A Framework for Automated Measurement of Responsible AI Harms in Generative AI Applications
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Abstract (arXiv)
We present a framework for the automated measurement of responsible AI (RAI) metrics for large language models (LLMs) and associated products and services. Our framework for automatically measuring harms from LLMs builds on existing technical and sociotechnical expertise and leverages the capabilities of state-of-the-art LLMs, such as GPT-4. We use this framework to run through several case studies investigating how different LLMs may violate a range of RAI-related principles. The framework may be employed alongside domain-specific sociotechnical expertise to create measurements for new harm areas in the future. By implementing this framework, we aim to enable more advanced harm measurement efforts and further the responsible use of LLMs.
Key facts. Cited by 12 papers in the map (data through 14 Oct 2026). Builds on 3 of its 4 references that are in the map. First posted on arXiv 26 Oct 2023.
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3 of 4 references.
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Citing papers per year: 2023: 1; 2024: 6; 2025: 4; 2026: 1.
12 papers.
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- 2026Bounded Minds, Generative Machines: Envisioning Conversational AI that Works with Human Heuristics and Reduces Bias Riskcited by 1
- 2026Bounded Minds, Generative Machines: Envisioning Conversational AI that Works with Human Heuristics and Reduces Bias Risk19 Jan 2026
- 2025Understanding and Meeting Practitioner Needs When Measuring Representational Harms Caused by LLM-Based Systems4 Jun 2025
- 2025Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs29 May 2025
- 2025Phi-4-reasoning Technical Report30 Apr 2025
- 2025Toward an Evaluation Science for Generative AI Systems7 Mar 2025
- 2024Phi-4 Technical Report12 Dec 2024
- 2024A Framework for Evaluating LLMs Under Task Indeterminacy21 Nov 2024
- 2024Phi-3 Safety Post-Training: Aligning Language Models with a "Break-Fix" Cycle18 Jul 2024
- 2024Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone22 Apr 2024
- 2024Are Large Language Models Reliable Argument Quality Annotators?15 Apr 2024
- 2024A Multi-Aspect Framework for Counter Narrative Evaluation using Large Language Models18 Feb 2024
- 2023Orca 2: Teaching Small Language Models How to Reason18 Nov 2023