AI, machine learning algorithms are susceptible to biased data: Harmful stereotypes and inequalities influencing healthcare can create potentially damaging biases in the data on which artificial intelligence and machine learning algorithms are trained.

Subject

Injustice;
Machine learning;
Pain;
Algorithms;
Minority & ethnic groups;
Artificial intelligence

Location

United States--US; Ann Arbor Michigan

Company / organization

Name:

University of Wisconsin-Madison

NAICS:

611310

Title

AI, machine learning algorithms are susceptible to biased data: Harmful stereotypes and inequalities influencing healthcare can create potentially damaging biases in the data on which artificial intelligence and machine learning algorithms are trained.

Author

Slabodkin, Greg

Publication title

Health Data Management (Online); New York

Publication year

2019

Publication date

Aug 13, 2019

Publisher

SourceMedia dba Arizent

Place of publication

New York

Country of publication

United States

Publication subject

Computers--Computer Networks, Insurance

Source type

Trade Journal

Language of publication

English

Document type

News

ProQuest document ID

2284663964

Document URL

https://www.proquest.com/trade-journals/ai-machine-learning-algorithms-are-susceptible/docview/2284663964/se-2?accountid=208611

Last updated

2019-09-05

Database

ProQuest One Academic

AI, machine learning algorithms are susceptible to biased data: Harmful stereotypes and inequalities influencing healthcare can create potentially damaging biases in the data on which artificial intelligence and machine learning algorithms are trained.

Content area