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<p>As AI-driven solutions become increasingly common, end users of those systems continue to lack transparency in understanding the AI system’s functionality leading to a lack of trust, and AI systems not reaching their full potential. Our research aims to address this research gap by developing a novel sample transparency card. This transparency card is grounded in key transparency requirements from the prominent AI legislation (the European Union’s (EU) AI Act), the international standards (national institute of standards and technology (NIST) and international organization for standardization (ISO)), and public transparency principles from 25 global organizations. The research follows a 2-phase research approach. First, we analyze the transparency requirements to gain a greater understanding of the legislative and organizational requirements. Second, based on transparency requirements, create common categories and develop a proposed sample transparency card. This research offers a novel contribution by developing a sample transparency card that can be seen by the AI end users and aligns with legislative acts and frameworks, promoting trust in AI systems.</p>

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Transparency requirements across AI legislative acts, frameworks and organizations: shaping a sample transparency card

  • 期刊论文

  • 发表日期：

    2025年4月22日

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  • Carter Cousineau,
  • Nadja Herger,
  • Rozita Dara

摘要

As AI-driven solutions become increasingly common, end users of those systems continue to lack transparency in understanding the AI system’s functionality leading to a lack of trust, and AI systems not reaching their full potential. Our research aims to address this research gap by developing a novel sample transparency card. This transparency card is grounded in key transparency requirements from the prominent AI legislation (the European Union’s (EU) AI Act), the international standards (national institute of standards and technology (NIST) and international organization for standardization (ISO)), and public transparency principles from 25 global organizations. The research follows a 2-phase research approach. First, we analyze the transparency requirements to gain a greater understanding of the legislative and organizational requirements. Second, based on transparency requirements, create common categories and develop a proposed sample transparency card. This research offers a novel contribution by developing a sample transparency card that can be seen by the AI end users and aligns with legislative acts and frameworks, promoting trust in AI systems.