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  • Human-AI Interaction and Collaboration

    Human-AI Interaction and Collaboration by Wu, Dan; Liang, Shaobo;

      • GET 20% OFF

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      • Publisher's listprice GBP 65.00
      • The price is estimated because at the time of ordering we do not know what conversion rates will apply to HUF / product currency when the book arrives. In case HUF is weaker, the price increases slightly, in case HUF is stronger, the price goes lower slightly.

        31 053 Ft (29 575 Ft + 5% VAT)
      • Discount 20% (cc. 6 211 Ft off)
      • Discounted price 24 843 Ft (23 660 Ft + 5% VAT)

    31 053 Ft

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    Availability

    Estimated delivery time: In stock at the publisher, but not at Prospero's office. Delivery time approx. 3-5 weeks.
    Not in stock at Prospero.

    Why don't you give exact delivery time?

    Delivery time is estimated on our previous experiences. We give estimations only, because we order from outside Hungary, and the delivery time mainly depends on how quickly the publisher supplies the book. Faster or slower deliveries both happen, but we do our best to supply as quickly as possible.

    Product details:

    • Publisher Cambridge University Press
    • Date of Publication 9 October 2025

    • ISBN 9781009587853
    • Binding Hardback
    • No. of pages320 pages
    • Weight 614 g
    • Language English
    • 694

    Categories

    Short description:

    This book explores how humans and generative AI can interact and collaborate efficiently and ethically.

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    Long description:

    The integration of AI into information systems will affect the way users interface with these systems. This exploration of the interaction and collaboration between humans and AI reveals its potential and challenges, covering issues such as data privacy, credibility of results, misinformation, and search interactions. Later chapters delve into application domains such as healthcare and scientific discovery. In addition to providing new perspectives on and methods for developing AI technology and designing more humane and efficient artificial intelligence systems, the book also reveals the shortcomings of artificial intelligence technologies through case studies and puts forward corresponding countermeasures and suggestions. This book is ideal for researchers, students, and industry practitioners interested in enhancing human-centered AI systems and insights for future research.

    'This book offers a comprehensive exploration of the dynamic interaction and collaboration between humans and AI across various domains. It tackles both the opportunities and challenges presented by AI, highlighting its potential to enhance productivity, ethical considerations, and its role in shaping the future of industries such as healthcare and education. A valuable resource for anyone interested in understanding the multifaceted impact of AI.' Chuanfu Chen, Senior Professor of Humanities and Social Sciences, Wuhan University, China

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    Table of Contents:

    Contributor biographies; Preface; 1. Introduction Dan Wu, Guoye Sun and Shaobo Liang; 2. User Interaction for Human-AI Interaction and Collaboration Dan Wu and Qingyue Guo ; 3. Privacy Identification of Human-Generative AI Interaction Dan Wu and Guoye Sun; 4. Credibility Assessment of Human-Generative AI Interaction Yuxiang Chris Zhao, Shijie Song and Yutian Jing; 5. AI-supported Crowdsourcing for Knowledge Sharing Chei Sian Lee, Dion Hoe-Lian Goh, Hang Guo, Kok Khiang Lim and Qian Wu; 6. AI-supported Search Interaction for Enhancing Users' Understanding Shaobo Liang and Chenrui Shi; 7. AI for Human and Misinformation Interactions: A Case of Social Media Nannan Huang, Xiuzhen Zhang and Jia Tina Du; 8. Effective Human-AI Collaborative Intelligence Zhuoren Jiang and Xiaozhong Liu; 9. Human-AI Collaboration for Identifying Health Information Wants Zhuochun Li, Zhimeng Luo, Ning Zou, Bo Xie and Daqing He; 10. Human-AI Collaboration for Scientific Discovery Shuo Zhao, Yang Liu, Jiayu Wan, Tan Tang and Xin Li; 11. Challenges of Generative AI on Human-AI Interaction and Collaboration Shaobo Liang and Cai Yiting; 12. Conclusion Dan Wu, Guoye Sun and Shaobo Liang.

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