Taxonomy of Risks posed by Language Models
Google DeepMind (United Kingdom) · California Institute of Technology · +2 more institutions
Abstract
Responsible innovation on large-scale Language Models (LMs) requires foresight into and in-depth understanding of the risks these models may pose. This paper develops a comprehensive taxonomy of ethical and social risks associated with LMs. We identify twenty-one risks, drawing on expertise and literature from computer science, linguistics, and the social sciences. We situate these risks in our taxonomy of six risk areas: I. Discrimination, Hate speech and Exclusion, II. Information Hazards, III. Misinformation Harms, IV. Malicious Uses, V. Human-Computer Interaction Harms, and VI. Environmental and Socioeconomic harms. For risks that have already been observed in LMs, the causal mechanism leading to harm,…
Citation impact
- FWCI
- 50.47
- Percentile
- 100%
- References
- 70
Authors
23Topics & keywords
- Misinformation
- Taxonomy (biology)
- Harm
- Risk analysis (engineering)
- Futures studies
- Computer science
- Risk management
- Data science
- Reduced inequalities