Health Law's Kaleidoscope : Health Law Rights in a Global Age

Within contemporary society the themes of globalization, health and regulation interlock in complex patterns, changing in response to the mix of cultural differences, regulatory preferences and available resources. To turn the kaleidoscope and to change the mix is to change the pattern. This book is about those patterns as they arise in the contemporary legal, health and ethical context, exploring the transformations and challenges brought by technological change and the regulatory options in the contemporary global village.

Reason is too large : analogy and precedent in law

Hunter argues that cognitive science models of human thinking explain how analogical reasoning and precedential reasoning operate in law. He offers an explanation of why various legal theories are so limited and calls for greater attention to what is actually happening when lawyers and judges reason, by analogy, with precedent.

Globalisation and Health : Challenges for Health Law and Bioethics

This timely collection explores ethical and legal dilemmas in healthcare arising from globalization. Conflicts between public interests and individual rights, the challenge of regulating professionals and access to health services, and the effects of a global market all feature prominently in contemporary debates in this area. As a result of globalization, issues in health law and bioethics can no longer be understood solely within political boundaries that define traditional notions of individuals and communities. Rather, solutions for emerging problems require a global conception of rights and obligations, including the re-evaluation of ethical frameworks and legal regimes that currently govern exchanges in healthcare. Leading scholars in bioethics, law, medicine and philosophy from various jurisdictions engage these themes in this volume, and demonstrate the need for transnational solutions in a global age of healthcare.

Near knowledge : inductive learning systems in law

Induction is an interesting model of legal reasoning, since it provides a method of capturing initial states of legal principles and rules, and adjusting these principles and rules over time as the law changes. In this article I explain how Artificial Intelligence-based inductive learning algorithms work, and show how they have been used in law to model legal domains. I identify some problems with implementations undertaken in law to date, and create a taxonomy of appropriate cases to use in legal inductive inferencing systems. I suggest that inductive learning algorithms have potential in modeling law, but that the artificial intelligence implementations to date are problematic. I argue that induction should be further investigated, since it has the potential to be an extremely useful mechanism for understanding legal domains.