# Language-based game theory in the age of artificial intelligence

arXiv: https://arxiv.org/abs/2403.08944 · HTML: https://mlsanity.com/paper/2403.08944/

## Key facts

- Cited by 10 papers in the map (data through 14 Oct 2026).
- Builds on 12 of its 79 references that are in the map.
- First posted on arXiv 13 Mar 2024.

## Builds on (most cited first, 12 of 12)

- [Sparks of Artificial General Intelligence: Early experiments with GPT-4](https://mlsanity.com/paper/2303.12712/) (2023)
- [Crowdsourcing a Word-Emotion Association Lexicon](https://mlsanity.com/paper/1308.6297/) (2013)
- [The Ethics of AI Ethics -- An Evaluation of Guidelines](https://mlsanity.com/paper/1903.03425/) (2019)
- [Explanations Can Reduce Overreliance on AI Systems During Decision-Making](https://mlsanity.com/paper/2212.06823/) (2022)
- [Discrimination in Online Ad Delivery](https://mlsanity.com/paper/1301.6822/) (2013)
- [Mathematical foundations of moral preferences](https://mlsanity.com/paper/2101.08193/) (2021)
- [The evolution of trust and trustworthiness](https://mlsanity.com/paper/2008.12948/) (2020)
- [The dual-process approach to human sociality: Meta-analytic evidence for a theory of internalized heuristics for self-preservation](https://mlsanity.com/paper/1906.09948/) (2019)
- [From Outcome-Based to Language-Based Preferences](https://mlsanity.com/paper/2206.07300/) (2022)
- [Doing good vs. avoiding bad in prosocial choice: A refined test and extension of the morality preference hypothesis](https://mlsanity.com/paper/1805.02903/) (2018)
- [Lying on networks: The role of structure and topology in promoting honesty](https://mlsanity.com/paper/2002.11034/) (2020)
- [Playing with words: Do people exploit loaded language to affect others' decisions for their own benefit?](https://mlsanity.com/paper/2106.03553/) (2021)

## Built on by (most cited first, 10 of 10)

- [FAIRGAME: a Framework for AI Agents Bias Recognition using Game Theory](https://mlsanity.com/paper/2504.14325/) (2025)
- [Strategic Communication and Language Bias in Multi-Agent LLM Coordination](https://mlsanity.com/paper/2508.00032/) (2025)
- [Social physics in the age of artificial intelligence](https://mlsanity.com/paper/2603.16900/) (2026)
- [Evolutionary mechanisms that promote cooperation may not promote social welfare](https://mlsanity.com/paper/2408.05373/) (2024)
- [GameTalk: Training LLMs for Strategic Conversation](https://mlsanity.com/paper/2601.16276/) (2026)
- [Cognitive networks highlight differences and similarities in the STEM mindsets of human and LLM-simulated trainees, experts and academics](https://mlsanity.com/paper/2502.19529/) (2025)
- [PPO-ACT: Proximal Policy Optimization with Adversarial Curriculum Transfer for Spatial Public Goods Games](https://mlsanity.com/paper/2505.04302/) (2025)
- [Game of Thought: Robust Information Seeking with Large Language Models Using Game Theory](https://mlsanity.com/paper/2602.01708/) (2026)
- [Human behaviour through a LENS: How Linguistic content triggers Emotions and Norms and determines Strategy choices](https://mlsanity.com/paper/2403.15293/) (2024)
- [Advanced Game-Theoretic Frameworks for Multi-Agent AI Challenges: A 2025 Outlook](https://mlsanity.com/paper/2506.17348/) (2025)

## Abstract (arXiv)

Understanding human behaviour in decision problems and strategic interactions has wide-ranging applications in economics, psychology, and artificial intelligence. Game theory offers a robust foundation for this understanding, based on the idea that individuals aim to maximize a utility function. However, the exact factors influencing strategy choices remain elusive. While traditional models try to explain human behaviour as a function of the outcomes of available actions, recent experimental research reveals that linguistic content significantly impacts decision-making, thus prompting a paradigm shift from outcome-based to language-based utility functions. This shift is more urgent than ever, given the advancement of generative AI, which has the potential to support humans in making critical decisions through language-based interactions. We propose sentiment analysis as a fundamental tool for this shift and take an initial step by analyzing 61 experimental instructions from the dictator game, an economic game capturing the balance between self-interest and the interest of others, which is at the core of many social interactions. Our meta-analysis shows that sentiment analysis can explain human behaviour beyond economic outcomes. We discuss future research directions. We hope this work sets the stage for a novel game theoretical approach that emphasizes the importance of language in human decisions.