Interdependent Human-Machine Teams
eBook - ePub

Interdependent Human-Machine Teams

The Path to Autonomy

  1. 300 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Interdependent Human-Machine Teams

The Path to Autonomy

About this book

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.- Investigates how interdependence is the missing ingredient necessary to produce operational autonomous 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

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Yes, you can access Interdependent Human-Machine Teams by William Lawless,Ranjeev Mittu,Donald Sofge,Hesham Fouad in PDF and/or ePUB format, as well as other popular books in Computer Science & Artificial Intelligence (AI) & Semantics. We have over one million books available in our catalogue for you to explore.

Table of contents

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