases.
• Commenters warn that naïve rewrites (possibly with AI) risk cutting off legitimate beneficiaries and breaking tax infrastructure.
• The episode is linked to a broader pattern of using “the computer” or “AI” as a blame sink, echoing scandals where automated systems were trusted over humans with catastrophic consequences.