Advances in Data Analysis and Classification ( IF 1.6 ) Pub Date : 2021-08-06 , DOI: 10.1007/s11634-021-00455-6 Sarah Friedrich 1 , Tim Friede 1 , Gerd Antes 2 , Harald Binder 2 , Sigrid Behr 3 , Werner Brannath 4 , Florian Dumpert 5 , Katja Ickstadt 6 , Markus Pauly 6 , Hans A. Kestler 7 , Johannes Lederer 8 , Heinz Leitgöb 9 , Ansgar Steland 10 , Adalbert Wilhelm 11
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.
中文翻译:
统计在人工智能中是否有作用?
人工智能(AI)的研究和应用引发了一场全面的科学、经济、社会和政治讨论。在这里,我们认为统计学作为一个跨学科的科学领域,对于人工智能的理论和实践理解及其未来发展都发挥着重要作用。统计数据甚至可能被视为人工智能的核心要素。凭借其在数据评估方面的专业知识,从研究问题的精确制定开始,经过研究设计阶段到结果的分析和解释,统计学是其他学科在教学、研究和实践中的天然合作伙伴。本文旨在强调统计方法在人工智能发展背景下的相关性。特别是,我们讨论统计学对人工智能领域的贡献,涉及方法论开发、研究的规划和设计、数据质量和数据收集的评估、因果关系和关联的区分以及结果不确定性的评估。此外,本文还讨论了在学校和大学中对课程进行同样必要和有意义的扩展,以将统计方面纳入人工智能教学。