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