Study: Consumers Actively Turned Off by AI

Original Article ↗ Hacker News Discussion ↗

Overall reaction to “AI”-branded products

  • Many commenters say “AI-powered” has become a negative signal: it implies cheapness, unreliability, or a cost-cutting move.
  • AI branding is seen as investor/marketing-driven rather than user-driven, similar to past buzzwords like “blockchain” or “information superhighway.”
  • Some note users care about outcomes, not tech labels; “AI” is like advertising a “30GB HDD” instead of “1000 songs in your pocket.”

Visible AI vs. Invisible ML Features

  • Strong distinction between:
    • Quiet, behind-the-scenes ML (photo search, classification, recommendations) that users often like or accept.
    • In-your-face “AI assistants” that users are pushed to interact with.
  • Several argue companies should stop marketing AI and just ship good features; people often like the function but dislike the AI label.

Customer Support, Chatbots, and UX

  • Widespread frustration with AI chatbots on websites, travel apps, and support lines.
  • Complaints: can’t actually perform actions, give circular or wrong answers, become upsell funnels, and act as barriers to reaching humans.
  • Many equate “AI” with “annoying chatbots and low-quality content.”

Quality, Trust, and “Hallucinations”

  • Errors, hallucinations, and mediocre output erode trust; branding errors as “hallucinations” is seen as spin.
  • Some report bad meeting transcripts and flawed features leading organizations to roll back AI tools.
  • Others report good experiences with speech-to-text and code assistants, emphasizing hardware/setup and expectations matter.

Cultural, Ethical, and Economic Concerns

  • Generative AI is associated with spam, SEO sludge, cheap art, and “slop content,” seen as “poisoning culture” and devaluing human creativity.
  • Fear that AI is mainly used to cut jobs, especially in customer service and creative work.
  • Some call the current wave part of broader “enshittification” and profit-at-all-costs dynamics.

Positive Use Cases and Design Preferences

  • Praised uses: coding assistants (Copilot, similar tools), summarization, pattern recognition, “boring” back-office or admin tasks, improved search/filtering.
  • Preferred pattern: AI augments existing UIs, does tedious work, remains optional, is fast, and doesn’t pretend to be a person.
  • Several advocate for “boring AI” — internal, task-focused, and not marketed as a headline feature.