Handbook of Human-AI Collaboration
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Beschreibung
This Open Access handbook provides a comprehensive and interdisciplinary perspective on Human–AI Collaboration, bringing together contributions from computer science, cognitive science, philosophy, social sciences, law, and design. As Foundation Models and Generative AI transform the capabilities of intelligent systems, understanding how humans and AI systems can effectively learn, reason, create, and make decisions together has become a central scientific and societal challenge.
The handbook begins by examining the foundations of Human–AI Collaboration, exploring the collaborative nature of intelligence and the cognitive, computational, philosophical, and design principles that underpin effective partnerships between humans and AI systems. It also highlights the importance of explainability and decision support in building trustworthy and collaborative AI.
The technological foundations of contemporary AI systems are presented through multimodal Foundation Models capable of processing and generating text, images, speech, audio, and code. Building upon these advances, the volume investigates how generative AI can augment human cognition and support creativity, problem solving, software development, and knowledge work.
Contributors further explore learning and reasoning with Foundation Models, including personalized learning, retrieval-augmented generation, and compositional reasoning frameworks. Methodologies and metrics for evaluating Human–AI interaction and teamwork are presented, together with benchmarking approaches for assessing collaborative performance.
Beyond technical aspects, the handbook examines the co-evolution of Human–AI Collaboration and society, addressing the long-term impact of generative AI, changing patterns of task allocation, and the emergence of distributed collaborative ecosystems. Ethical, legal, and governance dimensions are also discussed, including transparency, fairness, accountability, sustainability, misinformation, and responsible innovation in domains such as healthcare, education, work, and democratic participation.
By providing an integrated view of theory, technology, cognition, evaluation, society, and governance, this handbook offers a critical roadmap for researchers, practitioners, policymakers, and students seeking to understand and shape the future of collaborative intelligence.
This book is open access, which means that you have free and unlimited access Explores how humans and AI systems can collaborate rather than compete or substitute one another Examines cognitive, computational, and societal foundations of Human–AI Collaboration Presents methods for evaluating, benchmarking, and advancing Human–AI collaboration and teamwork
Autor*in
Mohamed Chetouani
Themen in »Handbook of Human-AI Collaboration«
Open Access Human AI Deep Neural Network (DNN) Foundational Models to Assis Humans Supporting Learning and Reasoning with Foundation Models Hybrid AI Large Generative Models (LGMs) Large Language Models (LLMs) Human and AI agents LGM nodes Ethical Guidelines and Legal Frameworks The EU Legal Choice Architecture (CA) AI Ethics and Sustainability