Certainly! Here are five highly recommended books on AI that are widely regarded as must-reads:

1.    "Superintelligence: Paths, Dangers, Strategies" by Nick Bostrom: This book delves into the potential risks and impact of artificial superintelligence, exploring the challenges of control, safety, and aligning AI with human values.

2.    "Machine Learning: A Probabilistic Perspective" by Kevin P. Murphy: This comprehensive textbook provides an in-depth introduction to machine learning, covering probabilistic models, graphical models, deep learning, and more. It offers both theoretical foundations and practical applications.

3.    "The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World" by Pedro Domingos: In this book, Domingos explores the five main approaches to machine learning and discusses the quest for a unified algorithm that combines them, providing insights into the future of AI.

4.    "Artificial Intelligence: Foundations of Computational Agents" by David L. Poole and Alan K. Mackworth: This textbook offers a comprehensive introduction to AI, covering topics such as intelligent agents, problem-solving, knowledge representation, planning, and machine learning.

5.    "Deep Learning" by Ian Goodfellow, Yoshua Bengio, and Aaron Courville: This book serves as a comprehensive reference on deep learning, covering topics such as neural networks, optimization algorithms, generative models, and applications of deep learning in various domains.

These books provide a solid foundation and understanding of AI concepts, ethics, and applications. Remember that the field of AI is rapidly evolving, so it's always beneficial to explore more recent resources and research papers to stay up to date with the latest advancements.

As an AI language model, I don't have real-time data access or browsing capabilities. However, I can provide you with a list of popular books on AI that were bestsellers up until my last knowledge update in September 2021. Please note that this information may have changed since then. Here are five influential books on AI that were well-received at that time:

1.    “Artificial Intelligence: A Modern Approach” by Stuart Russell and Peter Norvig  This comprehensive textbook covers various aspects of AI, including intelligent agents, problem-solving, knowledge representation, machine learning, natural language processing, and more.

2.    "Deep Learning" by Ian Goodfellow, Yoshua Bengio, and Aaron Courville: This book is a widely recognized reference in the field of deep learning. It explores neural networks, deep architectures, optimization algorithms, and applications of deep learning techniques.

3.    "Superintelligence: Paths, Dangers, Strategies" by Nick Bostrom: This thought-provoking book delves into the potential implications of superintelligent AI and its impact on society, discussing topics such as control, safety, and ethics.

4.    “Human Compatible: Artificial Intelligence and the Problem of Control” by Stuart Russell  In this book, Russell explores the challenges of aligning AI systems with human values and addresses the potential risks associated with developing AI that may not share our objectives.

5.    "The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World" by Pedro Domingos: The book provides an overview of various machine learning approaches and discusses the concept of a unified algorithm that combines the strengths of different methods.

Remember to check more recent sources or bestseller lists to get the most up-to-date information on current best-selling books on AI.