This provocative book investigates the relationship between law and artificial intelligence (AI) governance, and the need for new and innovative approaches to regulating AI and big data in ways that go beyond market concerns alone and look to sustainability and social good. Taking a multidisciplinary approach, the contributors demonstrate the interplay between various research methods, and policy motivations, to show that law-based regulation and governance of AI is vital to efforts at ensuring justice, trust in administrative and contractual processes, and inclusive social cohesion in our increasingly technologically-driven societies. The book provides valuable insights on the new challenges posed by a rapid reliance on AI and big data, from data protection regimes around sensitive personal data, to blockchain and smart contracts, platform data reuse, IP rights and limitations, and many other crucial concerns for law’s interventions. The book also engages with concerns about the ‘surveillance society’, for example regarding contact tracing technology used during the Covid-19 pandemic. The analytical approach provided will make this an excellent resource for scholars and educators, legal practitioners (from constitutional law to contract law) and policy makers within regulation and governance. The empirical case studies will also be of great interest to scholars of technology law and public policy. The regulatory community will find this collection offers an influential case for law’s relevance in giving institutional enforceability to ethics and principled design.

This provocative book investigates the relationship between law and artificial intelligence (AI) governance, and the need for new and innovative approaches to regulating AI and big data in ways that go beyond market concerns alone and look to sustainability and social good.

Taking a multidisciplinary approach, the contributors demonstrate the interplay between various research methods, and policy motivations, to show that law-based regulation and governance of AI is vital to efforts at ensuring justice, trust in administrative and contractual processes, and inclusive social cohesion in our increasingly technologically-driven societies. The book provides valuable insights on the new challenges posed by a rapid reliance on AI and big data, from data protection regimes around sensitive personal data, to blockchain and smart contracts, platform data reuse, IP rights and limitations, and many other crucial concerns for law’s interventions. The book also engages with concerns about the ‘surveillance society’, for example regarding contact tracing technology used during the Covid-19 pandemic.

The analytical approach provided will make this an excellent resource for scholars and educators, legal practitioners (from constitutional law to contract law) and policy makers within regulation and governance. The empirical case studies will also be of great interest to scholars of technology law and public policy. The regulatory community will find this collection offers an influential case for law’s relevance in giving institutional enforceability to ethics and principled design.

This provocative and timely book identifies and disrupts the conventional regulation and governance discourses concerning AI and big data. It suggests that, instead of being used as tools for exclusionist commercial markets, AI and big data can be employed in governing digital transformation for social good. Analysing the ways in which global technology companies have colonised data access, the book reveals how trust, ethics, and digital self-determination can be reconsidered and engaged to promote the interests of marginalised stakeholders in data arrangement. Chapters examine the regulation of labour engagement in digital economies, the landscape of AI ethics, and a multitude of questions regarding participation, costs, and sustainability. Presenting several informative case studies, the book challenges some of the accepted qualifiers of frontier tech and data use and proposes innovative ways of actioning the more conventional regulatory components of big data. Scholars and students in information and media law, regulation and governance, and law and politics will find this book to be critical reading. It will also be of interest to policymakers and the AI and data science community.

This provocative book investigates the relationship between law and artificial intelligence (AI) governance, and the need for new and innovative approaches to regulating AI and big data in ways that go beyond market concerns alone and look to sustainability and social good. Taking a multidisciplinary approach, the contributors demonstrate the interplay between various research methods, and policy motivations, to show that law-based regulation and governance of AI is vital to efforts at ensuring justice, trust in administrative and contractual processes, and inclusive social cohesion in our increasingly technologically-driven societies. The book provides valuable insights on the new challenges posed by a rapid reliance on AI and big data, from data protection regimes around sensitive personal data, to blockchain and smart contracts, platform data reuse, IP rights and limitations, and many other crucial concerns for law’s interventions. The book also engages with concerns about the ‘surveillance society’, for example regarding contact tracing technology used during the Covid-19 pandemic. The analytical approach provided will make this an excellent resource for scholars and educators, legal practitioners (from constitutional law to contract law) and policy makers within regulation and governance. The empirical case studies will also be of great interest to scholars of technology law and public policy. The regulatory community will find this collection offers an influential case for law’s relevance in giving institutional enforceability to ethics and principled design.

This provocative book investigates the relationship between law and artificial intelligence (AI) governance, and the need for new and innovative approaches to regulating AI and big data in ways that go beyond market concerns alone and look to sustainability and social good.

Taking a multidisciplinary approach, the contributors demonstrate the interplay between various research methods, and policy motivations, to show that law-based regulation and governance of AI is vital to efforts at ensuring justice, trust in administrative and contractual processes, and inclusive social cohesion in our increasingly technologically-driven societies. The book provides valuable insights on the new challenges posed by a rapid reliance on AI and big data, from data protection regimes around sensitive personal data, to blockchain and smart contracts, platform data reuse, IP rights and limitations, and many other crucial concerns for law’s interventions. The book also engages with concerns about the ‘surveillance society’, for example regarding contact tracing technology used during the Covid-19 pandemic.

The analytical approach provided will make this an excellent resource for scholars and educators, legal practitioners (from constitutional law to contract law) and policy makers within regulation and governance. The empirical case studies will also be of great interest to scholars of technology law and public policy. The regulatory community will find this collection offers an influential case for law’s relevance in giving institutional enforceability to ethics and principled design.

This provocative and timely book identifies and disrupts the conventional regulation and governance discourses concerning AI and big data. It suggests that, instead of being used as tools for exclusionist commercial markets, AI and big data can be employed in governing digital transformation for social good. Analysing the ways in which global technology companies have colonised data access, the book reveals how trust, ethics, and digital self-determination can be reconsidered and engaged to promote the interests of marginalised stakeholders in data arrangement. Chapters examine the regulation of labour engagement in digital economies, the landscape of AI ethics, and a multitude of questions regarding participation, costs, and sustainability. Presenting several informative case studies, the book challenges some of the accepted qualifiers of frontier tech and data use and proposes innovative ways of actioning the more conventional regulatory components of big data. Scholars and students in information and media law, regulation and governance, and law and politics will find this book to be critical reading. It will also be of interest to policymakers and the AI and data science community.