Co-Intelligence: Living and Working with AI

In the rapidly evolving landscape of healthcare technology, Co-Intelligence: Living and Working with AI, by Ethan Mollick, Ph.D. (an associate professor of management and academic director of Wharton Interactive, Wharton School, University of Pennsylvania), is a timely and insightful exploration of the symbiotic relationship between humans and artificial intelligence (AI). While not specifically tailored for the medical field or anesthesiology, this book offers valuable perspectives that may resonate deeply with the challenges and opportunities facing anesthesiology and perioperative medicine. The author brings his expertise in innovation to bear on the complex topic of AI integration. His approach is both pragmatic and forward-thinking, providing a framework for understanding and leveraging AI across various domains, including health care. The book is structured around four key rules for co-intelligence, which are presented as guiding principles for effective human–AI collaboration. These rules offer a roadmap for anesthesiologists and perioperative clinicians to consider when seeking to navigate the AI possibilities. The first rule, “always invite artificial intelligence to the table,” encourages practitioners to actively engage with AI tools in their daily practice. This aligns well with the growing trend of AI integration in anesthesiology, where AI-driven systems are increasingly being used for patient monitoring, perioperative risk prediction, and delivering personalized anesthetic care. The author emphasizes the need to understand that AI’s “jagged frontier”—its varying capabilities across different tasks—is particularly relevant in a field in which precision and safety are paramount. The second rule, “be the human in the loop,” may resonate strongly with medical practice considerations. It underscores the irreplaceable role of human judgment, empathy, and compassion in patient care, while acknowledging the power of augmenting the clinician with AI. In anesthesiology, where split-second decisions can have critical consequences, this balance between human expertise and AI support is crucial. The author’s insights can help clinicians navigate this delicate interplay, ensuring that AI enhances rather than replaces human decision-making. The third rule, “treat artificial intelligence like a person (but tell it what kind of person it is),” offers an intriguing perspective on how to optimize AI interactions. In the context of anesthesiology and perioperative medicine, the third rule could be interpreted to mean that more effective use of AI-driven clinical decision support systems, tailoring their outputs to specific clinical scenarios or patient populations, can be employed. Anesthesiology has an opportunity to help define what kind of AI tools and integrations into clinical practice would optimize perioperative care. The fourth rule, which emphasizes the importance of developing flexible policies and regulations for AI, is particularly pertinent to anesthesiology and perioperative medicine. As AI systems become more prevalent in anesthesia practice, there is a growing need for ethical guidelines and regulatory frameworks that can keep pace with technological advancements. Anesthesiology and perioperative clinicians need to also create new teams and expertise around how to regulate the ethical and practical use of AI. Like generations prior, when new technology or medication innovations required the expert input of clinicians for safe and effective care, the AI revolution in health care will also require a serious engagement across all specialties. Throughout the book, the author strikes a balance between optimism about AI’s potential and caution about its limitations. This nuanced approach is especially valuable in anesthesiology, where the stakes are high and the margin for error is slim. The book’s discussion of AI’s role in enhancing creativity and innovation could inspire new approaches to anesthesiology, perioperative care, research, quality improvement, and innovations that straddle multiple areas of expertise that have yet to be considered. One of the book’s strengths is its exploration of AI as a “connection machine,” capable of linking disparate ideas in meaningful ways. This concept has exciting implications for anesthesiology and health care at large, potentially accelerating the discovery of new anesthetic practices and treatment protocols or optimizing the risk profile of complex patients to reduce perioperative complications. The author’s examination of AI’s impact on the future of work is particularly relevant. Although not discussed specifically, the author’s framework of considering the future of work is a critical one for clinicians and leaders to consider. As AI systems become more sophisticated in tasks such as monitoring vital signs, predicting adverse events, and streamlining the perioperative care of complex patients, the role of anesthesiologists may evolve.1,2 The author’s insights can help clinicians prepare for this shift, focusing on areas in which human expertise remains irreplaceable while leveraging AI to enhance efficiency, scale the individual and team workforce, and optimize patient outcomes. The book also addresses the critical issue of AI alignment—ensuring that AI systems serve human goals and values. In anesthesiology, in which patient safety is paramount, this discussion takes on added significance. The author’s call for public dialogue on the ethical implications of AI development resonates with ongoing debates in medical ethics regarding the use of AI in clinical decision-making. While Co-Intelligence is not specifically written for healthcare professionals, its broad applicability allows anesthesiologists to draw valuable lessons and adapt them to their specific context. The book’s accessible style and concrete examples make it a valuable resource for clinicians and health system leaders at all levels of AI familiarity. However, readers should be aware that the rapid pace of AI development may render some of the book’s specific examples outdated. Nevertheless, the underlying principles and frameworks presented remain adaptable and important to consider in practice. In conclusion, Co-Intelligence offers a thought-provoking and practical framework to living and working with AI that is highly relevant to the field of anesthesiology. As AI continues to transform perioperative care, the author’s insights provide a valuable framework for embracing these changes while maintaining the human-centric approach that is at the heart of medical practice. The book can challenge all of us to think critically about how anesthesiology and perioperative medicine can leverage AI to enhance patient care, streamline workflows, augment the healthcare work force, and drive innovation. For anesthesiologists and perioperative clinicians navigating the AI revolution, Co-Intelligence offers a compelling vision of a future when human expertise and artificial intelligence work in harmony. It is a recommended read for those seeking to understand and harness the transformative potential of AI in anesthesiology and perioperative medicine. Competing Interests Dr. Tan has received research grant funding from the Foundation for Anesthesia Education and Research (Schaumburg, Illinois), the Anesthesia Patient Safety Foundation (Rochester, Minnesota), and the Southern California Environmental Health Sciences Center (Los Angeles, California). He consults for GE Healthcare (Chicago, Illinois), Edwards Lifesciences (Irvine, California), and Medtronic (Minneapolis, Minnesota).