Open Source · Orchestration
llm-lobbyist
Code for the paper: "Large Language Models as Corporate Lobbyists" (2023).
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From the listing
About llm-lobbyist
This repository contains the code and experiments for the 2023 paper 'Large Language Models as Corporate Lobbyists'. It implements a framework that uses LLMs to simulate lobbying strategies and policy influence. The project is implemented in Jupyter Notebooks and is intended for research reproducibility.
Best for
Researchers studying AI ethics, computational social science, or the intersection of LLMs and policy influence
Use cases
- Reproducing the paper's lobbying simulation experiments
- Exploring how LLMs can generate persuasive policy arguments
- Studying the ethical implications of AI-driven lobbying
Notes
174 stars on GitHub. Last updated 2023-01-13.
Pros
- Open source and fully reproducible research code
- Novel application of LLMs to a real-world policy domain
- Well-documented with the accompanying paper
Cons
- Not designed for production or real-world deployment
- Requires familiarity with the paper and its methodology
- Limited to the specific lobbying scenario described in the paper
Key facts
What we have checked
- GitHub stars
- 174
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Sources
Where this comes from
- github api via nightly crawl, recovered from git history e908f0e3f60ee9a6a9776accb9286b434cdbaebcRegistry
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Changelog
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