AI for Social Sciences

The use of AI in social sciences is on the rise and gaining significant momentum. The book aims to demystify AI and its applications in social sciences by offering a straightforward description of its key concepts and tools, all in an easy-to-understand language.

The book delves into the fundamental elements of AI systems, shedding light on their capabilities as well as their inherent constraints. Moreover, the author explores AI tools that find applications in the realm of social sciences, including decision support systems rooted in machine learning, as well as knowledge-based. In addition, the book addresses the pertinent issues that, while not purely AI-related, are crucial in AI applications within the social sciences, most notably security and privacy considerations.

The content should be accessible to an audience ranging from undergraduate students to researchers and practitioners in the fields of AI and social sciences, assuming they possess a basic understanding of mathematics and a keen interest in the subject. This book is a bridge between the worlds of AI and social sciences, aiming to provide a fundamental understanding for those eager to explore the intersection of these two domains.

Introduces AI in a broad yet rigorous way, without the level of mathematics or computer science needed in AI courses Discusses topics like knowledge representation, decision support systems, security, privacy, ethics and societal impacts Accessible to a wide audience, serves as reference for students and practitioners in social services and work management

Autorentext

Vicenç Torra is Professor of Artificial Intelligence in the Dept. of Computing Science at Umeå University. He has a PhD in Computer Science / AI from Polytechnical University of Catalonia in 1994. He has held positions at Universitat Rovira i Virgili (Catalonia, Spain), Artificial Intelligence Research Institute - Spanish Council for Scientific Research (IIIA-CSIC), Skövde University (2014-2020, Professorship, Sweden), and Maynooth University (2018-2020, Professorship, Ireland). Additionally, he has undertaken visiting positions at Tsukuba University in Japan, and maintains a longstanding and fruitful collaboration with Japanese researchers. Torra's areas of expertise center on artificial intelligence, with a particular focus on data privacy and approximate reasoning (reasoning under uncertainty, fuzzy sets and systems). He is IEEE and EurAI fellow, and ISI elected member. He has written several books including "Fundamentals of artificial intelligence" (in Catalan, Open University Press, 2007), "Modeling Decisions" (with Y. Narukawa, Springer, 2007), "Scala: from a functional programming perspective" (Springer, 2016), "Guide to data privacy" (Springer, 2022).

Inhalt

1. Introduction.- 2. Artificial intelligence and intelligent systems.- 3. Decision-support systems.- 4. Machine learning at work. Data-science.- 5. Security and privacy.- 6. Applications in social sciences.- 7. Ethics and AI.