Putting AI in the Critical Loop: Assured Trust and Autonomy in Human-Machine Teams

Putting AI in the Critical Loop: Assured Trust and Autonomy in Human-Machine Teams takes on the primary challenges of bidirectional trust and performance of autonomous systems, providing readers with a review of the latest literature, the science of autonomy, and a clear path towards the autonomy of human-machine teams and systems. Throughout this book, the intersecting themes of collective intelligence, bidirectional trust, and continual assurance form the challenging and extraordinarily interesting themes which will help lay the groundwork for the audience to not only bridge knowledge gaps, but also to advance this science to develop better solutions. The distinctively different characteristics and features of humans and machines are likely why they have the potential to work well together, overcoming each other's weaknesses through cooperation, synergy, and interdependence which forms a collective intelligence.? Trust is bidirectional and two-sided; humans need to trust AI technology, but future AI technology may also need to trust humans. Assesses the latest research advances, engineering challenges, and the theoretical gaps surrounding the question of autonomyReviews the challenges of autonomy (e.g., trust, ethics, legalities, etc.), including gaps in the knowledge of the scienceOffers a path forward to solutionsInvestigates the value of trust by humans of HMTs, as well as the bidirectionality of trust, understanding how machines learn to trust their human teammates INDICE: 1. Introduction2. Alternative paths to developing engineering solutions for human-machine teams 3. Risk determination versus risk perception: From hate speech, an erroneous drone attack, and military nuclear wastes to human machine autonomy4. Appropriate Context-Dependent Artificial Trust in Human-Machine Teamwork5. Toward a Causal Modeling Approach for Trust-Based Interventions in Human-Autonomy Teams6. Risk Management in Human-in-the-Loop AI-Assisted Attention Aware Systems7. Enabling Trustworthiness in Human-swarm Systems Through a Digital Twin8. Building Trust with the Ethical Affordances of Education Technologies: A Sociotechnical Systems Perspective9. Perceiving a Humorous Robot as a Social Partner10. Real-Time AI: Using AI on the Tactical Edge11. Building a Trustworthy AI Digital Twin: A Brave New World of Human Machine Teams & Autonomous Biological Internet of Things (BIoT)12. A framework of Human Factors methods for safe, ethical, and usable Artificial Intelligence in Defence13. A schema for harms-sensitive reasoning, and an approach to populate its ontology by human annotation

• ISBN: 978-0-443-15988-6
• Editorial: Academic Press
• Encuadernacion: Rústica
• Páginas: 304
• Fecha Publicación: 22/02/2024
• Nº Volúmenes: 1
• Idioma: Inglés