Bombarding gamblers with offers greatly increases betting and gambling harm

Original Article ↗ Hacker News Discussion ↗

Industry incentives and targeting of “whales”

  • Many see the findings as obvious: gambling firms aggressively target high‑spending “whales,” similar to pay‑to‑win freemium games.
  • Commenters note firms ban or limit successful or “smart” bettors while nurturing losing accounts, including via second‑hand account markets.
  • This is framed as a classic principal–agent and “tragedy of the commons” problem: any single ethical operator loses to more aggressive competitors.

Addiction, agency, and moral responsibility

  • Several explain that “just stop” misunderstands addiction; it’s viewed as an emotional‑regulation problem, not an information problem.
  • Others compare preying on gambling addicts to scamming vulnerable elderly people.
  • There’s debate whether addiction implies loss of capacity to choose, with some describing internal conflict over time (“I want to not want this”).
  • A minority voice claims gamblers are simply “stupid,” rejecting the addiction framing; others strongly disagree.

Regulation, legality, and advertising

  • Many argue legalization and rapid expansion (especially online and in sports) were major policy mistakes that should be rolled back.
  • Strong support for banning or strictly limiting gambling advertising, likening it to tobacco/alcohol controls and noting legal obstacles in the US.
  • Suggested measures:
    • Loss caps tied to an ID‑based “gambling license.”
    • Banning credit card use.
    • Restricting availability to physical venues (e.g., Vegas/reservations).
  • Some think such measures would effectively destroy current business models; several say that is desirable.

Promos, free bets, and user behavior

  • Multiple anecdotes of “free bet” or sign‑up bonus arbitrage; a few disciplined people claim significant profits, while others say they inevitably lost.
  • Consensus that offers are engineered to hook people into greater betting.

Comparisons and extensions

  • Gambling is repeatedly compared to big tobacco, alcohol, big tech algorithms, pharma, and environmental harms as examples of externalized damage.
  • Some argue gambling and prediction markets have no social benefit; others cite faster information aggregation as a minor upside.
  • A few worry similar manipulative “offer” dynamics will appear in AI products and other digital services.

Study design and evidence

  • One commenter questions the study’s causal claims; another clarifies that participants were randomly removed from mailing lists, countering that criticism.
  • Some express frustration that we need studies to prove something “obvious” before policy changes.