At long last and by popular demand, we have kicked off our seventh year of Doody’s Special Topics Lists with our first on artificial intelligence. 

Though an AI book list had been considered multiple times in the past, our Editorial Board decided now is the time to experiment with providing health sciences libraries a starting place for building collections that observe the intersection between AI and the health sciences. Thus, AI Intersections was born, and we are very excited to share this inaugural list in what will become a recurring series of DSTLs over the coming years. 

This first AI Intersections DSTL focuses on books that center discussions of AI literacy and ethics to help build a foundation across stakeholders on the basic principles of AI and the ethical concerns and questions its use raises, both in health contexts and more broadly. The ubiquity of AI discussions throughout the health information landscape and the race to develop and promote AI tools by information providers has begun creating a chasm between those that are AI proficient and those that are not, and between those that adopt it and those that reject it, with a wide variety of voices caught somewhere in the middle. Such a rapidly growing divide necessitates a unifying and foregrounding knowledge and insight, especially for health professionals and students whose main focus will always be, or should always be, their studies, research, and patients. 

In truth, developing a book list like this one is much like chasing a thunderstorm. While you can get close to the lightning and feel the rain, the storm keeps moving and it eventually outpaces you or fizzles out into oblivion. The capacities of, ways to engage with, and potential impacts of AI are evolving at a rapid pace, and published book literature can only capture so much at a time. As such, this DSTL accomplishes two goals quite well. First, it identifies historical works outside of the AI mainframe to offer context for contemporary AI-centric works to create a consciousness around the advent and adoption of technologies that have previously changed our world. Second, it demonstrates the dearth of books that specifically address AI literacy and offers a clarion call to publishers and advocates to continue producing resources that ensure no one is left behind as they chase the AI storm. 

Future AI Intersections DSTLs will pick up where this one leaves off by covering AI’s role in health sciences education, clinical decision-making, and patient care and education. Until then, we are thrilled to offer this foundational list, and hope librarians find it useful for their work, their collections, and their library users. All told, the list comprises 36 titles from 20 publishers. The list prices for these titles range from $14.99 to $600, with an average cost of $90.58. Below are five Doody’s reviews of some of the books on the list you should check out:  

Generative Artificial Intelligence in Health and Medicine: Opportunities and Responsibilities for Transformative Innovation 

“This book is a very helpful and needed entry on the medical use of generative artificial intelligence. As opposed to a wide canvas of current use cases of generative artificial intelligence…this book discusses a much-needed framework for approaching the creation and deployment of new technologies in a way that is both effective and equitable.” Aaron Saguil, MD, MPH, FAAFP  

Preparing Healthcare Workers for an AI-Driven Workplace 

“This short book addresses five key aspects of critical thinking and outlines ways healthcare workers can excel in critical thinking and reasons it is needed to succeed in the future of health care which increasingly relies on artificial intelligence….I recommend this book as a valuable resource to healthcare workers seeking a refresher on critical thinking and further explanation of its impact on AI.” Mary Heitschmidt, PhD, APRN, CCRN, FAHA 

Artificial Intelligence and Healthcare: The Impact of Algorithmic Bias on Health Disparities 

“This book is an effective starting place for anyone interested in getting started in learning about AI’s use in healthcare. It is effective at teaching the basics concerning AI, its creation, possible ethical pitfalls in its use, and current policy surrounding it both in the United States and the European Union.” Chad Quilling, DO Candidate