Understanding The Impact Of Machine Learning On Labor And Education
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Understanding the Impact of Machine Learning on Labor and Education
This book provides a novel framework for understanding and revising labor markets and education policies in an era of machine learning. It posits that while learning and knowing both require thinking, learning is fundamentally different than knowing because it results in cognitive processes that change over time. Learning, in contrast to knowing, requires time and agency. Therefore, “learning algorithms”—that enable machines to modify their actions based on real-world experiences—are a fundamentally new form of artificial intelligence that have potential to be even more disruptive to labor markets than prior introductions of digital technology. To explore the difference between knowing and learning, Turing’s “Imitation Game,”—that he proposed as a test for machine thinking—is expanded to include time dependence. The arguments presented in the book introduce three novel concepts: (1) Comparative learning advantage: This is a concept analogous to comparative labor advantage but arises from the disparate times required to learn new knowledge bases/skillsets. It is argued that in the future, comparative learning advantages between humans and machines will determine their division of labor. (2) Two dimensions of job performance—expertise and interpersonal: Job tasks can be sorted into two broad categories. Tasks that require expertise have stable endpoints, which makes these tasks inherently repetitive and subject to automation. Tasks that are interpersonal are highly context-dependent and lack stable endpoints, which makes these tasks inherently non-routine. Humans compared to machines have a comparative learning advantage along the interpersonal dimension, which is increasing in value economically. (3) The Learning Game is a time-dependent version of Turing’s “Imitation Game.” It is more than a thought experiment. The “Learning Game” provides a mathematical framework with quantitative criteria for training and assessing comparative learning advantages. The book is highly interdisciplinary—presenting philosophical arguments in economics, artificial intelligence, and education. It also provides data, mathematical analysis, and testable criteria that researchers in these fields will find of practical use. The book calls for a rethinking of how labor markets operate and how the education system should prepare students for future jobs. It concludes with a list of counterintuitive recommendations for future education and labor policies that all stakeholders—employers, employees, educators, students, and political leaders—should heed.
De Gruyter Handbook of Media Technology and Innovation
Author: Richard A. Gershon
language: en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date: 2025-01-27
The De Gruyter Handbook of Media Technology and Innovation brings together scholars from around the world to provide key insights on emerging technology trends and issues related to the fields of media management, information technology, product design planning and digital lifestyle. This handbook is about the power of good ideas. It’s about those business enterprises, government planners, educators and entrepreneurs that have harnessed the power of good ideas to become real difference makers in the world we live in. Keeping pace with fast paced technology change requires ongoing assessment and reassessment of the media management and technology fields to address important questions and emerging issues. A major premise of this book is that given the complex and ever-changing state of media technology – we have a responsibility and obligation to engage in a broader interdisciplinary dialogue whose purpose is to understand the current and future state of media technology and innovation as well as to appreciate the social impact that such technologies have on business, education and the general public. Forecasting the future, as any weatherperson or stock broker can tell you, is a risky business. But in this book we use the phrase "the creative next step" as a way to talk about the future and what we can expect in terms of the opportunities and challenges going forward.
Working for a Future
This book builds on the success of “Working to Learn" (Palgrave Macmillan, 2020) by focusing on the future of work and how young people, especially low-income young people and young people of color, are pursuing college and career goals through work-based learning experiences, yet encountering an increasingly racially and socioeconomically stratified labor market and educational system. Through policy analysis and case studies both from US and abroad, the authors will present the argument for why these models warrant revisitation, innovation, and investment, and elevate profiles of young workers, nonprofits, corporate partners, and governments today who are using work opportunities to open doors once closed.