Interdependent Human-Machine Teams

The Path to Autonomy
Herausgeber: Lawless, William; Fouad, Hesham; Sofge, Donald; Mittu, Ranjeev

• Broschiertes Buch

Produktbeschreibung

Interdependent Human-Machine Teams: The Path to Autonomy examines the foundations, metrics, and applications of human-machine systems, the legal ramifications of autonomy, trust by the public, and trust by the users and AI systems of their users, integrating concepts from various disciplines such as AI, machine learning, social sciences, quantum mechanics, and systems engineering. In this book, world-class researchers, engineers, ethicists, and social scientists discuss what machines, humans, and systems should discuss with each other, to policymakers, and to the public. It establishes the meaning and operation of "shared contexts" between humans and machines, policy makers, and the public and explores how human-machine systems affect targeted audiences (researchers, machines, robots, users, regulators, etc.) and society, as well as future ecosystems composed of humans, machines, and systems.

Produktdetails

• Verlag: Elsevier Science
• Seitenzahl: 448
• Erscheinungstermin: 10. Dezember 2024
• Englisch
• Abmessung: 229mm x 152mm x 23mm
• Gewicht: 599g
• ISBN-13: 9780443292460
• ISBN-10: 0443292469
• Artikelnr.: 70891897

Inhaltsangabe

1. Introduction to "autonomous human-machine teams"
2. Toward a new foundation for AI
3. Human-machine teaming using large language models
4. Development of a team cohesion scale for use in human-autonomy team
research
5. Enabling human-machine symbiosis: Automated establishment of common
ground and estimates of the topological structures of Commander’s
Intent
6. Measuring consequential changes in human-autonomous system
interactions
7. User affordances to engineer open-world enterprise dynamics
8. Truth-O-Meter: Collaborating with LLM in fighting its hallucinations
9. Natural versus artificial intelligence: AI insights from the
cognitive sciences
10. Intention when humans team with AI
11. Autonomy: A family resemblance concept? An exploration of human-robot
teams
12. A theoretical approach to management of limited attentional resources
to support the m:N operation in advanced air mobility ecosystem
13. Predicting workload of dispatchers supervising autonomous systems
14. The generative AI weapon of mass destruction: Evolving disinformation
threats, vulnerabilities, and mitigation frameworks
15. Ethics for artificial agents
16. Self-visualization for the human-machine mind-body problem
17. Knowledge, consciousness, and debate: advancing the science of
autonomous human-machine teams