Big Data S Threat To Liberty

Big Data permeates all aspects of modern life, and while there is no shortage of potential benefits resulting from this, author Henrik Skaug Sætra argues that we must also understand the threats Big Data poses to liberty. The issues discussed in Big Data’s Threat to Liberty: Surveillance, Nudging, and the Curation of Information are related to how we are constantly under surveillance. Data is gathered from our homes, our cars, our smartphones, various devices around the house, and public sources such as facial recognition enabled camera surveillance and various websites and social networks. Furthermore, the information gathered is used to influence our actions. Detailed personality profiles are utilized in order to make us purchase products and services, or pay our taxes, through tailor-made nudges aimed at irrational and subconscious mechanisms, and delivered with a level of precision only possible with Big Data-driven algorithmic curation of data. Finally, the information we receive through various media is curated by algorithms, and even people are curated in order to satisfy our desires. By providing us with what the algorithm believes we want, we are spared from the exposure of unpleasant information, and even unpleasant people. The ideological landscapes we traverse are thus characterized by conformity, and a concomitant tyranny of popular opinion becomes ever more coercive as this occurs. The question is: How does being constantly watched, manipulated, and having our world-views shaped as just described affect our freedom? In this book it is argued that Big Data’s threat to individual liberty is routinely misunderstood and underappreciated due to (a) vagueness resulting from the concept of liberty being used without it being defined, or (b) the use of definitions based on flawed understandings of what liberty is. In this new and unique contribution to the ethics of Big Data and artificial intelligence, both these challenges are thoroughly addressed. Explanation of key Big Data–related technologies and how they affect modern society, including explanation of surveillance technologies and nudging algorithms, and how Big Data, Machine Learning, and Artificial Intelligence algorithms are used to tailor and mold opinion Conceptualization of the term liberty, making the concept tangible, as a clear understanding of various forms of liberty enables a proper debate about the effects of technology on liberty, and a debate about what sort of liberty we value A thorough technical explanation of how Big Data influences individuals by way of surveillance that allows for detailed personality profiles, nudging, and the algorithmic curation of information

This incisive book presents a critical evaluation of fintech, the use of technology to provide financial services. While fintech has been hailed as a game changer and a disruptor, Imad Moosa illustrates critical similarities between the present popularity of fintech and the dot-com hype of the early 2000s.

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.

What is artificial intelligence? What are the Sustainable Development Goals (SDGs)? How does AI affect the SDGs? Artificial Intelligence has a real impact on our lives and on our environment, and the Sustainable Development Goals enable us to evaluate these impacts in a systematic manner. This book shows that doing so requires us to understand the context of AI – the infrastructure it is built on, who develops it, who owns it, who has access to it, who uses it, and what it is used for – rather than relying on an isolationist theory of technology. By doing so, we can analyze not only the direct effects of AI on sustainability, but also the indirect – or second-order – effects. AI for the Sustainable Development Goals shows how AI potentially affects all SDGs – both positively and negatively.

Security studies, also known as international security studies, is an academic subfield within the wider discipline of international relations that examines organized violence, military conflict, and national security. Meant to serve as an introduction to the field of security studies, Contextualizing Security is a collection of original essays, primary source lectures, and previously published material in the overlapping fields of security studies, political science, sociology, journalism, and philosophy. It offers both graduate and undergraduate students a grasp on both foundational issues and more contemporary debates in security studies. Nineteen chapters cover security studies in the context of homeland security and liberty, U.S. foreign policy, lessons from the Cold War, science and technology policy, drones, cybersecurity, the War on Terror, migration, study-abroad programs, the surveillance state, Africa, and China. CONTRIBUTORS: Amelia Ayers, James E. Baker, Roy D. Blunt, Mark Boulton, Naji Bsisu, Robert E. Burnett, Daniel Egbe, Laila Farooq, Lisa Fein, Anna Holyan, Jeh C. Johnson, Richard Ledgett, David L. McDermott, James McRae, Amanda Murdie, Bernie Sanders, Jeremy Scahill, Kristan Stoddart, Jeremy Brooke Straughn, J. R. Swanegan, and Kali Wright-Smith

This book examines the influence of key films on public understanding of big data and the algorithmic systems that structure our digitally mediated lives. From star-powered blockbusters to civic-minded documentaries positioned to facilitate weighty debates about artificial intelligence, these texts frame our discourse and mediate our relationship to technology. Above all, they impact society’s abilities to regulate AI and navigate big tech’s political and economic maneuvers to achieve market dominance and regulatory capture. Foregrounding data politics with close readings of key films like Moneyball, Minority Report, The Social Dilemma, and Coded Bias, Gerald Sim reveals compelling ways in which films and tech industry–adjacent media define apprehension of AI. With the mid-2010s techlash in danger of fizzling out, Screening Big Data explores the relationship between this resistance and cultural infrastructure while highlighting the urgent need to refocus attention onto how technocentric media occupy the public imagination. This book will interest students and scholars of film and media studies, digital culture, critical data studies, and technopolitics.

Data at the Boundaries of European Law represents an original and engaged piece of scholarship in an important and fast developing field of policy and research. Beyond, and including, the most recent major new pieces of EU legislation-the Data Governance Act, together with the Data Act and the AI Act still going through the legislative process-this book draws attention to the substance of a number of core themes of the relationship between law and the digital world that are still somewhat hidden. These themes include the mimetic regulatory trajectories in and around the GDPR, transparency, ownership, and accountability, as well as the translation of all of these into core areas of public law such as criminal law, migration law, and intellectual property law. As a result, this book occupies a distinctive place in the debate on digital law that goes beyond the various silos of knowledge of particular legal disciplines. The issues addressed in this book are of interest to a global readership. They grapple with a number of the difficult themes of our times as applied to private and public actors and their (future) regulation in a manner that is relevant not just in Europe but worldwide.

Application of Big Data for National Security provides users with state-of-the-art concepts, methods, and technologies for Big Data analytics in the fight against terrorism and crime, including a wide range of case studies and application scenarios. This book combines expertise from an international team of experts in law enforcement, national security, and law, as well as computer sciences, criminology, linguistics, and psychology, creating a unique cross-disciplinary collection of knowledge and insights into this increasingly global issue. The strategic frameworks and critical factors presented in Application of Big Data for National Security consider technical, legal, ethical, and societal impacts, but also practical considerations of Big Data system design and deployment, illustrating how data and security concerns intersect. In identifying current and future technical and operational challenges it supports law enforcement and government agencies in their operational, tactical and strategic decisions when employing Big Data for national security Contextualizes the Big Data concept and how it relates to national security and crime detection and prevention Presents strategic approaches for the design, adoption, and deployment of Big Data technologies in preventing terrorism and reducing crime Includes a series of case studies and scenarios to demonstrate the application of Big Data in a national security context Indicates future directions for Big Data as an enabler of advanced crime prevention and detection