A Comparison of Machine Learning Applications Across Professional Sectors

10 Pages Posted: 21 May 2018

See all articles by Gabriel Bailey

Gabriel Bailey

University of Texas at Austin - School of Information

Allison Joffrion

University of Texas at Austin - School of Information

Megan Pearson

University of Texas at Austin - School of Information

Date Written: May 5, 2018

Abstract

Outside of the technology world, there is a great deal of confusion surrounding artificial intelligence and its related concepts. The terminology can be confusing and often prevents the general public from engaging with the conversation about its impact and implications in a substantial way. This review will cover the uses of machine learning in the financial, health care, and advertising industries in order to shed light on its various applications in an accessible way. By synthesizing the literature associated with each sector's uses of machine learning, we will contribute to the conversation in a way that seeks to clarify an often mythologized subject in a way that can be understood by anyone who wishes to engage with the larger conversation about the role, scope, and ethics of machine learning in the future.

Keywords: machine learning, applied machine learning, computational advertising, finance, healthcare

Suggested Citation

Bailey, Gabriel and Joffrion, Allison and Pearson, Megan, A Comparison of Machine Learning Applications Across Professional Sectors (May 5, 2018). Available at SSRN: https://ssrn.com/abstract=3174123 or http://dx.doi.org/10.2139/ssrn.3174123

Gabriel Bailey

University of Texas at Austin - School of Information ( email )

Austin, TX
United States

Allison Joffrion (Contact Author)

University of Texas at Austin - School of Information ( email )

Austin, TX
United States

Megan Pearson

University of Texas at Austin - School of Information ( email )

Austin, TX
United States

Here is the Coronavirus
related research on SSRN

Paper statistics

Downloads
78
Abstract Views
250
rank
343,838
PlumX Metrics