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Ethical and Social Risks of Harm from Language Models
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- Authors
- Laura Weidinger, John Mellor, Maribeth Rauh, Conor Griffin, Jonathan Uesato, et al.
- Venue
- Preprint, not yet peer-reviewed
- Published
- December 2021
- ID
- arXiv:2112.04359
Abstract
This paper aims to help structure the risk landscape associated with large-scale Language Models (LMs). In order to foster advances in responsible innovation, an in-depth understanding of the potential risks posed by these models is needed. A wide range of established and anticipated risks are analysed in detail, drawing on multidisciplinary expertise and literature from computer science, linguistics, and social sciences. We outline six specific risk areas: I. Discrimination, Exclusion and Toxicity, II. Information Hazards, III. Misinformation Harms, V. Malicious Uses, V. Human-Computer Interaction Harms, VI. Automation, Access, and Environmental Harms. The first area concerns the perpetuation of stereotypes, unfair discrimination, exclusionary norms, toxic language, and lower performance by social group for LMs. The second focuses on risks from private data leaks or LMs correctly inferring sensitive information. The third addresses risks arising from poor, false or misleading information including in sensitive domains, and knock-on risks such as the erosion of trust in shared information. The fourth considers risks from actors who try to use LMs to cause harm. The fifth focuses on risks specific to LLMs used to underpin conversational agents that interact with human users, including unsafe use, manipulation or deception. The sixth discusses the risk of environmental harm, job automation, and other challenges that may have a disparate effect on different social groups or communities. In total, we review 21 risks in-depth. We discuss the points of origin of different risks and point to potential mitigation approaches. Lastly, we discuss organisational responsibilities in implementing mitigations, and the role of collaboration and participation. We highlight directions for further research, particularly on expanding the toolkit for assessing and evaluating the outlined risks in LMs.
The authors' own abstract, copied from arxiv.org.
How to cite it
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Weidinger, L., Mellor, J., Rauh, M., Griffin, C., Uesato, J., et al. (2021). Ethical and Social Risks of Harm from Language Models. Preprint, not yet peer-reviewed. https://arxiv.org/abs/2112.04359
Weidinger, Laura, et al. "Ethical and Social Risks of Harm from Language Models." Preprint, not yet peer-reviewed, 2021, https://arxiv.org/abs/2112.04359.
@article{weidinger2021ethical,
title = {Ethical and Social Risks of Harm from Language Models},
author = {Laura Weidinger and John Mellor and Maribeth Rauh and Conor Griffin and Jonathan Uesato and others},
journal = {Preprint, not yet peer-reviewed},
year = {2021},
url = {https://arxiv.org/abs/2112.04359},
}What it is
A structured map of 21 risks from language models across six areas — discrimination, information hazards, misinformation, malicious use, human-computer interaction harms, and environmental and economic cost. Free on arXiv.
Why I recommend it
The best single reference if you need vocabulary for a specific harm rather than a general argument. Written by a lab, so read it as a lab's own framing.
Topics
Added Sep 19, 2026 · 0 opens
