Dealing With Semantic Inconsistencies in AI Governance

Abstract

In the rapidly evolving field of matching Law and Artificial Intelligence (AI), semantic inconsistencies are a major challenge for effective governance. Semantic inconsistencies arise when the terminology and definitions used in regulatory frameworks diverge from their practical applications and technological realities, leading to misunderstandings, misapplications, and inefficiencies. This chapter explores the nature of semantic inconsistencies in AI governance, including divergent definitions, evolving technological concepts, and ambiguous ethical and legal standards. It examines the implications of these inconsistencies such as regulatory inefficiencies, misalignment with technological realities, conflicts between jurisdictions, and erosion of public trust. To address these challenges, the chapter proposes strategies including establishing standardized definitions, updating regulatory frameworks, promoting international collaboration, enhancing transparency and communication, and incorporating flexibility in regulations.

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