Environmental concerns. Examples: • https://wisconsinwatch.org/2026/03/wisconsin-data-center-water-olympic-swimming-pools-microsoft-mount-pleasant-racine/ • https://www.independent.co.uk/tech/ai-data-center-emissions-environment-b2887454.html • https://www.theguardian.com/environment/2025/oct/04/pfas-pollution-data-centers-ai • https://www.theatlantic.com/magazine/2026/04/ai-data-centers-energy-demands/686064/ (if you have a public library, it might have a subscription you can use)
Economic concerns (& anger) — https://www.npr.org/2025/11/23/nx-s1-5615410/ai-bubble-nvidia-openai-revenue-bust-data-centers — https://fortune.com/2026/03/19/ai-memory-chip-shortage-hbm-economy/
Job frustrations (mass layoffs, management forcing slopware on employees, corrupted data, hardware failures from the AI acting as malware, growing communication gaps). Political alarm (the AI industry is bolstering the rise in fascism by interfering in democratic processes and civil rights). Ethics. Fatigue with the slop. Personal costs to deal with DDoS attacks and accidental code that affects hardware. Distrust and anger from unauthorized scraping for training datasets.