# Open-Sourcing Highly Capable Foundation Models: An Evaluation of Risks, Benefits, and Alternative Methods for Pursuing Open-Source Objectives

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/open-sourcing-highly-capable-foundation-models-an-evaluation-of-risks-benefits/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Elizabeth Seger,Noemi Dreksler,Richard Moulange,Emily Dardaman,Jonas Schuett,Kevin Wei,Christoph Winter,Mackenzie Arnold,Seán Ó hÉigeartaigh,Anton Korinek,Markus Anderljung,Ben Bucknall,Alan Chan,Eoghan Stafford,Leonie Koessler,Aviv Ovadya,Ben Garfinkel,Emma Bluemke,Michael Aird,Patrick Levermore,Julian Hazell,Abhishek Gupta |
| Citations | 26 |
| DOI | 10.2139/ssrn.4596436 |
| Fields | Computer Science,Decision Sciences,Social Sciences |
| Open Access | true |
| OA Status | green |
| OA URL | https://doi.org/10.2139/ssrn.4596436 |
| OpenAlex ID | https://openalex.org/W4387508266 |
| Type | preprint |
| Year | 2023 |

## Paper authors

- [Noemi Dreksler](https://scholariq.org/researchers/noemi-dreksler/)

## Paper journal

- [SSRN Electronic Journal](https://scholariq.org/journals/ssrn-electronic-journal/)

## Paper primary topic

- [Ethics and Social Impacts of AI](https://scholariq.org/topics/ethics-and-social-impacts-of-ai/)

## Paper topics

- [Ethics and Social Impacts of AI](https://scholariq.org/topics/ethics-and-social-impacts-of-ai/)
- [Explainable Artificial Intelligence (XAI)](https://scholariq.org/topics/explainable-artificial-intelligence-xai/)
- [Scientific Computing and Data Management](https://scholariq.org/topics/scientific-computing-and-data-management/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.