Ecosystem Graphs: Documenting the Foundation Model Supply Chain

Authors

  • Rishi Bommasani Stanford University
  • Dilara Soylu Stanford University
  • Thomas I. Liao Independent Researcher
  • Kathleen A. Creel Northeastern University
  • Percy Liang Stanford University

DOI:

https://doi.org/10.1609/aies.v7i1.31629

Abstract

Foundation models (e.g. GPT-4, Gemini, Llama 3) pervasively influence society, warranting greater understanding. While the models garner much attention, accurately characterizing their impact requires considering the broader sociotechnical ecosystem in which they are created and deployed. We propose Ecosystem Graphs as a documentation framework to centralize knowledge of this ecosystem. Ecosystem Graphs is composed of assets (datasets, models, applications) linked together by dependencies that indicate technical and social relationships. To supplement the graph structure, each asset is further enriched with fine-grained metadata, such as the model’s estimated training emissions or licensing guidelines. Since its release in March 2023, Ecosystem Graphs represents an ongoing effort to document 568 assets (112 datasets, 359 models, 97 applications) from 117 organizations. Ecosystem Graphs functions as a multifunctional resource: we discuss two major uses by the 2024 AI Index and the UK’s Competition and Markets Authority that demonstrate the value of Ecosystem Graphs.

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Published

2024-10-16

How to Cite

Bommasani, R., Soylu, D., Liao, T. I., Creel, K. A., & Liang, P. (2024). Ecosystem Graphs: Documenting the Foundation Model Supply Chain. Proceedings of the AAAI ACM Conference on AI, Ethics, and Society, 7(1), 196–209. https://doi.org/10.1609/aies.v7i1.31629