Regulating AI: What Everyone Needs to Know about Artificial Intelligence and the Law Front Cover

Regulating AI: What Everyone Needs to Know about Artificial Intelligence and the Law

Description

Until somewhat recently, AI was mostly an academic pursuit that always seemed far away from being released outside of academia. Today, however, AI is touching almost every aspect of human life. As such, there are several emerging legal and policy questions that society will need to reckon with. Although we are faced with new challenges, we have many opportunities to utilize true-and-tested frameworks and legal infrastructure that has been centuries in the making.

This book tries to bring together two disparate fields, law and technology, and give the reader and understanding of their convergence and divergence. We start to answer many of these questions, or at least open the discussion that acknowledges its complexity. This is an exploration of those questions and where possible we try to go over information that might be helpful in appreciating the depth of those questions. As technology and law are two large subjects that span a wide range, we do our best to narrow the scope of the chapters as best we can.

This book should not be taken as “original research” in that we hypothesize how the legal system should change or what the answers to these questions are. We instead look at the underlying logic that is provided within current legal frameworks to see how they can be adapted to fit current AI and future generations of much more powerful AI. Just as this is an emerging field, we are emerging researchers interested in starting to put pen to paper on the kind of questions we will spend our lifetimes pursuing.

In the last chapter we ask AI to make some forward looking projections about how it sees AI and law intersecting in the future. In summary, this book is not intended to convey original research or ideas about how AI and the law should interact in the future. It is not formal, academic research, but rather thoughts, ideas, and frameworks that two students wanted to compile based on classwork across Stanford and externally.

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