Bi-directionality in Human-AI Collaborative Systems
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71 261 Ft (67 867 Ft + 5% VAT)
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71 261 Ft
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Product details:
- Publisher Academic Press
- Date of Publication 1 July 2025
- ISBN 9780443405532
- Binding Paperback
- No. of pages506 pages
- Size 235x191 mm
- Language English 700
Categories
Long description:
Bi-directionality in Human-AI Collaborative Systems investigates the foundations, metrics, and applications of human-machine systems, along with the legal ramifications of autonomy, including standards, trust by the public, and bidirectional trust by users and AI systems. The book addresses the challenges in creating synergistic human and AI-based autonomous system-of-systems by focusing on the underlying challenges associated with bi-directionality. Chapters cover advances in LLMs, logic, machine learning choices, the development of standards, as well as human-centered approaches to autonomous human-machine teams. This is a valuable resource for world-class researchers and engineers who are theorizing on, designing, and developing autonomous systems.
It will also be useful for government scientists, business leaders, social scientists, philosophers, regulators and legal experts interested in the impact of autonomous human-machine teams and systems.
- Investigates the challenges in creating synergistic human and AI-based autonomous system-of-systems
- Integrates concepts from a wide range of disciplines, including applied and theoretical AI, quantum mechanics, social sciences, and systems engineering
- Presents debates, models, and concepts of mutual dependency for autonomous human-machine teams, challenging assumptions across AI, systems engineering, data science, and quantum mechanics
Table of Contents:
1. Introduction
2. Interdependence in the human-machine fusion process
3. Advances in large language models
4. Logic applied to machines as part of a human-machine team
5. Machine learning model choices
6. Mixing machines and humans with mathematics
7. The development of standards for human-machine teams
8. The Systems Engineering Research Center’s approach to teams of swarms, machines and humans
9. Human-machine teams in aviation
10. Autonomous human-machine teams in Australia
11. A human-centered approach to autonomous human-machine teams
12. Risks and ethics in human-machine teams
13. Data Poisoning in human-machine teams
14. Trust and among human-machine teammates
15. Belief and consciousness in human-machine teams
16. Explainability in human-machine teams
17. Risk, trust, and safety in human-machine teams
18. Joint awareness in human-machine teams 19. Shared mental models in human-machine teams
20. System design and engineering for human-machine teams
21. Testing and evaluation of human-machine teams
Bi-directionality in Human-AI Collaborative Systems
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