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Carl Benedikt Frey

Bio: Carl Benedikt Frey is an academic researcher from University of Oxford. The author has contributed to research in topics: Capital market & Intellectual property. The author has an hindex of 12, co-authored 26 publications receiving 4499 citations.

Papers
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Journal ArticleDOI
TL;DR: In this paper, a Gaussian process classifier was used to estimate the probability of computerisation for 702 detailed occupations, and the expected impacts of future computerisation on US labour market outcomes, with the primary objective of analyzing the number of jobs at risk and the relationship between an occupations probability of computing, wages and educational attainment.

4,853 citations

Journal ArticleDOI
TL;DR: In this paper, the authors examined the impacts of the launch of Uber on workers employed in conventional taxi services and found that incumbent taxi drivers experienced a relative earnings decline of about 10 percent subsequent to Uber's entry into a new market, while there were no significant effects on their labor supply.

152 citations

Book
18 Jun 2019
TL;DR: The Technology Trap as discussed by the authors takes a sweeping look at the history of technological progress and how it has radically shifted the distribution of economic and political power among society's members, showing that the immediate consequences of mechanization were devastating for large swaths of the population.
Abstract: "From the Industrial Revolution to the age of artificial intelligence, The Technology Trap takes a sweeping look at the history of technological progress and how it has radically shifted the distribution of economic and political power among society’s members. As Carl Benedikt Frey shows, the Industrial Revolution created unprecedented wealth and prosperity over the long run, but the immediate consequences of mechanization were devastating for large swaths of the population. Middle-income jobs withered, wages stagnated, the labor share of income fell, profits surged, and economic inequality skyrocketed. These trends, Frey documents, broadly mirror those in our current age of automation, which began with the Computer Revolution. Just as the Industrial Revolution eventually brought about extraordinary benefits for society, artificial intelligence systems have the potential to do the same. But Frey argues that this depends on how the short term is managed. In the nineteenth century, workers violently expressed their concerns over machines taking their jobs. The Luddite uprisings joined a long wave of machinery riots that swept across Europe and China. Today’s despairing middle class has not resorted to physical force, but their frustration has led to rising populism and the increasing fragmentation of society. As middle-class jobs continue to come under pressure, there’s no assurance that positive attitudes to technology will persist. The Industrial Revolution was a defining moment in history, but few grasped its enormous consequences at the time. The Technology Trap demonstrates that in the midst of another technological revolution, the lessons of the past can help us to more effectively face the present."

89 citations

13 Feb 2015
TL;DR: In this article, the authors highlight the key challenges, explore some of the new technology brought on by the digital age and set out an agenda for change, calling for long term thinking to mitigate the negative effects of an ever more automated and digital economy.
Abstract: Exploring trends in automation this report points to sluggish job creation caused partly by increasing automation, and argues that secular stagnation in the digital age can only be avoided by a shift towards inclusive growth. The authors highlight the key challenges, explore some of the new technology brought on by the digital age and set out an agenda for change, calling for long term thinking to mitigate the negative effects of an ever more automated and digital economy. Technology at Work marks the start of a new programme of research supported by Citi, the Oxford Martin Programme on Technology and Employment.

85 citations


Cited by
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Journal ArticleDOI
TL;DR: The COVID-19 Government Response Tracker (OxCGRT) as mentioned in this paper is a dataset that addresses the need for continuously updated, readily usable and comparable information on policy measures.
Abstract: COVID-19 has prompted unprecedented government action around the world. We introduce the Oxford COVID-19 Government Response Tracker (OxCGRT), a dataset that addresses the need for continuously updated, readily usable and comparable information on policy measures. From 1 January 2020, the data capture government policies related to closure and containment, health and economic policy for more than 180 countries, plus several countries' subnational jurisdictions. Policy responses are recorded on ordinal or continuous scales for 19 policy areas, capturing variation in degree of response. We present two motivating applications of the data, highlighting patterns in the timing of policy adoption and subsequent policy easing and reimposition, and illustrating how the data can be combined with behavioural and epidemiological indicators. This database enables researchers and policymakers to explore the empirical effects of policy responses on the spread of COVID-19 cases and deaths, as well as on economic and social welfare.

1,727 citations

Posted Content
TL;DR: A list of five practical research problems related to accident risk, categorized according to whether the problem originates from having the wrong objective function, an objective function that is too expensive to evaluate frequently, or undesirable behavior during the learning process, are presented.
Abstract: Rapid progress in machine learning and artificial intelligence (AI) has brought increasing attention to the potential impacts of AI technologies on society. In this paper we discuss one such potential impact: the problem of accidents in machine learning systems, defined as unintended and harmful behavior that may emerge from poor design of real-world AI systems. We present a list of five practical research problems related to accident risk, categorized according to whether the problem originates from having the wrong objective function ("avoiding side effects" and "avoiding reward hacking"), an objective function that is too expensive to evaluate frequently ("scalable supervision"), or undesirable behavior during the learning process ("safe exploration" and "distributional shift"). We review previous work in these areas as well as suggesting research directions with a focus on relevance to cutting-edge AI systems. Finally, we consider the high-level question of how to think most productively about the safety of forward-looking applications of AI.

1,569 citations

Journal ArticleDOI
TL;DR: The authors argue that the interplay between machine and human comparative advantage allows computers to substitute for workers in performing routine, codifiable tasks while amplifying the comparative advantage of workers in supplying problem-solving skills, adaptability, and creativity.
Abstract: In this essay, I begin by identifying the reasons that automation has not wiped out a majority of jobs over the decades and centuries. Automation does indeed substitute for labor�as it is typically intended to do. However, automation also complements labor, raises output in ways that leads to higher demand for labor, and interacts with adjustments in labor supply. Journalists and even expert commentators tend to overstate the extent of machine substitution for human labor and ignore the strong complementarities between automation and labor that increase productivity, raise earnings, and augment demand for labor. Changes in technology do alter the types of jobs available and what those jobs pay. In the last few decades, one noticeable change has been a "polarization" of the labor market, in which wage gains went disproportionately to those at the top and at the bottom of the income and skill distribution, not to those in the middle; however, I also argue, this polarization is unlikely to continue very far into future. The final section of this paper reflects on how recent and future advances in artificial intelligence and robotics should shape our thinking about the likely trajectory of occupational change and employment growth. I argue that the interplay between machine and human comparative advantage allows computers to substitute for workers in performing routine, codifiable tasks while amplifying the comparative advantage of workers in supplying problem-solving skills, adaptability, and creativity.

1,325 citations

Journal ArticleDOI
TL;DR: In this article, the authors present a state-of-the-art review of Industry 4.0 based on recent developments in research and practice, and present an overview of different opportunities for sustainable manufacturing in Industry 5.0.

1,276 citations

Posted Content
TL;DR: In this paper, the authors analyzed the effect of the increase in industrial robot usage between 1990 and 2007 on US local labor markets, and showed that robots may reduce employment and wages, and that the local labor market effects of robots can be estimated by regressing the change in employment and wage on the exposure to robots in each local labour market, defined from the national penetration of robots into each industry and the local distribution of employment across industries.
Abstract: As robots and other computer-assisted technologies take over tasks previously performed by labor, there is increasing concern about the future of jobs and wages. We analyze the effect of the increase in industrial robot usage between 1990 and 2007 on US local labor markets. Using a model in which robots compete against human labor in the production of different tasks, we show that robots may reduce employment and wages, and that the local labor market effects of robots can be estimated by regressing the change in employment and wages on the exposure to robots in each local labor market—defined from the national penetration of robots into each industry and the local distribution of employment across industries. Using this approach, we estimate large and robust negative effects of robots on employment and wages across commuting zones. We bolster this evidence by showing that the commuting zones most exposed to robots in the post-1990 era do not exhibit any differential trends before 1990. The impact of robots is distinct from the impact of imports from China and Mexico, the decline of routine jobs, offshoring, other types of IT capital, and the total capital stock (in fact, exposure to robots is only weakly correlated with these other variables). According to our estimates, one more robot per thousand workers reduces the employment to population ratio by about 0.18-0.34 percentage points and wages by 0.25-0.5 percent.

979 citations