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Clustering the AI Landscape: Navigating Global Insights from Leading AI Indexes

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Cita

This study develops a scorecard validation model for evaluating key Artificial Intelligence (AI) indexes, aiming to provide a comprehensive framework for assessing the multifaceted nature of AI development. Focusing on four significant AI indexes and one AI report from 2021 to 2023, the research employs both expert judgment and advanced text mining techniques, including k-means clustering. This dual approach facilitates a detailed examination of AI indexes, highlighting their strengths, weaknesses, and overall market comprehensiveness. The findings contribute to understanding the AI sector’s evolution, offering critical insights for policy formulation and strategic decision-making in AI. Acknowledging the inherent subjectivity in the evaluation process and potential data biases, the paper suggests future research avenues, including cross-sectoral and regional analyses of AI trends and a deeper exploration of ethical considerations in AI. This study serves as a valuable resource for stakeholders navigating the complex AI landscape, providing a structured method for comparing and understanding AI advancements.

eISSN:
2285-388X
Lingua:
Inglese
Frequenza di pubblicazione:
2 volte all'anno
Argomenti della rivista:
Business and Economics, Business Management, other, Mathematics and Statistics for Economists, Statitistics, Econometrics