Christo El Morr - Böcker

AI's impact on human societies is and will be drastic in so many ways. AI is being adopted and implemented around the world, and government and universities are investing in AI studies, research, and development. However, very little research exists about the impact of AI on our lives. This book will address this gap; it will gather reflections from around the world to assess the impact of AI on different aspects of society as well as propose ways in which we can address this impact and the research agendas needed.

AI's impact on human societies is and will be drastic in so many ways. AI is being adopted and implemented around the world, and government and universities are investing in AI studies, research, and development. However, very little research exists about the impact of AI on our lives. This book will address this gap; it will gather reflections from around the world to assess the impact of AI on different aspects of society as well as propose ways in which we can address this impact and the research agendas needed.

This book offers a practical introduction to healthcare analytics that does not require a background in data science or statistics. It presents the basics of data, analytics and tools and includes multiple examples of their applications in the field. The book also identifies practical challenges that fuel the need for analytics in healthcare as well as the solutions to address these problems. In the healthcare field, professionals have access to vast amount of data in the form of staff records, electronic patient record, clinical findings, diagnosis, prescription drug, medical imaging procedure, mobile health, resources available, etc. Managing the data and analyzing it to properly understand it and use it to make well-informed decisions can be a challenge for managers and health care professionals. A new generation of applications, sometimes referred to as end-user analytics or self-serve analytics, are specifically designed for non-technical users such as managers and business professionals. The ability to use these increasingly accessible tools with the abundant data requires a basic understanding of the core concepts of data, analytics, and interpretation of outcomes. This book is a resource for such individuals to demystify and learn the basics of data management and analytics for healthcare, while also looking towards future directions in the field.

This book provides a hands-on introduction to Machine Learning (ML) from a multidisciplinary perspective that does not require a background in data science or computer science.

This book offers a bold and critical examination of the intersections between artificial intelligence (AI) and disability justice. Rather than framing AI as a neutral or purely beneficial tool, the book interrogates how AI systems reproduce ableism, deepen systemic exclusions, and perpetuate colonial, neoliberal, and corporate power structures. It challenges the prevailing reliance on "tech fixes"—improving datasets or tweaking algorithms—and instead insists on addressing the deeper social, political, and ethical dimensions of AI development and deployment. Through a disability justice lens, it highlights the complex realities faced by disabled communities and emphasizes the need for approaches that dismantle ableism rather than superficially enhance accessibility.Covering topics such as algorithmic bias, data colonialism, technoableism, and the militarization of AI, this book foregrounds critical frameworks including design justice, data sovereignty, and participatory governance. It draws on diverse scholarly perspectives and activist insights to propose actionable pathways toward more accountable, equitable, and inclusive AI futures. By centering disabled people’s experiences and knowledge, the book offers not only critique but also visionary strategies for transforming AI systems to serve justice rather than entrench oppression.