A data science axiology: the nature, value, and risks of data science
This foundational work addresses the need for a philosophical framework to guide the understanding and responsible development of data science across all disciplines, though it is speculative and incremental in nature.
The paper tackles the problem of defining and evaluating data science as a research paradigm, arguing it is not a science but a powerful tool for knowledge discovery with broad applications and risks, and presents an initial axiology to understand its benefits and challenges.
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.