AI Transparency: A Conceptual, Normative, and Practical Frame Analysis

Abstract

This study aims to dissect the normative discourse about artificial intelligence (AI) transparency using frame analysis. By employing a predominantly deductive, qualitative, and interpretative approach, the research leverages a qualitative frame analysis informed by a literature review on AI ethics and transparency. The study examines various AI ethical frameworks and regulations - China's Next Generation Artificial Intelligence Development Plan, the OECD's Recommendation of the Council on Artificial Intelligence, the White House’s Blueprint for an AI Bill of Rights, and the EU's Artificial Intelligence Act - to understand how transparency is framed, transparency's objects, the defined accountability, and the responsible entities for ensuring transparency in the production of AI information. The study highlights transparency as a core ethical principle for trustworthy AI, emphasising its importance in final outputs and throughout AI development and deployment stages for fostering public trust. The findings indicate variability in language, priorities, and approaches to transparency across different frameworks, influenced by their socio-political, economic, and cultural contexts. Despite encouraging transparency as an ethical principle, the study notes a need for concrete guidance for its practical implementation across different AI applications. This gap underscores the need for critical examination and improvement in governance to enhance transparency and accountability in AI development and deployment. The innovative methodological approach, combining qualitative frame analysis with a theory-driven codebook, offers a novel template for investigating key concepts and issues in AI ethics and governance.