[ARTICLE] This paper highlights the critical role of statistical methodology in the development and understanding of artificial intelligence (AI), emphasizing contributions to methodological development, study design, data quality assessment, and the integration of statistical aspects into AI education.

Co-authored by Adalbert Wilhelm (ESSEC Business School),  Sarah Friedrich, Gerd Antes, Sigrid Behr et al.

The research on and application of artificial intelligence (AI) has triggered a comprehensive scientific, economic, social and political discussion. Here we argue that statistics, as an interdisciplinary scientific field, plays a substantial role both for the theoretical and practical understanding of AI and for its future development. Statistics might even be considered a core element of AI. With its specialist knowledge of data evaluation, starting with the precise formulation of the research question and passing through a study design stage on to analysis and interpretation of the results, statistics is a natural partner for other disciplines in teaching, research and practice. This paper aims at highlighting the relevance of statistical methodology in the context of AI development. In particular, we discuss contributions of statistics to the field of artificial intelligence concerning methodological development, planning and design of studies, assessment of data quality and data collection, differentiation of causality and associations and assessment of uncertainty in results. Moreover, the paper also discusses the equally necessary and meaningful extensions of curricula in schools and universities to integrate statistical aspects into AI teaching.

[Please read the research paper here]