Artificial Intelligence: Selected Resources

A revealing look at how negative biases against women of color are embedded in search engine results and algorithms.

In a masterful blend of history and on-the ground reporting, Christian traces the explosive growth in the field of machine learning and surveys its current, sprawling frontier. Whether they--and we--succeed or fail in solving the alignment problem will be a defining human story. The Alignment Problem offers an unflinching reckoning with humanity's biases and blind spots, our own unstated assumptions and often contradictory goals.

In this book, Terry Sejnowski explains how deep learning went from being an arcane academic field to a disruptive technology in the information economy. The new version of AI Sejnowski and others developed, which became deep learning, is fueled instead by data.

Reporting from the cutting edge of scientific research, The Ethical Algorithm offers a new approach: a set of principled solutions based on the emerging and exciting science of socially aware algorithm design.

How will Artificial Intelligence affect crime, war, justice, jobs, society and our very sense of being human? The rise of AI has the potential to transform our future more than any other technology--and there's nobody better qualified or situated to explore that future than Max Tegmark, an MIT professor who's helped mainstream research on how to keep AI beneficial.

This volume explores the scientific, economic, and social implications of advanced artificial intelligence systems in human life.

From Wharton professor and author of the popular One Useful Thing Substack newsletter Ethan Mollick comes the definitive playbook for working, learning, and living in the new age of AI. Mollick urges us to engage with AI as co-worker, co-teacher, and coach. He assesses its profound impact on business and education, using dozens of real-time examples of AI in action. Co-Intelligence shows what it means to think and work together with smart machines, and why it's imperative that we master that skill.

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. With little resistance from law or society, surveillance capitalism is on the verge of dominating the social order and shaping the digital future -- if we let it.

Delegating important decisions to machines gives rise to deep moral concerns about responsibility, transparency, freedom, fairness, and democracy. Algorithms and Autonomy connects these concerns to the core human value of autonomy in the contexts of algorithmic teacher evaluation, risk assessment in criminal sentencing, predictive policing, background checks, news feeds, ride-sharing platforms, social media, and election interference.

Bringing together theories of whiteness and race in the humanities and social sciences with a deep understanding of the history and practice of science and computing, Artificial Whiteness is an incisive, urgent critique of the uses of AI as a political tool to uphold social hierarchies.

Conceptualizing algorithms as ethicopolitical entities that are entangled with the data attributes of people, Amoore outlines how algorithms give incomplete accounts of themselves, learn through relationships with human practices, and exist in the world in ways that exceed their source code.

This book provides an overview of the role of AI in medicine and, more generally, of issues at the intersection of mathematics, informatics, and medicine. It is intended for AI experts, offering them a valuable retrospective and a global vision for the future, as well as for non-experts who are curious about this timely and important subject.

Turning Point is essential reading for anyone concerned about how artificial intelligence works and what can be done to ensure its benefits outweigh its harm.

In this book, Ed Finn considers how the algorithm--in practical terms, "a method for solving a problem"--has its roots not only in mathematical logic but also in cybernetics, philosophy, and magical thinking. Finn argues that the algorithm deploys concepts from the idealized space of computation in a messy reality, with unpredictable and sometimes fascinating results.