Wharton@Work

August 2019 | 

A Human’s Guide to Machine Intelligence: How Algorithms Are Shaping Our Lives and How We Can Stay in Control


A Human's Guide to Machine Intelligence: How Algorithms Are Shaping Our Lives and How We Can Stay in Control

If you recently applied for a mortgage or a job, made a purchase on Amazon, or watched a movie on Netflix, you interacted with an algorithm. Some of them simply make suggestions, while others make decisions for us. Algorithms can drive cars, make investments, set insurance premiums, and offer doctors diagnostic guidance.

In his new book, Wharton professor Kartik Hosanagar says that while they can make our lives easier, “they are also adversely affecting us in ways that are currently beyond our control.”

Most of us are familiar with at least a few cautionary tales, since they tend to make headlines. Amazon’s gender-biased recruiting algorithm, Uber’s self-driving car that killed a pedestrian, and IBM’s Watson Health that gave potentially fatal cancer treatment recommendations are some of the best known. But, says Hosanagar, “AI-based algorithms are here to stay. To discard them now would be like Stone Age humans deciding to reject the use of fire because it can be tricky to control.”

In A Human’s Guide to Machine Intelligence (Viking, 2019), Hosanagar answers three related questions: (1) What causes algorithms to behave in unpredictable, biased, and potentially harmful ways? (2) If algorithms can be irrational and unpredictable, how do we decide when to use them? (3) How do we, as individuals who use algorithms in our personal or professional lives and as a society, shape the narrative of how algorithms impact us?

This important new book will deepen your understanding of algorithms and the risks associated with algorithmic decision making. Hosanagar explains how we can hold algorithms accountable: a user’s “bill of rights” clarifying the level of transparency, “explainability” (knowing why algorithms decide what they decide), and control we can and should expect from the algorithms we use. As he notes, having a “vague notion of how autonomous algorithms function is no longer sufficient for responsible citizens, consumers, and professionals.” We don’t need to become machine learning specialists, but to limit and control their power over our lives we do need a solid understanding of the big picture. A Human’s Guide to Machine Intelligence more than fills the bill.