Testing the Automation Revolution Hypothesis (original) (raw)
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Although the effects of automation on the future of work have received considerable attention, little research has been conducted on the costs of this technological transformation for different populations of workers. This article makes an important contribution as one of the first to analyze the intersectional effects of workforce automation across race and gender in the United States. Multilevel survey data models are employed using two distinct measures of automation job displacement risk for over 1.4 million Americans across 385 occupations. This research demonstrates that the intersection of race and gender matters for individual automation risks. Education, age, disability, and nativity are also significant. These findings indicate that labor market outcomes of job automation will be based not only on differences in human capital but critically on socially constructed identities as well.
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New technologies offer employers the ability to replace tasks done by human labour with those done by machines. There are challenges for both employers and employees, as employers look for strategies for the implementation of automation technologies and employees may have concerns about their employment being threatened by automation technologies. In this research, we analyse data of over 500 Bulgarians to learn about how they perceive the automation of their job. The analysis finds that there are segments of the population defined by demographics and attitudes that are more fearful of the automation of their jobs than others. Additionally, we see that attitudes towards the dehumanizing effects of automation, peer-pressure, technical expertise of the respondent, and a person’s self-perception of professionalism are the main drivers of the fear of automation. Finally, the paper evaluates respondents’ attitudes towards various individual, corporate and social solution to automation fe...
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International Journal of Management and Social Science Research Review, 2017
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SocArXiv
A study done by the United States Bureau of Labor Statistics found that of men ages 25 to 54, 13.2% were without work (Eberstadt). The British Broadcasting Company (BBC) believes this can be attributed to the increased use of robots—specifically in the manufacturing industry. Since 2000, industrial robots have replaced 1.7 million manufacturing jobs worldwide, and of these 1.7 million jobs, 260,000 were lost in the United States (Robots’ 'to replace up to 20 million factory jobs' by 2030) displaying the massive contribution automation has had on America’s unemployment crisis. According to Workism Is Making Americans Miserable, blue-collar jobs produce tangible products such as coal steel rods, and houses (Thompson) allowing manufacturers to easily replace them with more economically efficient robots. When 1,896 experts were asked the following question, “Will networked, automated, artificial intelligence (AI) applications and robotic devices have displaced more jobs than the...
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XIX international scientific conference. London. Great Britain.
Most discussions surrounding artificial intelligence and automation pivot around a fundamental question: do these advancements create a landscape ripe with new opportunities, or do they spell doom for traditional employment? In an era where machines increasingly augment or replace human tasks, we must scrutinize the intricate balance between innovation and workforce displacement. This exploration researchs into varied perspectives on how these technological revolutions could reshape jobs, economies, and our very understanding of work as we know it.
Wage Against The Machine Addressing the outflow of jobs to AI-based Automation
— The advent of Artificial Intelligence (AI) has led to the reduction of human dependency in the workforce. While similar to the increase of machine dependency during the height of Industrialization Period, the inclusion of AI requires less and less human intervention. This may lead to loss of jobs for humans, a reorganization of human role in the industry or a new shift in paradigm may lead to an economical and lifestyle change. This paper discusses the historical and future trend of technological unemployment, specifically with the advancement of AI. This includes observing historical evidences and dissecting predictions by experts and prominent fiction writers.
2018
Financial services jobs could be relatively vulnerable to automation in the shorter term, while transport jobs are more vulnerable to automation in the longer term 4.1. Total automation rates across industries 4.2. Impact on industries over time 4.3. Drivers of differences between industries 4.4. Which sectors are likely to see the largest jobs gains? 5. Which occupations could see the highest rates of automation? 5.1. Total automation risk across occupation categories 5.2. Impact over time by occupation 5.3. Drivers of differences between occupations 5.4. Composition of industries by occupational category 6. Why does the potential rate of job automation vary by type of worker? 6.1. Total automation risk across workers 6.2. Potential automation rates by education level 7. What are the public policy implications? 7.1. Education and skills 7.2. Job creation through increased public and private investment 7.3. Enhancing social safety nets 8. Implications for business: constraints, opportunities and responsibilities 8.1. What constraints will need to be overcome to realise benefits for business? 8.2. AI's impact on company value chains 8.3. AI and healthcare provision 8.4. Businesses need to help workers retrain and adapt to new technologies 8.5. Conclusion Annex-technical methodology