Compute gaming wins and losses.

Compute gaming wins and losses. is a detailed work activity in O*NET — a concrete unit of work shared across 3 occupations and seen in 3 occupation-specific tasks. It rolls up into the broader work activity Calculate financial data. in Estimating the Quantifiable Characteristics of Products, Events, or Information .

Detailed work activities are the most granular shared layer in O*NET's work-activity hierarchy (Generalized → Intermediate → Detailed → occupation-specific task). The figures below describe how this activity shows up across the economy and what independent studies measure about AI and this kind of work — not a prediction that the work will be automated.

AI exposure

Of the 3 tasks under this activity that the OpenAI / Eloundou “GPTs are GPTs” study rated, 3 (100%) are flagged as directly exposed to language models (E1) or exposed via model-powered tools (E2).

Exposure estimates overlap with model capabilities — whether a model could speed the task up — not whether the work will be done by software. Observed AI use is augmentation and assistance today, not jobs replaced.

Member tasks

Occupation-specific tasks O*NET maps to this detailed work activity, most important first.

• Calculate the value of chips won or lost by players. · Gambling Change Persons and Booth Cashiers · importance 4.8 · direct LLM exposure
• Compute amounts of players' wins or losses, or scan winning tickets presented by patrons to calculate the amount of money won. · Gambling Dealers · importance 4.6 · direct LLM exposure
• Compute and verify amounts won or lost, paying out winnings or referring patrons to workers, such as gaming cashiers, so that winnings can be collected. · Gambling and Sports Book Writers and Runners · importance 4.3 · exposure with tools

Occupations that perform this

• Gambling Change Persons and Booth Cashiers
• Gambling Dealers
• Gambling and Sports Book Writers and Runners

Sources for this page

Every figure above traces to a named public dataset and the exact release below — not hand-written opinion. See the full methodology for what each measure does and does not mean.

• O*NET 30.3 U.S. Department of Labor / National Center for O*NET Development
• “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130 OpenAI / academic

Data compiled June 2, 2026. Figures are estimates, not advice.

@misc{singulariki-compute-gaming-wins-and-losses,
  title  = {Compute gaming wins and losses.},
  author = {{Singulariki}},
  year   = {2026},
  note   = {O*NET 30.3; “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130. Accessed June 7, 2026},
  url    = {https://singulariki.com/detailed-activities/compute-gaming-wins-and-losses}
}