2021
DOI: 10.1007/s11634-021-00455-6
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Is there a role for statistics in artificial intelligence?

Abstract: 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 pa… Show more

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Cited by 41 publications
(29 citation statements)
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“…Clearly, we need additional efforts to promote statistical or data literacy at all levels of society. This issue has been raised by the DAGStat before, see Friedrich et al (2021). Equally important, we as the scientific community need to increase our efforts in making ourselves more understandable.…”
Section: Conclusion and Discussionmentioning
confidence: 99%
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“…Clearly, we need additional efforts to promote statistical or data literacy at all levels of society. This issue has been raised by the DAGStat before, see Friedrich et al (2021). Equally important, we as the scientific community need to increase our efforts in making ourselves more understandable.…”
Section: Conclusion and Discussionmentioning
confidence: 99%
“…As a statistician, the process of knowledge gain starts with a research question and continues with the acquisition of data, which then enters into the statistical model, see Figure 1 in Friedrich et al (2021) for an illustration. Data acquisition here might either refer to the design of an adequate experiment or to the use of so-called secondary data, which has been collected for a different purpose.…”
Section: Introductionmentioning
confidence: 99%
“…A growing number of researchers from various disciplines have expressed the view that many of the research questions are not too different in both disciplines ( 7 ). In fact, it may be argued that a large number of the differences in the analytical approach are only superficial and caused more by differences in terminology and scientific culture than from genuine dissimilarities ( 8 ). Differences may exist in terminology (not intentional) as they evolved in different scientific cultures with their legacy, nomenclature, notation, and philosophical perspectives ( 7 , 9 , 10 ).…”
Section: What Is the Difference Between Ai And Statistics?mentioning
confidence: 99%
“…ML is a technique that automates data analysis by resorting to the power of statistical tools [ 21 , 31 ] and has become a favoured framework to cope with big data by producing predictive models [ 24 ] across several fields [ 1 , 43 , 51 , 56 ]. However, those models are known for lacking interpretability and explainability [ 17 ] and this, in turn, reduces their accountability because issues relating to risk assessment and safe adoption are overlooked [ 39 ].…”
Section: Final Thoughtsmentioning
confidence: 99%