Bi-directionality in Human-AI Collaborative Systems

Chapter 1 Introduction to bidirectionality in human–AI collaborative systems<br>Chapter 2 Foundational approaches to post-hoc explainability for image classification<br>Chapter 3 Explaining poisoned AI models<br>Chapter 4 Desirability vs. feasibility: a research through design inquiry of explainable AI<br>Chapter 5 Credition, uncertainty, consciousness, and communication<br>Chapter 6 On the principles and effectiveness of gamification in bidirectional artificial intelligence and explainable AI<br>Chapter 7 Employing Kolmogorov–Arnold network for man–machine collaboration<br>Chapter 8 Collaborative communication for unnamable risks: a creative writing approach to aligning human–machine situation models in an open world<br>Chapter 9 Not all explanations are created equal: investigating the pitfalls of current XAI evaluation<br>Chapter 10 A mixture-of-experts flock: examining expert influence<br>Chapter 11 On replacing humans with human simulators in human-in-the-loop systems built to interact with humans<br>Chapter 12 Addressing procrastination and improving task completion efficiency through agent-based interventions<br>Chapter 13 Navigating the sociotechnical labyrinth: dynamic certification for responsible embodied AI<br>Chapter 14 Searching XAI collaborating with manager: bidirectional learning for human-tech applications<br>Chapter 15 Natural perception-based control types for human/machine systems<br>Chapter 16 Hybrid forums as a means to perceive bidirectional risks<br>Chapter 17 Credit assignment: challenges and opportunities in developing human-like learning agents<br>Chapter 18 Human–machine teams: advantages afforded by the quantum-likeness of interdependence