Computing Is Indeed a Discipline in Crisis (cacm.acm.org)

The computing field is facing a multi‑front crisis: explosive private investment chasing AGI and productizable AI contrasts with shrinking U.S. federal support for academic computing, weakening the traditional pipeline of faculty, PhD students and postdocs. Talent inflows are already cooling—international enrollments look set to fall, tech hiring has softened amid layoffs and automation, and a high‑profile MIT study suggesting 95% of enterprise generative‑AI programs fail underscores that deployment realities lag the hype. Together these trends concentrate influence and agenda‑setting in well‑funded Silicon Valley labs, leaving academic research underfunded and less able to pursue long‑term, foundational work. That concentration has technical and structural implications: reliance on corporate money biases research toward short‑term, productizable outputs; fewer graduate students and less stable academic staffing threaten basic research and reproducibility; and scholarly infrastructure is straining—AAAI‑26 saw roughly 23,000 valid submissions, a volume that breaks traditional peer‑review and curation models. The combination of overhype, poor deployment outcomes, talent pipeline erosion, and overloaded venues raises the real possibility of another “AI winter” unless policymakers, funders, and the research community act to rebalance public investment, preserve open foundational research, and redesign scholarly evaluation and conference reviewing at scale.