Position: On the Societal Impact of Open Foundation Models
Authors: Sayash Kapoor, Rishi Bommasani, Kevin Klyman, Shayne Longpre, Ashwin Ramaswami, Peter Cihon, Aspen K Hopkins, Kevin Bankston, Stella Biderman, Miranda Bogen, Rumman Chowdhury, Alex Engler, Peter Henderson, Yacine Jernite, Seth Lazar, Stefano Maffulli, Alondra Nelson, Joelle Pineau, Aviya Skowron, Dawn Song, Victor Storchan, Daniel Zhang, Daniel E. Ho, Percy Liang, Arvind Narayanan
ICML 2024 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | Overall, our work supports a more grounded assessment of the societal impact of open foundation models by outlining what research is needed to empirically validate their theoretical benefits and risks. |
| Researcher Affiliation | Collaboration | 1Princeton University 2Stanford University 3Massachusetts Institute of Technology 4Georgetown University 5Git Hub 6Center for Democracy and Technology 7Eleuther AI 8Humane Intelligence 9Brookings Institution 10Hugging Face 11Australian National University 12Open Source Initiative 13Institute for Advanced Study 14Meta 15University of California, Berkeley 16Mozilla AI. |
| Pseudocode | No | The paper presents conceptual frameworks and analyses, not algorithms or pseudocode blocks. |
| Open Source Code | No | This paper is a position paper and does not describe a methodology for which open-source code would be provided by the authors. |
| Open Datasets | No | This is a position paper that analyzes existing research and concepts; it does not conduct new experiments that would involve training datasets. While it references other papers that use datasets (e.g., Table A1), it does not provide access information for datasets used in its own research. |
| Dataset Splits | No | The paper does not conduct empirical experiments or model training and therefore does not specify training, validation, or test dataset splits. |
| Hardware Specification | No | The paper is a conceptual position paper and does not describe experimental work that would require specific hardware specifications. |
| Software Dependencies | No | The paper is a conceptual position paper and does not describe experimental work that would require specific software dependencies for reproducibility. |
| Experiment Setup | No | The paper is a conceptual position paper and does not describe experimental work that would involve specific setup details like hyperparameters or training configurations. |