Stable Menus of Public Goods: AI-Enabled Progress

Sara Fish
6/15/2026
cs.GTcs.AIcs.CY

No official code found. Best implementation: sara-fish/stable_menus_ai_enabled_progress (0 stars, MIT, last commit 2026-06-01).

Abstract

Using an open problem from the EC 2025 paper "Stable Menus of Public Goods" as a testbed, we conduct experiments to understand the effectiveness of different AI-for-EconCS research workflows. Specifically, we study three questions: Does providing human intuition in the prompt help? Does automated multi-turn interaction help? And, does an LLM outperform a first-year PhD student? Regarding the first two questions, we provide evidence for the following workflow suggestions: (1) prompting with human intuition can encourage the LLM to have better "taste", (2) multi-turn workflows help when the pipeline encourages "ambitious" steps. Regarding the third question, using an unpublished manuscript written by the paper's senior authors prior to collaborating with the first-year PhD student, we compare the effectiveness of the LLM with that of the first-year PhD student, and find that the LLM is slightly less effective.

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Code Implementations(1)

sara-fish/stable_menus_ai_enabled_progressCommunity64%
MIT

Code and data associated with the paper "Stable Menus of Public Goods: AI-Enabled Progress"

00Jun 1, 20264 months agoMIT

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Cite this paper

@article{fish2026stable,
  title  = {Stable Menus of Public Goods: AI-Enabled Progress},
  author = {Sara Fish},
  year   = {2026},
  eprint = {2606.16989},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2606.16989v1}
}

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