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Against Prediction : Profiling, Policing, and Punishing in an Actuarial Age by
From random security checks at airports to the use of risk assessment in sentencing, actuarial methods are being used more than ever to determine whom law enforcement officials target and punish. And with the exception of racial profiling on our highways and streets, most people favor these methods because they believe theyOCOre a more cost-effective way to fight crime. In "Against Prediction," Bernard E. Harcourt challenges this growing reliance on actuarial methods. These prediction tools, he demonstrates, may in fact "increase" the overall amount of crime in society, depending on the relative responsiveness of the profiled populations to heightened security. They may also aggravate the difficulties that minorities already have obtaining work, education, and a better quality of lifeOCothus perpetuating the pattern of criminal behavior. Ultimately, Harcourt shows how the perceived success of actuarial methods has begun to distort our very conception of just punishment and to obscure alternate visions of social order. In place of the actuarial, he proposes instead a turn to randomization in punishment and policing. The presumption, Harcourt concludes, should be "against prediction. ""
Algorithms of Oppression: How Search Engines Reinforce Racism by
A revealing look at how negative biases against women of color are embedded in search engine results and algorithms Run a Google search for "black girls"--what will you find? "Big Booty" and other sexually explicit terms are likely to come up as top search terms. But, if you type in "white girls," the results are radically different. The suggested porn sites and un-moderated discussions about "why black women are so sassy" or "why black women are so angry" presents a disturbing portrait of black womanhood in modern society. In Algorithms of Oppression, Safiya Umoja Noble challenges the idea that search engines like Google offer an equal playing field for all forms of ideas, identities, and activities. Data discrimination is a real social problem; Noble argues that the combination of private interests in promoting certain sites, along with the monopoly status of a relatively small number of Internet search engines, leads to a biased set of search algorithms that privilege whiteness and discriminate against people of color, specifically women of color. Through an analysis of textual and media searches as well as extensive research on paid online advertising, Noble exposes a culture of racism and sexism in the way discoverability is created online. As search engines and their related companies grow in importance--operating as a source for email, a major vehicle for primary and secondary school learning, and beyond--understanding and reversing these disquieting trends and discriminatory practices is of utmost importance. An original, surprising and, at times, disturbing account of bias on the internet, Algorithms of Oppression contributes to our understanding of how racism is created, maintained, and disseminated in the 21st century.
Automating Inequality: How High-tech Tools Profile, Police, and Punish the Poor by
WINNER:The2018 McGannon Center Book Prize and shortlisted for the Goddard Riverside Stephan Russo Book Prize for Social Justice The New York Times Book Review:"Riveting." Naomi Klein: "This book is downright scary." Ethan Zuckerman, MIT: "Should be required reading." Dorothy Roberts, author ofKilling the Black Body: "A must-read." Astra Taylor, author ofThe People's Platform:"The single most important book about technology you will read this year." Cory Doctorow: "Indispensable." A powerful investigative look at data-based discrimination--and how technology affects civil and human rights and economic equity The State of Indiana denies one million applications for healthcare, foodstamps and cash benefits in three years--because a new computer system interprets any mistake as "failure to cooperate." In Los Angeles, an algorithm calculates the comparative vulnerability of tens of thousands of homeless people in order to prioritize them for an inadequate pool of housing resources. In Pittsburgh, a child welfare agency uses a statistical model to try to predict which children might be future victims of abuse or neglect. Since the dawn of the digital age, decision-making in finance, employment, politics, health and human services has undergone revolutionary change. Today, automated systems--rather than humans--control which neighborhoods get policed, which families attain needed resources, and who is investigated for fraud. While we all live under this new regime of data, the most invasive and punitive systems are aimed at the poor. InAutomating Inequality,Virginia Eubanks systematically investigates the impacts of data mining, policy algorithms, and predictive risk models on poor and working-class people in America. The book is full of heart-wrenching and eye-opening stories, from a woman in Indiana whose benefits are literally cut off as she lays dying to a family in Pennsylvania in daily fear of losing their daughter because they fit a certain statistical profile. The U.S. has always used its most cutting-edge science and technology to contain, investigate, discipline and punish the destitute. Like the county poorhouse and scientific charity before them, digital tracking and automated decision-making hide poverty from the middle-class public and give the nation the ethical distance it needs to make inhumane choices: which families get food and which starve, who has housing and who remains homeless, and which families are broken up by the state. In theprocess, they weaken democracy and betray our most cherished national values. This deeply researched and passionate book could not be more timely.
Do Economists Make Markets?: On the Performativity of Economics by
Around the globe, economists affect markets by saying what markets are doing, what they should do, and what they will do. Increasingly, experimental economists are even designing real-world markets. But, despite these facts, economists are still largely thought of as scientists who merely observe markets from the outside, like astronomers look at the stars. Do Economists Make Markets? boldly challenges this view. It is the first book dedicated to the controversial question of whether economics is performative--of whether, in some cases, economics actually produces the phenomena it analyzes. The book's case studies--including financial derivatives markets, telecommunications-frequency auctions, and individual transferable quotas in fisheries--give substance to the notion of the performativity of economics in an accessible, nontechnical way. Some chapters defend the notion; others attack it vigorously. The book ends with an extended chapter in which Michel Callon, the idea's main formulator, reflects upon the debate and asks what it means to say economics is performative. The book's insights and strong claims about the ways economics is entangled with the markets it studies should interest--and provoke--economic sociologists, economists, and other social scientists. In addition to the editors and Callon, the contributors include Marie-France Garcia-Parpet, Francesco Guala, Emmanuel Didier, Philip Mirowski, Edward Nik-Khah, Petter Holm, Vincent-Antonin Lépinay, and Timothy Mitchell.
An Engine, Not a Camera: How Financial Models Shape Markets by
In An Engine, Not a Camera, Donald MacKenzie argues that the emergence of modern economic theories of finance affected financial markets in fundamental ways. These new, Nobel Prize-winning theories, based on elegant mathematical models of markets, were not simply external analyses but intrinsic parts of economic processes.Paraphrasing Milton Friedman, MacKenzie says that economic models are an engine of inquiry rather than a camera to reproduce empirical facts. More than that, the emergence of an authoritative theory of financial markets altered those markets fundamentally. For example, in 1970, there was almost no trading in financial derivatives such as "futures." By June of 2004, derivatives contracts totaling $273 trillion were outstanding worldwide. MacKenzie suggests that this growth could never have happened without the development of theories that gave derivatives legitimacy and explained their complexities. MacKenzie examines the role played by finance theory in the two most serious crises to hit the world's financial markets in recent years- the stock market crash of 1987 and the market turmoil that engulfed the hedge fund Long-Term Capital Management in 1998. He also looks at finance theory that is somewhat beyond the mainstream-chaos theorist Benoit Mandelbrot's model of "wild" randomness. MacKenzie's pioneering work in the social studies of finance will interest anyone who wants to understand how America's financial markets have grown into their current form.
Of Privacy and Power: The Transatlantic Struggle Over Freedom and Security by
How disputes over privacy and security have shaped the relationship between the European Union and the United States and what this means for the future We live in an interconnected world, where security problems like terrorism are spilling across borders, and globalized data networks and e-commerce platforms are reshaping the world economy. This means that states' jurisdictions and rule systems clash. How have they negotiated their differences over freedom and security? Of Privacy and Power investigates how the European Union and United States, the two major regulatory systems in world politics, have regulated privacy and security, and how their agreements and disputes have reshaped the transatlantic relationship. The transatlantic struggle over freedom and security has usually been depicted as a clash between a peace-loving European Union and a belligerent United States. Henry Farrell and Abraham Newman demonstrate how this misses the point. The real dispute was between two transnational coalitions--one favoring security, the other liberty--whose struggles have reshaped the politics of surveillance, e-commerce, and privacy rights. Looking at three large security debates in the period since 9/11, involving Passenger Name Record data, the SWIFT financial messaging controversy, and Edward Snowden's revelations, the authors examine how the powers of border-spanning coalitions have waxed and waned. Globalization has enabled new strategies of action, which security agencies, interior ministries, privacy NGOs, bureaucrats, and other actors exploit as circumstances dictate. The first serious study of how the politics of surveillance has been transformed, Of Privacy and Power offers a fresh view of the role of information and power in a world of economic interdependence.
The Rise of Big Data Policing: Surveillance, Race, and the Future of Law Enforcement by
Winner, 2018 Law & Legal Studies PROSE Award The consequences of big data and algorithm-driven policing and its impact on law enforcement In a high-tech command center in downtown Los Angeles, a digital map lights up with 911 calls, television monitors track breaking news stories, surveillance cameras sweep the streets, and rows of networked computers link analysts and police officers to a wealth of law enforcement intelligence. This is just a glimpse into a future where software predicts future crimes, algorithms generate virtual "most-wanted" lists, and databanks collect personal and biometric information. The Rise of Big Data Policing introduces the cutting-edge technology that is changing how the police do their jobs and shows why it is more important than ever that citizens understand the far-reaching consequences of big data surveillance as a law enforcement tool. Andrew Guthrie Ferguson reveals how these new technologies --viewed as race-neutral and objective--have been eagerly adopted by police departments hoping to distance themselves from claims of racial bias and unconstitutional practices. After a series of high-profile police shootings and federal investigations into systemic police misconduct, and in an era of law enforcement budget cutbacks, data-driven policing has been billed as a way to "turn the page" on racial bias. But behind the data are real people, and difficult questions remain about racial discrimination and the potential to distort constitutional protections. In this first book on big data policing, Ferguson offers an examination of how new technologies will alter the who, where, when and how we police. These new technologies also offer data-driven methods to improve police accountability and to remedy the underlying socio-economic risk factors that encourage crime. The Rise of Big Data Policing is a must read for anyone concerned with how technology will revolutionize law enforcement and its potential threat to the security, privacy, and constitutional rights of citizens. Read an excerpt and interview with Andrew Guthrie Ferguson in The Economist.
Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy by 
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