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

TL;DR

This paper explores the fundamental nature, purpose, and risks of data science, emphasizing its role as a research paradigm with profound implications and uncertainties beyond traditional science.

Contribution

It introduces an initial axiology of data science, defining its core features, potential benefits, risks, and open challenges to guide future understanding and development.

Findings

Data science is a research paradigm with vast scope and power.

It involves inherent uncertainties and risks due to its inscrutability.

Data science will significantly impact our understanding of the world.

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.