Why Does Everyone Hate AI?

Scope of “everyone hates AI”

• Several commenters argue “everyone” is exaggerated. Surveys cited: a US poll with ~60% negative, 40% neutral/positive; others showing strong US/Anglosphere skepticism but more optimism in Asia.
• Many note high usage despite dislike: roughly half of Americans reportedly use AI chatbots; many students and teachers do as well.
• Some frame apparent consensus as a “vocal minority + availability” effect: anti‑AI voices are louder than pro‑AI users who quietly rely on it.

Economic anxiety and labor impacts

• Strong concern that AI will automate white‑collar work, decimate “commercial art” and content jobs, and concentrate wealth further.
• People expect efficiency gains to enrich owners, not reduce prices or improve ordinary lives.
• Fear that knowledge work offshores or disappears, pushing people into fewer, worse‑paid roles; talk of UBI or fake jobs programs as eventual responses.

Art, creativity, and meaning

• Many see generative AI as theft of artists’ work via mass scraping and unpaid training.
• AI output is often described as soulless, emotionally empty, “plastic,” and flooding markets with cheap, bland content.
• Key distinction: capital‑A Art probably survives, but AI threatens the commercial work that lets artists pay rent.

Low quality, “slop,” and enshittification

• Outside software, AI is associated with low effort, generic output that signals “I don’t care about you.”
• Complaints about AI‑generated spam, SEO sludge, bad customer support chatbots, and non‑deterministic answers in contexts that demand reliability.
• Some note inverse survivorship bias: people mainly notice the bad AI content, not the good.

Forced adoption, corporate behavior, and power

• Widespread resentment that AI is being pushed everywhere: into phones, apps, workplaces, and products without user demand.
• Workers report being required to use tools they dislike; some managers auto‑generate emails with obvious nonsense.
• AI is seen as centralizing power, accelerating “knowledge + capital” compounding, and furthering surveillance and manipulation.

Costs, infrastructure, and environment

• Anger over rising RAM/SSD and device prices attributed to datacenter build‑out and AI demand.
• Concerns about data centers’ electricity and water usage, and governments prioritizing them over local citizens.

Positive uses and optimism

• Several developers and power users report large productivity gains (e.g., 3–5× faster coding, easier research, better cold‑start for projects).
• Some compare AI to past disruptive tech bubbles (railroads, dot‑coms): overhyped but ultimately transformative.