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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Academic Article
Taylor & Francis OnlineData-driven technologies represent a technological rationality that renders our experiences in the world as distant, unfamiliar, and perhaps even unreliable when compared to the knowledge about the world that our technological systems present us with. Read on Taylor & Francis OnlineFebruary 2021 -
Academic Article
Institute of Network CulturesThis essay conceptualizes study the imbrication as a maxim in researching the role of datasets in producing, distributing, and consuming knowledge. Read on Institute of Network CulturesJanuary 2021 -
Academic Article
ACM FAT* 2020A study of AI in clinical care use, with a particular focus on the sepsis detection system, "Sepsis Watch." Read on ACM FAT* 2020January 2020 -
Academic Article
NatureStudying AI agents as if they are animate moves responsibility for the behavior of machines away from their designers, thereby undermining efforts to establish a professional ethics code for AI practitioners. Read on NatureOctober 2019 -
Academic Article
Engaging Science, Technology, and SocietyIn this article, Research Lead Madeleine Clare Elish investigates who bears the responsibility when an automated system fails. "Just as the crumple zone in a car is designed to absorb the force of impact in a crash, the human ... Read on Engaging Science, Technology, and SocietyMay 2019 -
Academic Article
Criminal Justice and BehaviorData & Society Fellow Cynthia Conti-Cook and co-authors assess the bias involved in risk assessment tools. "In the top layer, we identify challenges to fairness within the risk-assessment models themselves. We explain type... Read on Criminal Justice and BehaviorNovember 2018 -
Academic Article
Fordham Law ReviewThis paper is a response to calls for explainable machines by Data & Society Postdoctoral Scholar Andrew Selbst and Affiliate Solon Barocas. "We argue that calls for explainable machines have failed to recognize the connec... Read on Fordham Law ReviewMarch 2018 -
Academic Article
SSRNSarah Bird, Fernando Diaz, Hanna Wallach, with D&S affiliates Solon Barocas and Kate Crawford, wrote this analysis about implications in autonomous experimentation in AI. In the field of computer science, large-scale exp... Read on SSRNOctober 2016 -
Academic Article
Florida Law Review ForumThe mythology surrounding “big data” rests on the notion that technical systems can increase efficiency and decrease bias. Such “neutral” systems are supposedly good for implementing legal logic because, like these systems, law... Read on Florida Law Review ForumAugust 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