Automating Inequality

Author describes case studies on how inequality is being automated and targeted on certain groups of people. She describes three cases in United States where the new technologies we’re seeing absolutely have the potential to lower barriers, to integrate services, and to really act to make social service systems more efficient and more navigable, what I found in my seven years of reporting on the book is that what we’re actually doing is creating what I call a digital poorhouse, which is an invisible institution that profiles, polices, and punishes the poor when they come into contact with public services.

Focus: AI Ethics/Policy
Source: Open Transcripts
Readability: Intermediate
Type: Video with Transcript
Open Source: Yes
Keywords: N/A
Learn Tags: Bias Data Collection/Data Set Ethics Government AI and Machine Learning
Summary: A lecture given by Virginia Eubanks, associate professor of polticial science at the University of Albany and author of _Automating Inequality_, in which she discusses three cases where technology used in public policies is creating inequality: automated welfare system, electronic registry of unhoused persons, and statistical model used to predict which children are victims of abuse.