Sarah 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 SSRN

The 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 Forum

D&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 Nature

In 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 SSRN

D&S Affiliates Ifeoma Ajunwa, Kate Crawford, and Jason Schultz examine the effectiveness of the law as a check on worker surveillance, given recent technological innovations. This law review article focuses on popular trend... Read on SSRN

D&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 SSRN

Abstract: 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 SIGCAS

The 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 arXiv

D&S fellow Sorelle Friedler and her research colleagues investigate the ways that algorithms make decisions in all aspects of our lives and whether or not we can determine if these algorithms are biased, involve illegal dis... Read on arXiv.org