Handbook Of Critical Studies Of Artificial Intelligence

As artificial intelligence (AI) continues to seep into more areas of society and culture, critical social perspectives on its technologies are more urgent than ever before. Bringing together state-of-the-art research from experienced scholars across disciplines, this Handbook provides a comprehensive overview of the current state of critical AI studies.

We live in an age of artificial intelligence. Machines think and act in ever more complex ways, making suggestions and decisions on our behalf. While AI might be seen as practical and profitable, issues of data surveillance, algorithmic control, and sexist and racist bias persist. In this rapidly changing landscape, social analysis of AI risks getting scaled down to issues of ‘ethics’, ‘responsibility’, and ‘fairness’. While these are important issues, they must be addressed not from an ‘AI first’ perspective, but more thoroughly in terms of power and contention. Approaching artificial intelligence from the often overlooked perspective of critical social theory, this book provides a much-needed intervention on how both old and new theories conceptualize the social consequences of AI. Questions are posed about the ideologies driving AI, the mythologies surrounding AI, and the complex relationship between AI and power. Simon Lindgren provides a way of defining AI as an object of social and political critique, and guides the reader through a set of contentious areas where AI and politics intersect. In relation to these topics, critical theories are drawn upon, both as an argument for and an illustration of how AI can be critiqued. Given the opportunities and challenges of AI, this book is a must-read for students and scholars in the humanities, social sciences, and STEM disciplines.

This timely Handbook explores the relationship between public policy and artificial intelligence (AI) technologies across a broad range of geographical, technical, political and policy contexts. It contributes to critical AI studies, focusing on the intersection of the norms, discourses, policies, practices, and regulation that shape AI in the public sector. Expert authors in the field discuss the creation and use of AI technologies and how public authorities respond to their development, by bringing together emerging scholarly debates about AI technologies with longer-standing insights on public administration, policy, regulation and governance. Contributions in the Handbook mobilise diverse perspectives to critically examine techno-solutionist approaches to public policy and AI, dissect the politico-economic interests underlying AI promotion, and analyse implications for sustainable development, fairness, and equality. Ultimately, this Handbook questions whether regulatory concepts such as ethical, trustworthy, or accountable AI safeguard a democratic future or contribute to a problematic de-politicisation of the public sector. The Handbook on Public Policy and Artificial Intelligence is a crucial resource for students and scholars of public policy and administration, political economy, political science, sociology, law, regulation and governance, computer science and technology studies. It is also beneficial to policy practitioners, civil society actors, and regulators working with AI technologies.

The field of artificial intelligence (AI) has made tremendous advances in the last two decades, but as smart as AI is now, it is getting smarter and becoming more autonomous. This raises a host of challenges to current legal doctrine, including whether AI/algorithms should count as ‘speech’, whether AI should be regulated under antitrust and criminal law statutes, and whether AI should be considered as an agent under agency law or be held responsible for injuries under tort law. This book contains chapters from US and international law scholars on the role of law in an age of increasingly smart AI, addressing these and other issues that are critical to the evolution of the field.

This cutting-edge Handbook offers a comprehensive introduction to the emerging research field of artificial intelligence (AI) in human resource management (HRM). Broadly mapping AI fields relevant for HR, it not only considers the more well-known areas of machine learning and natural language processing, but also lesser-known fields such as affective computing and robotic process automation.

Different theories, models and narratives of innovation compete for both legitimacy and authority. However, despite the variations, they all offer a consistent pro-innovation bias, dismissing resistance as irrational, and overlooking the value of non-users and collateral impacts. This book looks at innovation from a different perspective and asks, what has been left out? It offers a reflexive view and invites researchers to consider new avenues of research, through a critique of current representations of innovation.

An authoritative, up-to-date survey of the state of the art in artificial intelligence, written for non-specialists.

For decades, optimization methods such as Fuzzy Logic, Artificial Neural Networks, Firefly, Simulated annealing, and Tabu search, have been capable of handling and tackling a wide range of real-world application problems in society and nature. Analysts have turned to these problem-solving techniques in the event during natural disasters and chaotic systems research. The Handbook of Research on Artificial Intelligence Techniques and Algorithms highlights the cutting edge developments in this promising research area. This premier reference work applies Meta-heuristics Optimization (MO) Techniques to real world problems in a variety of fields including business, logistics, computer science, engineering, and government. This work is particularly relevant to researchers, scientists, decision-makers, managers, and practitioners.