Heartificial Empathy is a deep, multi-faceted exploration of empathy, its role in business and, more specifically, its potential in the future of machine intelligence. Dial opens the book by examining the growing need for empathy in general then quickly transitions into a comprehensive framework for understanding it from both an interpersonal and a scientific perspective. From there, he moves into the role of empathy in an organizational setting and, finally, crescendos into the heart of the book’s central message, which focuses on the potential for prioritizing empathy as it relates to artificial intelligence. The book is filled with theoretical knowledge that Dial puts into perspective using case studies, graphics, Twitter posts, and his own personal ethics. The book also includes illustrations from Joel Anderson Waithe, which go even further to bring to life the sense of empathy for which Dial advocates so strongly.
Empathy is a concept that everyone is familiar with, but it looks different from person to person. As such, the term is often used in a variety of contexts that highlight subtle differences in what empathy can mean to the individual. At the same time, it is a well-studied psychological phenomenon that is tied up with academic frameworks that offer more concrete but less accessible definitions. Between these two worlds, Dial manages to approach the subject with a sense of clarity, poise and relatability that ensures all readers can follow him into his central thesis. Indeed, his framework for empathy in itself offers great value that stands on its own; in other words, Heartificial Empathy would be a worthwhile read even if it were limited to understanding empathy and its necessary role in organizational settings. His perspective on machine learning is what makes the book ground breaking, but his ability to put his message into perspective is, by far, the book’s most compelling feature.
At times, Dial’s aims for the future of AI read, perhaps, a bit idealistic; but the urgency of his message and the comprehensiveness of its delivery work together to establish a resounding reminder that, if a quality so fundamentally human as empathy feels out of reach as an industry norm, then we must need it now more than ever. Of course, Dial’s vision for empathic AI is far more readily accessible to his peers and to anyone who is already tuned into the exciting developments in AI over the last several years; but he also makes a thoughtful and very well executed structural choice to cater his message to readers who are coming to the book from a business standpoint by leading with his framework for understanding empathy and its role in organizational practice and making a compelling call to action before examining how these principles play into the future of AI more specifically.
Heartificial Empathy is a must-read for anyone interested in business, AI, or even simply the human condition.
