Taxonomy of Risks posed by Language Models

Google DeepMind (United Kingdom) · California Institute of Technology · +2 more institutions

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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

578
total citations
FWCI
50.47
Percentile
100%
References
70
Citations per year

Authors

23

Topics & keywords

Keywords
  • Misinformation
  • Taxonomy (biology)
  • Harm
  • Risk analysis (engineering)
  • Futures studies
  • Computer science
  • Risk management
  • Data science
UN Sustainable Development Goals
  • Reduced inequalities
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