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Robot-proof : higher education in the age of artificial intelligence
Aoun J., The MIT Press, Cambridge, MA, 2017. 216 pp. Type: Book (978-0-262037-28-0)
Date Reviewed: Jun 14 2018

The book proposes a new model of higher education that goes beyond the classical undergraduate/graduate model and should be a better fit for the fabric of a modern technologically driven society. It consists of five chapters.

The first chapter serves as motivation for and analysis of the proposed model. The author analyzes the impact of technological development on the labor force from various perspectives and in the context of education as a vital element of the social fabric. He concludes that, in the modern digital economy, students have to go beyond “knowing things” and instead offer a high level of creativity and flexibility for thinking differently than machines.

The second chapter extends the ideas mentioned in the first from the perspective of labor relations. The author discusses how technology transforms the workplace, changing the level and type of skills needed even in areas traditionally isolated from automation. The most interesting sections are “Working with Ideas” and “Critical and Systems Thinking.” In the former, the author shows (via various examples) that technical expertise and good reasoning skills are not enough for success in an artificial intelligence (AI)-infused world; other qualities such as temperament, collaborative spirit, critical thinking, and so on are also important. In the latter section, the author discusses the role of systems and critical thinking. The former involves seeing across areas where machines might be able to comprehend, and the latter is a cornerstone of human creativity.

In chapters 3 and 4, the core of the book, the author defines his ideas for a new learning model. Chapter 3 shows that the current US education system is still focused on convergent thinking because it was designed to meet the needs of 19th and 20th century economies. In the 21st century, however, a proper education must include the development of a set of literacies: technical literacy, data literacy, and human literacy. The chapter provides a detailed discussion of the impact of each of these. Further, the author discusses the role of cognitive capacities such as critical thinking, systems thinking, entrepreneurship, and cultural agility in the context of changes in the educational system. The author argues that education in “humanics” based on the three aforementioned literacies is a step beyond traditional learning and teaching schemes. In chapter 4, the focus is on experimental learning, which in higher education means work-study jobs, research opportunities, and internships.

In the last chapter, “Learning for Life,” the author argues for lifelong learning and discusses what this means for colleges, which have to become lifelong learning centers. This includes implementing customized and personalized models of learning, customized models of delivery, and so on.

Overall, the text is easy to read and the examples are helpful. The book will be useful for faculty and researchers actively engaged in the education process at the university level. Most importantly, the book conveys ideas that may change perspectives and mindsets, and thus encourage researchers to develop an education model free of AI fears.

More reviews about this item: Amazon, Goodreads

Reviewer:  Stefka Tzanova Review #: CR146086 (1808-0421)
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