Sound Research WIKINDX
Sound Research WIKINDX |
|
 |
|
Bender, E. M., Gebru, T., McMillan-Major, A., & Shmitchell, S. 2021 On the dangers of stochastic parrots: Can language models be too big? 🦜. Paper presented at Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency. Added by: Mark Grimshaw-Aagaard (5/5/26, 4:48 AM) Last edited by: Mark Grimshaw-Aagaard (5/5/26, 4:50 AM) |
 |
| Resource type: Proceedings Article Language: en: English Peer reviewed Published DOI: 10.1145/3442188.3445922 ID no. (ISBN etc.): 9781450383097 BibTeX citation key: Bender2021 Email resource to friend View all bibliographic details  |
Categories: General Keywords: Artificial creativity, Artificial Intelligence Creators: Bender, Gebru, McMillan-Major, Shmitchell Collection: Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency |
Views: 54/54
|
| Abstract |
|
The past 3 years of work in NLP have been characterized by the development and deployment of ever larger language models, especially for English. BERT, its variants, GPT-2/3, and others, most recently Switch-C, have pushed the boundaries of the possible both through architectural innovations and through sheer size. Using these pretrained models and the methodology of fine-tuning them for specific tasks, researchers have extended the state of the art on a wide array of tasks as measured by leaderboards on specific benchmarks for English. In this paper, we take a step back and ask: How big is too big? What are the possible risks associated with this technology and what paths are available for mitigating those risks? We provide recommendations including weighing the environmental and financial costs first, investing resources into curating and carefully documenting datasets rather than ingesting everything on the web, carrying out pre-development exercises evaluating how the planned approach fits into research and development goals and supports stakeholder values, and encouraging research directions beyond ever larger language models.
Added by: Mark Grimshaw-Aagaard Last edited by: Mark Grimshaw-Aagaard |