Against generalisation: Data-driven decisions need context to be human-compatible-Reference-Cited by-同舟云学术

Against generalisation: Data-driven decisions need context to be human-compatible

Published:2021-11-26 Issue:4 Volume:38 Page:162-169
ISSN:0266-3821
Container-title:Business Information Review
language:en
Short-container-title:Business Information Review

Author:

Richardson Sharon¹^ORCID

Affiliation:

1. University of Zürich, Switzerland

Abstract

During the past two decades, there have been a number of breakthroughs in the fields of data science and artificial intelligence, made possible by advanced machine learning algorithms trained through access to massive volumes of data. However, their adoption and use in real-world applications remains a challenge. This paper posits that a key limitation in making AI applicable has been a failure to modernise the theoretical frameworks needed to evaluate and adopt outcomes. Such a need was anticipated with the arrival of the digital computer in the 1950s but has remained unrealised. This paper reviews how the field of data science emerged and led to rapid breakthroughs in algorithms underpinning research into artificial intelligence. It then discusses the contextual framework now needed to advance the use of AI in real-world decisions that impact human lives and livelihoods.

Publisher

SAGE Publications

Subject

Economics, Econometrics and Finance (miscellaneous),Business, Management and Accounting (miscellaneous),Business and International Management

Link

http://journals.sagepub.com/doi/pdf/10.1177/02663821211061986

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