A Wharton professor and tech entrepreneur examines how algorithms and artificial intelligence are starting to run every aspect of our lives, and how we can shape the way they impact us
Through the technology embedded in almost every major tech platform and every web-enabled device, algorithms and the artificial intelligence that underlies them make a staggering number of everyday decisions for us, from what products we buy, to where we decide to eat, to how we consume our news, to whom we date, and how we find a job. We've even delegated life-and-death decisions to algorithms--decisions once made by doctors, pilots, and judges. In his new book, Kartik Hosanagar surveys the brave new world of algorithmic decision-making and reveals the potentially dangerous biases they can give rise to as they increasingly run our lives. He makes the compelling case that we need to arm ourselves with a better, deeper, more nuanced understanding of the phenomenon of algorithmic thinking. And he gives us a route in, pointing out that algorithms often think a lot like their creators--that is, like you and me.
Hosanagar draws on his experiences designing algorithms professionally--as well as on history, computer science, and psychology--to explore how algorithms work and why they occasionally go rogue, what drives our trust in them, and the many ramifications of algorithmic decision-making. He examines episodes like Microsoft's chatbot Tay, which was designed to converse on social media like a teenage girl, but instead turned sexist and racist; the fatal accidents of self-driving cars; and even our own common, and often frustrating, experiences on services like Netflix and Amazon. A Human's Guide to Machine Intelligence is an entertaining and provocative look at one of the most important developments of our time and a practical user's guide to this first wave of practical artificial intelligence.
Hosanagar, a Wharton professor of technology and digital business, attempts, with mixed success, to explain his field to a lay audience impacted by "algorithmic decision-making." He covers overly familiar terrain to begin with, discussing the increasing role of artificial intelligence in online commerce, social media, and news reporting to demonstrate the topic's importance. Where he adds value is in using his expertise to discuss how algorithms work, and how the designs of some, such as Amazon and Netflix's personalization algorithms, reduce diversity of choice for consumers. The inherent complexity of algorithms, however, presents an obstacle to comprehension that Hosanagar never fully overcomes. In a concluding section, Hosanagar proposes a bill of rights for people affected by algorithms (that is to say, almost everyone), a well-intentioned idea that comes across as impractical. Making accessible to the average person a "description of the data used to train" algorithms and "an explanation regarding the procedures used by the algorithms," to pick two of his suggestions, would be a daunting task. Nonetheless, Hosanagar deserves credit for valiantly attempting, throughout this thoughtful treatise, to widen understanding of a technology central to modern society.