Large Language Models as Games

If computers are dramatic experiences, Large Language Models (LLMs) are games. Consumer AI once served mainly as a feature within larger products, but LLMs and generative tools have created a market for AI as a service. Their conversational design fosters engagement as both tools and entertainment. Prompting has become an art, with users directing LLMs like actors in a co-created performance. This paper identifies five generative interaction types: collaboration, exploration, adversarial, narrative, and roleplaying. From these, four gameplay modes emerge: interactive prompting, playing games with LLMs, using LLMs as in-game agents, and generating games via LLMs. These modes reflect principles of game design—challenge, reward, strategy—embedded in LLM interactions. Whether used for productivity or play, prompting creates a feedback-rich, exploratory experience. This paper argues that LLM use inherently constitutes a form of generative play grounded in interactive storytelling.

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Publication Details

Journal
ScholarSpace (University of Hawaii at Manoa)
Published
2025-12-23
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
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article

Large Language Models as Games

Trevor Bihl
ScholarSpace (University of Hawaii at Manoa)
AI in Service Interactions
article

Large Language Models as Games

Trevor Bihl
article en

Abstract

If computers are dramatic experiences, Large Language Models (LLMs) are games. Consumer AI once served mainly as a feature within larger products, but LLMs and generative tools have created a market for AI as a service. Their conversational design fosters engagement as both tools and entertainment. Prompting has become an art, with users directing LLMs like actors in a co-created performance. This paper identifies five generative interaction types: collaboration, exploration, adversarial, narrative, and roleplaying. From these, four gameplay modes emerge: interactive prompting, playing games with LLMs, using LLMs as in-game agents, and generating games via LLMs. These modes reflect principles of game design—challenge, reward, strategy—embedded in LLM interactions. Whether used for productivity or play, prompting creates a feedback-rich, exploratory experience. This paper argues that LLM use inherently constitutes a form of generative play grounded in interactive storytelling.

ScholarSpace (University of Hawaii at Manoa)
Decent work and economic growth
Openalex Percentile: Top 18%
AI in Service Interactions
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Large Language Models as Games — Trevor Bihl · ScholarSpace (University of Hawaii at Manoa) (2025) | TGRS Research Map | TGRS