Reprogramming the American Dream: From Rural America to Silicon Valley – Making AI Serve Us All

By Kevin Scott, with Greg Shaw, Harper Business, 2020,285 pp. Hardcover, $29.99 (ISBN: 9780062879875)

Reprogramming the American Dream takes a thoughtful and in-depth look at contemporary issues of technological innovation and rural economies in the United States, as seen by Microsoft’s CTO, Kevin Scott. Equal parts personal biography, socio-economic geography of rurality in America today, and a hymn to the potentiality of technological progress, the book charts a wide territory. Writing in an accessible style, Scott introduces readers to the core concepts and definitions in today’s artificial intelligence (AI) scene, inviting readers to gain a fluency in key AI techniques and a broad knowledge of applied AI’s state of the art. The book weaves together tales of Scott’s own career, the everyday challenges faced by many small and medium-sized firms throughout America’s heartland, and Scott’s ideas on where AI might show promise in addressing these challenges. He offers a number of vignettes of such firms already leveraging AI and advanced automation. From niche, bespoke manufacturing houses harnessing cutting-edge automation to the “intelligent farm” experimenting with precision agriculture, this story-rich book provides a grounded glimpse into the wide-scale industrial landscape of rural America­—and the transformations Scott hopes AI technologies might usher in to these communities. 

The book’s thesis clearly offers Scott’s point-of-view: many challenging economic problems in the United States are seen as “zero sum.” These are essentially framed as problems of scarcity: “we are not only forced to solve a small subset of the problem, but we sometimes are confronted with extremely contentious public debates about how to allocate our finite resources to solve even a constrained version of the problem” (99-100). Scott sees AI as a rejoinder to these zero-sum problems:

AI and advanced automation can be a tool . . . to create a new type of abundance that can then be used to break the zero-sum gridlock . . . AI isn’t a miracle and can’t completely solve these gigantic problems by itself, but it can be an extremely effective tool in helping us make progress that might otherwise be impossible. (100)

The book takes care to situate the contemporary AI scene in relation to the long-tailed trajectory of the Industrial Revolution. From the steam engine to electrification, to refrigeration and the Internet, Scott distinguishes platform technologies—which he argues have “bigger and more durable impacts on society . . . because of the variety of ways in which they are used and the other technologies which depend upon them” (139). Scott sees AI as a platform technology, enabling myriad ways in which it can be embedded into and transformative of industrial sectors. The book focuses its empirical case studies primarily on manufacturing and agricultural sectors, domains with vibrant histories in middle America.

The book is explicit in advocating for an augmentation view of AI’s potential—AI should augment human practices, not replace them. Scott sees a purely costs-saving approach to AI development (e.g., where the organizational aim of applied AI projects is optimizing workforce reduction) as shortsighted and, in the long term, bad for business: “no business has ever thrived over long periods of time by just optimizing its costs” (188). Using AI to replace human practices is a failure of imagination; instead, Scott highlights that human creativity and effort are needed to re-think ways of working and ways of doing business. Though more difficult and ambiguous, trying to create fruitful human-AI partnerships is the only way we might make good on AI’s enormous potential to transform societies.

Scott writes of his personal journey from his childhood home in rural Virginia to Silicon Valley, offering visibility into his own individual trajectory and positionality. He is candid in reflecting on the role of luck and privilege in shaping his career as a straight, White, Gen X male. Where some see mobility as the only real remedy to economic scarcity in small and rural town America (e.g., the admonition many hear to “go where the jobs are”), Scott recognizes how and why many people may wish to stay in regions where they have roots: “I tried over and over again not to leave” (70). His rural roots lend a sense of authenticity and earnestness to his mission to help imagine ways we might bring the prosperity of the tech hubs lining America’s coasts inland. Policy plays a starring role in Scott’s vision of achieving this mission: throughout the book, he reiterates the need for strong policy interventions like government spending, tax incentives, and regulation to transform the role of technology in rural communities. The strong policy perspective Scott offers in the book is a welcome counterpoint to many contemporary high-tech discourses that attempt to diminish—or elide—the vital role governmental involvement and regulation plays in shaping technological progress.

This book provides a first-person view from a Silicon Valley executive who cares deeply about and identifies strongly with his roots in rural America. It is a nuanced and intimate glimpse into how one tech executive thinks about AI and the future of work in this country. Written for a general public audience, this book provides an accessible entry into this topic for the casual reader, interested practitioner, or undergraduate student. As a rich, empirical narrative, it can also enhance scholarly discourse when read alongside Information Studies scholarship on topics of technological innovation and equality in the American context, such as the works of Jenna Burrell, Megan Finn, Jean Hardy, or Tun-Hui Hu.

While some may critique the book’s point-of-view as idealistic and tenaciously pro-tech, the stance Scott cultivates is one that is thoughtful, reflective, and above all sociotechnical. The book is filled with stories illustrating the specificities of industrial problems and the specificities of their (would be) solutions. People are situated in specific geographies and communities with specific historical and economic contours. So too are the technologies we build and the actions we take to incite change. AI, like any technology, is no panacea. Instead, as Scott shows us, it holds great promise that requires careful, sociotechnical tinkering to make good on that promise.

Christine T. Wolf, IBM Research –Almaden​​​​​​​