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Release Strategies and the Social Impacts of Language Models

Irene Solaiman, Miles Brundage, Jack Clark, Amanda Askell, Ariel Herbert-Voss, Jeff Wu, Alec Radford, Gretchen Krueger, Jong Wook Kim, Sarah Kreps, Miles McCain, Alex Newhouse, Jason Blazakis, Kris McGuffie, Jasmine Wang

TL;DR

This report discusses OpenAI's work related to the release of its GPT-2 language model and discusses staged release, which allows time between model releases to conduct risk and benefit analyses as model sizes increased.

Abstract

Large language models have a range of beneficial uses: they can assist in prose, poetry, and programming; analyze dataset biases; and more. However, their flexibility and generative capabilities also raise misuse concerns. This report discusses OpenAI's work related to the release of its GPT-2 language model. It discusses staged release, which allows time between model releases to conduct risk and benefit analyses as model sizes increased. It also discusses ongoing partnership-based research and provides recommendations for better coordination and responsible publication in AI.

Release Strategies and the Social Impacts of Language Models

TL;DR

This report discusses OpenAI's work related to the release of its GPT-2 language model and discusses staged release, which allows time between model releases to conduct risk and benefit analyses as model sizes increased.

Abstract

Large language models have a range of beneficial uses: they can assist in prose, poetry, and programming; analyze dataset biases; and more. However, their flexibility and generative capabilities also raise misuse concerns. This report discusses OpenAI's work related to the release of its GPT-2 language model. It discusses staged release, which allows time between model releases to conduct risk and benefit analyses as model sizes increased. It also discusses ongoing partnership-based research and provides recommendations for better coordination and responsible publication in AI.

Paper Structure

This paper contains 27 sections, 8 figures.

Table of Contents

  1. Staged Release
  2. Partnerships
  3. Engagement
  4. Social Impacts of Large Language Models
  5. Beneficial Use Potential
  6. Misuse: Actor Assessment
  7. Billion Parameter Model: Threat Landscape
  8. Detecting Synthetic Text
  9. Bias: Exploratory Research
  10. Future Trends in Language Models
  11. Recommendations for Publication Norms in AI
  12. Example:
  13. Example: Men
  14. Example: Women
  15. Methodology
  16. ...and 12 more sections

Figures (8)

  • Figure 1: RoBERTa-Large Transferred Model Accuracy
  • Figure 2: Detection Accuracy With Respect to the Text Length
  • Figure 3: Responses When Inputted "The victim": Female Categories
  • Figure 4: Responses When Inputted "Police describe the suspect as"
  • Figure 5: Comparing tf-idf for GPT-2 Fine-Tuned Models and Source Texts
  • ...and 3 more figures