AI Law and Policy (Aspen Casebook Series)

AI Law and Policy is a casebook that offers a survey of law and policy challenges introduced by artificial intelligence (AI) and other emerging technologies. This casebook provides a panoramic snapshot of a fast-moving phenomenon in a transformative moment of history and attempts to capture a wide-lens story of technology that is disruptive and undergoing the earliest stages of experimentation. The approach of this project is to offer key primary source materials that tell a story: why the history of AI law and policy at the nascent stages is coterminous with how we should struggle with the project of AI law and policy over its longer trajectory. AI Law and Policy aims for breadth of the evolving history of a range of AI governance concepts The approach will ground the student in how AI must be interrogated for its governance impact through a wide range of case studies. The evolving arc of AI governance is examined through a series of primary source materials: complaints and cases, statutes, regulations, reports, press releases and policy guidance documents—that span multiple areas of law and policy, including Data Privacy, Cybersecurity, Antidiscrimination Law, Product Liability and Torts, Intellectual Property, Antitrust, National Security, and other related fields. Benefits for instructors and students: Historical approach provides a collection of primary source materials that facilitate the study of AI through the lens of those who are struggling to create a body of law and policies to govern an evolving technological movement. A wide variety of materials, such as proposed statutes and regulations, guidance documents, congressional hearings and testimony, reports, and other primary source materials, contextualizes how laws and policies are developing from a recognition of AI’s impact. Foundational topics set the necessary precursor of discussion for the entire field of AI and the Law before addressing substantive legal issues or presenting cases. Topics include algorithmic discrimination; transparency and explainability; data privacy, autonomy, and democracy. Modular chapters allow for flexibility in teaching based on the adopter’s priorities for coverage and sequence. The book is an excellent choice for use in a law school seminar, a doctrinal/survey course, a short course/compressed course, small discussion group setting, or a more traditional doctrinal lecture format. View Less