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RAI Guidelines: Method for Generating Responsible AI Guidelines Grounded in Regulations and Usable by (Non-)Technical Roles

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arxiv 2307.15158 v2 pith:R222XJQU submitted 2023-07-27 cs.HC

classification cs.HC
keywords guidelinesresponsiblerolescatalogdevelopmentgroundedusableacross
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Many guidelines for responsible AI have been suggested to help AI practitioners in the development of ethical and responsible AI systems. However, these guidelines are often neither grounded in regulation nor usable by different roles, from developers to decision makers. To bridge this gap, we developed a four-step method to generate a list of responsible AI guidelines; these steps are: (1) manual coding of 17 papers on responsible AI; (2) compiling an initial catalog of responsible AI guidelines; (3) refining the catalog through interviews and expert panels; and (4) finalizing the catalog. To evaluate the resulting 22 guidelines, we incorporated them into an interactive tool and assessed them in a user study with 14 AI researchers, engineers, designers, and managers from a large technology company. Through interviews with these practitioners, we found that the guidelines were grounded in current regulations and usable across roles, encouraging self-reflection on ethical considerations at early stages of development. This significantly contributes to the concept of `Responsible AI by Design' -- a design-first approach that embeds responsible AI values throughout the development lifecycle and across various business roles.

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  1. PASTA: A Scalable Framework for Multi-Policy AI Compliance Evaluation

    cs.HC 2026-01 conditional novelty 6.0 of 10

    PASTA is a model-card-based LLM pipeline that evaluates an AI system against five regulations in minutes for about $3, with expert-aligned violation and relevance scores.

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