Leila Halawi – författare

Trust in Generative Artificial Intelligence: Human‑Robot Interaction and Ethical Considerations is a comprehensive exploration of the critical role of trust in the rapidly evolving world of AI. Edited by Joanna Paliszkiewicz, Ireneusz Dąbrowski, and Leila Halawi, this book provides a thorough examination of how trust influences the integration and effectiveness of generative AI in various aspects of society. The book spans three main sections, offering insights from international experts across multiple disciplines and a blend of theoretical foundations and practical insights, making it a valuable resource for both understanding and implementing trust in AI systems. Readers will benefit from in‑depth analyses of emerging trends, systematic literature reviews, and case studies on trust in diverse contexts, from social media to healthcare. The focus on human‑robot interaction and ethical considerations provides a nuanced understanding of the psychological and ethical factors at play. Aimed at researchers, practitioners, and policymakers interested in AI, ethics, and human‑robot interaction, this edited collection is also suitable for educators and students in fields related to AI and technology, providing a comprehensive resource for academic study and practical application.

Trust in Generative Artificial Intelligence: Human‑Robot Interaction and Ethical Considerations is a comprehensive exploration of the critical role of trust in the rapidly evolving world of AI. Edited by Joanna Paliszkiewicz, Ireneusz Dąbrowski, and Leila Halawi, this book provides a thorough examination of how trust influences the integration and effectiveness of generative AI in various aspects of society. The book spans three main sections, offering insights from international experts across multiple disciplines and a blend of theoretical foundations and practical insights, making it a valuable resource for both understanding and implementing trust in AI systems. Readers will benefit from in‑depth analyses of emerging trends, systematic literature reviews, and case studies on trust in diverse contexts, from social media to healthcare. The focus on human‑robot interaction and ethical considerations provides a nuanced understanding of the psychological and ethical factors at play. Aimed at researchers, practitioners, and policymakers interested in AI, ethics, and human‑robot interaction, this edited collection is also suitable for educators and students in fields related to AI and technology, providing a comprehensive resource for academic study and practical application.

This textbook presents a practical approach to predictive analytics for classroom learning. It focuses on using analytics to solve business problems and compares several different modeling techniques, all explained from examples using the SAS Enterprise Miner software. The authors demystify complex algorithms to show how they can be utilized and explained within the context of enhancing business opportunities. Each chapter includes an opening vignette that provides real-life example of how business analytics have been used in various aspects of organizations to solve issue or improve their results. A running case provides an example of a how to build and analyze a complex analytics model and utilize it to predict future outcomes.