Advances in Human-AI Collaboration

Preface

Advances in Human–AI Collaboration considers how humans and AI systems work in tandem. This is critical as we move toward an increasingly integrated technology landscape. The knowledge helps ensure successful deployment and optimal benefits of AI applications in various settings. The chapters contain pertinent concepts and fundamentals to enable an understanding of human–AI collaboration opportunities, challenges, and applications. Illustrations of human–AI interaction are contained throughout the chapters. Human interaction with intelligent automation is outlined in Chapter 1. Limitations, trustworthiness, and ability to see inside AI’s inner workings can help users assess when human judgment is needed and which decisions are safe to leave to AI. Interaction fundamentals are outlined in Chapters 2 and 3.

Design guidelines and user experience (UX) principles are introduced in Chapter 4 about Guidelines for Human–AI Interaction and UX. Examples of human intelligence vs. AI are considered in Chapter 5. AI-supported classrooms have shown improved learning and engagement. Teachers are working with AI tutors. Simulations can reduce the costs of training, and real-time analytics can support measures of learning. Training with AI support is described in Chapter 6. Mental models in human–AI collaboration and human–AI teaming are discussed in Chapters 7 and 8. Machine learning and predictive accuracy may not be enough. Model transparency and audits can help track how predictions ...