Workers Machines And Economic Growth

Why the United States lags behind other industrialized countries in sharing the benefits of innovation with workers and how we can remedy the problem. The United States has too many low-quality, low-wage jobs. Every country has its share, but those in the United States are especially poorly paid and often without benefits. Meanwhile, overall productivity increases steadily and new technology has transformed large parts of the economy, enhancing the skills and paychecks of higher paid knowledge workers. What’s wrong with this picture? Why have so many workers benefited so little from decades of growth? The Work of the Future shows that technology is neither the problem nor the solution. We can build better jobs if we create institutions that leverage technological innovation and also support workers though long cycles of technological transformation. Building on findings from the multiyear MIT Task Force on the Work of the Future, the book argues that we must foster institutional innovations that complement technological change. Skills programs that emphasize work-based and hybrid learning (in person and online), for example, empower workers to become and remain productive in a continuously evolving workplace. Industries fueled by new technology that augments workers can supply good jobs, and federal investment in R&D can help make these industries worker-friendly. We must act to ensure that the labor market of the future offers benefits, opportunity, and a measure of economic security to all.

A timely investigation of the potential economic effects, both realized and unrealized, of artificial intelligence within the United States healthcare system. In sweeping conversations about the impact of artificial intelligence on many sectors of the economy, healthcare has received relatively little attention. Yet it seems unlikely that an industry that represents nearly one-fifth of the economy could escape the efficiency and cost-driven disruptions of AI. The Economics of Artificial Intelligence: Health Care Challenges brings together contributions from health economists, physicians, philosophers, and scholars in law, public health, and machine learning to identify the primary barriers to entry of AI in the healthcare sector. Across original papers and in wide-ranging responses, the contributors analyze barriers of four types: incentives, management, data availability, and regulation. They also suggest that AI has the potential to improve outcomes and lower costs. Understanding both the benefits of and barriers to AI adoption is essential for designing policies that will affect the evolution of the healthcare system.

This book examines the current state of the technologically-caused unemployed, and attempts to answer the question of how to proceed into an era beyond technological unemployment. Beginning with an overview of the most salient issues, the experts collected in this work present their own novel visions of the future and offer suggestions for adapting to a more symbiotic economic relationship with AI. These suggestions include different modes of dealing with education, aging workers, government policies, and the machines themselves. Ultimately, they lay out a whole new approach to economics, one in which we learn to merge with and adapt to our increasingly intelligent creations.

Why the United States lags behind other industrialized countries in sharing the benefits of innovation with workers and how we can remedy the problem. The United States has too many low-quality, low-wage jobs. Every country has its share, but those in the United States are especially poorly paid and often without benefits. Meanwhile, overall productivity increases steadily and new technology has transformed large parts of the economy, enhancing the skills and paychecks of higher paid knowledge workers. What’s wrong with this picture? Why have so many workers benefited so little from decades of growth? The Work of the Future shows that technology is neither the problem nor the solution. We can build better jobs if we create institutions that leverage technological innovation and also support workers though long cycles of technological transformation. Building on findings from the multiyear MIT Task Force on the Work of the Future, the book argues that we must foster institutional innovations that complement technological change. Skills programs that emphasize work-based and hybrid learning (in person and online), for example, empower workers to become and remain productive in a continuously evolving workplace. Industries fueled by new technology that augments workers can supply good jobs, and federal investment in R&D can help make these industries worker-friendly. We must act to ensure that the labor market of the future offers benefits, opportunity, and a measure of economic security to all.

In recent decades digital devices have reshaped daily life, while tech companies’ stock prices have thrust them to the forefront of the business world. In this rapid, global development, the promise of a new machine age has been accompanied by worries about accelerated joblessness thanks to new forms of automation. Jason E. Smith looks behind the techno-hype to lay out the realities of a period of economic slowdown and expanding debt: low growth rates and an increase of labor-intensive jobs at the bottom of the service sector. He shows how increasing inequality and poor working conditions have led to new forms of workers’ struggles. Ours is less an age of automation, Smith contends, than one in which stagnation is intertwined with class conflict.

The big stories -- The skills of the new machines : technology races ahead -- Moore's law and the second half of the chessboard -- The digitization of just about everything -- Innovation : declining or recombining? -- Artificial and human intelligence in the second machine age -- Computing bounty -- Beyond GDP -- The spread -- The biggest winners : stars and superstars -- Implications of the bounty and the spread -- Learning to race with machines : recommendations for individuals -- Policy recommendations -- Long-term recommendations -- Technology and the future (which is very different from "technology is the future").