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Link to original content: https://doi.org/10.48550/arXiv.2307.10460
[2307.10460] A data science axiology: the nature, value, and risks of data science
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Computer Science > Artificial Intelligence

arXiv:2307.10460 (cs)
[Submitted on 19 Jul 2023 (v1), last revised 21 Jul 2023 (this version, v2)]

Title:A data science axiology: the nature, value, and risks of data science

Authors:Michael L. Brodie
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Abstract:Data science is not a science. It is a research paradigm with an unfathomed scope, scale, complexity, and power for knowledge discovery that is not otherwise possible and can be beyond human reasoning. It is changing our world practically and profoundly already widely deployed in tens of thousands of applications in every discipline in an AI Arms Race that, due to its inscrutability, can lead to unfathomed risks. This paper presents an axiology of data science, its purpose, nature, importance, risks, and value for problem solving, by exploring and evaluating its remarkable, definitive features. As data science is in its infancy, this initial, speculative axiology is intended to aid in understanding and defining data science to recognize its potential benefits, risks, and open research challenges. AI based data science is inherently about uncertainty that may be more realistic than our preference for the certainty of science. Data science will have impacts far beyond knowledge discovery and will take us into new ways of understanding the world.
Subjects: Artificial Intelligence (cs.AI); Databases (cs.DB); Machine Learning (cs.LG)
ACM classes: I.2; I.2.4; I.2.7; K.2
Cite as: arXiv:2307.10460 [cs.AI]
  (or arXiv:2307.10460v2 [cs.AI] for this version)
  https://doi.org/10.48550/arXiv.2307.10460

Submission history

From: Michael Brodie [view email]
[v1] Wed, 19 Jul 2023 21:12:04 UTC (979 KB)
[v2] Fri, 21 Jul 2023 21:32:12 UTC (979 KB)
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