Library
Use our library to explore Data & Society's original empirical research and read our expert commentary. Sort by media type, or select one or more topic categories to begin browsing.
Publisher
Title
Date
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blog post
CultureDigitally.orgD&S Advisor Tarleton Gillespie responds to Gizmodo's recent piece alleging bias in Facebook's Trending Topics list. He argues that information algorithms like the ones used to identify “trends” on Facebook do not work alone... Read on CultureDigitally.orgMay 2016 -
Academic Article
NatureSorelle FriedlerPaul RaccugliaKatherine C. ElbertPhilip D.F. AdlerCasey FalkMalia B. WennyAurelio MolloMatthias ZellerD&S fellow Sorelle Friedler's latest research appears in Nature. She and her team document their creation of a machine-learning algorithm that accurately predicts new ways to make crystals. The team trained the algorithm u... Read on NatureMay 2016 -
blog post
London School of Economics blogD&S Affiliate Seeta Peña Gangadharan discusses how automated systems have transformed the ways in which our data is processed, analyzed, and used by companies that are not held to account for the potential uses of data that... Read on London School of Economics blogApril 2016 -
Academic Article
SSRNIn this Working Paper from We Robot 2016, D&S Researcher Madeleine Elish employs the concept of “moral crumple zones” within human-machine systems as a lens through which to think about the limitations of current frameworks... Read on SSRNMarch 2016 -
Academic Article
SSRND&S Fellow Sorelle Friedler and D&S Affiliate Ifeoma Ajunwa argue in this essay that well settled legal doctrines that prohibit discrimination against job applicants on the basis of sex or race dictate an examination of... Read on SSRNMarch 2016 -
Academic Article
SIGCASAbstract: What claims are made about the objectivity of machines versus that of human experts? Whereas most current debates focus on the growing impact of algorithms in the age of Big Data, I argue here in favor of taking a lon... Read on SIGCASMarch 2016 -
Academic Article
arXivSuresh VenkatasubramanianSorelle FriedlerPhilip D.F. AdlerCasey FalkGabriel RybeckCarlos E ScheideggerBrandon SmithThe ubiquity and power of machine learning models in society to determine and control an increasing number of real-world decisions presents a challenge. D&S fellow Sorelle Friedler and a team of researchers have developed ... Read on arXivFebruary 2016 -
Longform
SlateD&S Researcher Madeleine Clare Elish considers the possibility of a full-on replacement of humans by robots. She argues that this scenario is nowhere near as close as we have been led to believe. Though algorithms can do an... Read on SlateFebruary 2016 -
op-ed
New York TimesIn this op-ed, Data & Society fellow Seeta Peña Gangadharan addresses the question "Can Crime Be Ethically Predicted?" and argues that bias is inherent in the technical systems used in predictive policing leading to "fundam... Read on New York TimesNovember 2015 -
Resource
Data & SocietyPredictive policing refers to the use of analytical techniques to make statistical predictions about potential criminal activity. The basic underlying assumption of predictive policing is that crime is not randomly distributed ... Read moreOctober 2015