Zuboff vividly brings to life the consequences as surveillance capitalism advances from Silicon Valley into every economic sector. Vast wealth and power are accumulated in ominous new "behavioral futures markets," where predictions about our behavior are bought and sold, and the production of goods and services is subordinated to a new "means of behavioral modification." The threat has shifted from a totalitarian Big Brother state to a ubiquitous digital architecture: a "Big Other" operating in the interests of surveillance capital. Here is the crucible of an unprecedented form of power marked by extreme concentrations of knowledge and free from democratic oversight. Zuboff's comprehensive and moving analysis lays bare the threats to twenty-first century society: a controlled "hive" of total connection that seduces with promises of total certainty for maximum profit -- at the expense of democracy, freedom, and our human future.

Businesses face a new frontier of operational dilemmas, from algorithmic bias and data privacy concerns to the legal and ethical quandaries of AI-generated content. Questions of accountability for AI actions, intellectual property rights, and the threat of data laundering or AI hallucinations further complicate the landscape. Amid these challenges, enterprises are tasked with navigating a "pre-regulatory era," where global authorities are racing to establish policies and frameworks for a trustworthy and lawful AI ecosystem.   The AI Governance Handbook is a comprehensive guide tailored for stakeholders at the forefront of AI adoption--executives, managers, data scientists, engineers, and compliance professionals. This essential resource provides the knowledge, tools, and strategies to lead organizations through the complexities of implementing AI responsibly and effectively.

Artificial intelligence is being used, on a massive scale, to decide who gets hired, fired and promoted. Through whistleblower exclusives, leaked internal documents and astonishing real-world practices, journalist Hilke Schellmann reveals the secret rise of AI in the world of work. Testing them herself, she discovers that many algorithms making these high-stakes calculations do more harm than good, and traces their origins to troubling pseudoscientific ideas about people's 'true' essence. Interviewing experts, developers and ordinary workers, The Algorithm offers fascinating and alarming truths. From software analysing interviewees' facial expressions and tone of voice, to video games assessing their performance, to 'personality profiles' built from candidates' social media, almost all major employers use AI in recruitment.

Algorithms are now widely employed to make decisions that have increasingly far-reaching impacts on individuals and society as a whole ("algorithmic governance"), which could potentially lead to manipulation, biases, censorship, social discrimination, violations of privacy, property rights, and more. This has sparked a global debate on how to regulate AI and robotics ("governance of algorithms"). This book discusses both of these key aspects: the impact of algorithms, and the possibilities for future regulation.

Algorithms: Technology, Culture, Politics develops a relational, situated approach to algorithms. It takes a middle ground between theories that give the algorithm a singular and stable meaning in using it as a central analytic category for contemporary society and theories that dissolve the term into the details of empirical studies. The book discusses algorithms in relation to hardware and material conditions, code, data, and subjects such as users, programmers, but also "data doubles". The individual chapters bridge critical discussions on bias, exclusion, or responsibility with the necessary detail on the contemporary state of information technology.

The narratives around big data and data science are overwhelmingly white, male, and techno-heroic. In Data Feminism, Catherine D'Ignazio and Lauren Klein present a new way of thinking about data science and data ethics-one that is informed by intersectional feminist thought. Illustrating data feminism in action, D'Ignazio and Klein show how challenges to the male/female binary can help challenge other hierarchical (and empirically wrong) classification systems. They explain how, for example, an understanding of emotion can expand our ideas about effective data visualization, and how the concept of invisible labor can expose the significant human efforts required by our automated systems. And they show why the data never, ever "speak for themselves." Data Feminism offers strategies for data scientists seeking to learn how feminism can help them work toward justice, and for feminists who want to focus their efforts on the growing field of data science. But Data Feminism is about much more than gender. It is about power, about who has it and who doesn't, and about how those differentials of power can be challenged and changed.

This thought-provoking book follows the EU's journey into the digital age, explaining how it uses legislation and policy to tackle challenges such as the abuse of market power by Big Tech companies and the spread of hate speech and disinformation. Werner Stengg draws on his extensive experience in shaping digital policy to expertly analyse the EU's ambitious legislative and innovation programme, which focuses on human rights and prioritises trustworthy, transparent, and accountable usage of digital technologies. Alongside this examination of legislation and policy, Stengg also outlines the EU's major investment agenda into the digital infrastructures required to become a global player in our data-driven and AI-powered economy. Ultimately, the book highlights that innovations in the digital sphere are essential not only for the global competitiveness of European companies, but also for Europe to safeguard its resilience, autonomy, and technological sovereignty at a time of mounting geopolitical tensions.

What will you do when your AI misbehaves? The promise of artificial intelligence is automated decision-making at scale, but that means AI also automates risk at scale. Are you prepared for that risk? Already, many companies have suffered real damage when their algorithms led to discriminatory, privacy-invading, and even deadly outcomes. Self-driving cars have hit pedestrians; HR algorithms have precluded women from job searches; mortgage systems have denied loans to qualified minorities. And often the companies who deployed the AI couldn't explain why the black box made the decision it did. In this environment, AI ethics isn't merely an academic curiosity, it's a business necessity. In "Ethical Machines," Reid Blackman gives you all you need to understand AI ethics as a risk management challenge.

This book is one of two companion volumes that explore theories and histories of information from a humanistic perspective. They consider information as a long-standing feature of social, cultural, and conceptual management, a matter of social practice, and a fundamental challenge for the humanities today. Bringing together essays by prominent critics, Information: Keywords highlights the humanistic nature of information practices and concepts by thinking through key terms. It describes and anticipates directions for how the humanities can contribute to our understanding of information from a range of theoretical, historical, and global perspectives.

Most of recorded human history is one big data gap. Starting with the theory of Mand the Hunter, the chroniclers of the past have left little space for women's role in the evolution of humanity, whether cultural or biological. Instead, the lives of men have been taken to represent those of humans overall. When it comes to the lives of the other half of humanity, there is often nothing but silence.

This book highlights research on the behavioral biases affecting judgmental accuracy in judgmental forecasting and showcases the state-of-the-art in judgment-based predictive analytics. In recent years, technological advancements have made it possible to use predictive analytics to exploit highly complex (big) data resources. Consequently, modern forecasting methodologies are based on sophisticated algorithms from the domain of machine learning and deep learning. However, research shows that in the majority of industry contexts, human judgment remains an indispensable component of the managerial forecasting process. This book discusses ways in which decision-makers can address human behavioral issues in judgmental forecasting.

This book provides an in-depth overview of what is currently happening in the field of Law and Artificial Intelligence (AI). From deep fakes and disinformation to killer robots, surgical robots, and AI lawmaking, the many and varied contributors to this volume discuss how AI could and should be regulated in the areas of public law, including constitutional law, human rights law, criminal law, and tax law, as well as areas of private law, including liability law, competition law, and consumer law. Aimed at an audience without a background in technology, this book covers how AI changes these areas of law as well as legal practice itself. This scholarship should prove of value to academics in several disciplines (e.g., law, ethics, sociology, politics, and public administration) and those who may find themselves confronted with AI in the course of their work, particularly people working within the legal domain (e.g., lawyers, judges, law enforcement officers, public prosecutors, lawmakers, and policy advisors).

AI technology has come to play a central role in the modern data economy. Through a combination of increased computing power, the growing availability of data and the advancement of algorithms, AI has now become an umbrella term for some of the most transformational technological breakthroughs of this age. The importance of AI stems from both the opportunities that it offers and the challenges that it entails. While AI applications hold the promise of economic growth and efficiency gains, they also create significant risks and uncertainty. The potential and perils of AI have thus come to dominate modern discussions of technology and ethics - and although AI was initially allowed to largely develop without guidelines or rules, few would deny that the law is set to play a fundamental role in shaping the future of AI. As thedebate over AI is far from over, the need for rigorous analysis has never been greater. This book thus brings together contributors from different fields and backgrounds to explore how the law might provide answers to some of the most pressing questions raised by AI.

This book focuses on facial recognition technology (FRT) and sheds light on previously unexplored aspects that involve systematic legal issues concerning its regulation, the protection of rights and freedoms, the preservation of democracy and the rule of law. FRT employs cutting-edge AI systems capable of processing biometric data for identification, verification and categorization purposes. Although there have been huge strides in the research and development of these systems in the last few decades and computer scientists are following and supporting this evolution, legal scholars have only been investigating the implications for fundamental rights for the past few years. The introduction of new regulations (especially the European Union AI Act) have turned the debate on its head, putting FRT in the spotlight. However, there are still certain aspects that have not yet been explored but will be crucial in the coming years for the democratic, social, technical, ethical, and legal acceptance of this technology. The contributions gathered here address various legal approaches to FRT that are emerging at the global level. In this regard, they particularly examine how the distinction between private and public entities' use of - and consequently also their respective rules on - FRT is becoming increasingly unclear, as some of the latest cases show.

This open access edited volume focuses on fairness issues concerning the use of artificial intelligence (AI) for social service provision in national welfare systems. With this, it touches upon important questions in the innovation agenda of countries across continents about the ethics, justice, quality, responsibility, accountability, and transparency to use AI for state functions. The volume shows that in many countries, AI, or at least data analytics methods, are already in place to support the assessment of beneficiaries for deciding on the value criteria to distinguish between legal /fraudulent, deserving/non-deserving, or needy/non-needy recipients. The book provides a cross-cultural comparison of AI-based social assessment among national welfare systems of 9 countries across 4 continents: Spain, Estonia, Germany, Iran, India, Nigeria, Ukraine, China and USA.

It is widely presumed that digitalisation, automation and artificial intelligence (AI) shape the future of work; yet, gender is rarely considered in those debates. This ground-breaking book, written by a leading thinker on gender, inclusion and organisations, is based on in-depth research to show which patterns of gender and digitalisation emerge. By weaving these different patterns together, is it possible to understand the dynamic and complex ways gender and digitalisation intertwine in the work context? The book highlights how futures of work are imagined between automation and augmentation: it shows which tasks are expected to be done by machines, and where humans are expected to have a competitive advantage. The book showcases how algorithmic bias is constructed as ultimately fixable, and analyses in/visibilities in AI production processes. Above all, the book shows how patterns relating to gender and inclusion are shaped and could be re-shaped.

This pioneering Research Handbook on Public Management and Artificial Intelligenceprovides a comprehensive overview of the potentials, challenges, and governance principles of AI in a public management context. Multidisciplinary in approach, it draws on a variety of jurisdictional perspectives and expertly analyses key topics relating to this socio-technical phenomenon. Showcasing contributions by a collection of eminent scholars from across the globe, this Research Handbook presents cutting-edge research on AI in public management. Organised into three parts corresponding with distinct foci of research, it explores the adoption and implementation of AI in public management settings, presents specific case studies and examples of AI in the public sector, and outlines future trends and directions in the evolution of AI adoption and use in public management.

Social, Ethical & Legal Aspects of Generative AI: Tools, Techniques, and Systems highlights the transformative exploration of the AI revolution. This groundbreaking discourse deciphers the nexus between cutting-edge generative AI tools and the societal framework that shapes their impact. Generative AI is more than a technological marvel; it's a societal force reshaping industries, education, healthcare, and governance. Explore the ethical dilemmas, legal challenges, and innovative solutions driving its global adoption. This volume provides an insight into the latest innovations and state-of-the-art research in the fields of Social, Ethical & Legal Aspects of Generative AI, showcasing their potential to address AI's profound societal implications.