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@article{marcin_economic_nodate,
title = {Economic impacts of artificial intelligence},
abstract = {Artificial intelligence plays an increasingly important role in our lives and economy and is already having an impact on our world in many different ways. Worldwide competition to reap its benefits is fierce, and global leaders – the US and Asia – have emerged on the scene.},
language = {en},
author = {Marcin, SZCZEPANSKI},
keywords = {AI},
file = {Marcin - Economic impacts of artificial intelligence.pdf:C\:\\Users\\jonas\\Zotero\\storage\\QCQSJAZD\\Marcin - Economic impacts of artificial intelligence.pdf:application/pdf},
}
@article{ernst_economics_nodate,
title = {The economics of artificial intelligence: {Implications} for the future of work},
abstract = {The current wave of technological change based on advancements in artificial intelligence (AI) has created widespread fear of job losses and further rises in inequality. This paper discusses the rationale for these fears, highlighting the specific nature of AI and comparing previous waves of automation and robotization with the current advancements made possible by a wide-spread adoption of AI. It argues that large opportunities in terms of increases in productivity can ensue, including for developing countries, given the vastly reduced costs of capital that some applications have demonstrated and the potential for productivity increases, especially among the low-skilled. At the same time, risks in the form of further increases in inequality need to be addressed if the benefits from AI-based technological progress are to be broadly shared. For this, skills policy are necessary but not sufficient. In addition, new forms of regulating the digital economy are called for that prevent further rises in market concentration, ensure proper data protection and privacy and help share the benefits of productivity growth through a combination of profit sharing, (digital) capital taxation and a reduction in working time. The paper calls for a moderately optimistic outlook on the opportunities and risks from artificial intelligence, provided policy-makers and social partners take the particular characteristics of these new technologies into account.},
language = {en},
author = {Ernst, Ekkehard and Merola, Rossana and Samaan, Daniel},
keywords = {AI},
file = {Ernst et al. - The economics of artificial intelligence Implicat.pdf:C\:\\Users\\jonas\\Zotero\\storage\\DFSVUNVV\\Ernst et al. - The economics of artificial intelligence Implicat.pdf:application/pdf},
}
@article{noauthor_macroeconomic_nodate,
title = {The macroeconomic impact of artificial intelligence},
language = {en},
keywords = {AI},
file = {The macroeconomic impact of artificial intelligenc.pdf:C\:\\Users\\jonas\\Zotero\\storage\\MZJABFXS\\The macroeconomic impact of artificial intelligenc.pdf:application/pdf},
}
@article{noauthor_assessing_nodate,
title = {Assessing the {Economic} {Impact} of {Artificial} {Intelligence}},
language = {en},
keywords = {AI},
file = {S-GEN-ISSUEPAPER-2018-1-PDF-E.pdf:C\:\\Users\\jonas\\Zotero\\storage\\45FCEHXK\\S-GEN-ISSUEPAPER-2018-1-PDF-E.pdf:application/pdf},
}
@article{moro_universal_2021,
title = {Universal resilience patterns in labor markets},
volume = {12},
copyright = {2021 The Author(s)},
issn = {2041-1723},
url = {https://www.nature.com/articles/s41467-021-22086-3},
doi = {10.1038/s41467-021-22086-3},
abstract = {Cities are the innovation centers of the US economy, but technological disruptions can exclude workers and inhibit a middle class. Therefore, urban policy must promote the jobs and skills that increase worker pay, create employment, and foster economic resilience. In this paper, we model labor market resilience with an ecologically-inspired job network constructed from the similarity of occupations’ skill requirements. This framework reveals that the economic resilience of cities is universally and uniquely determined by the connectivity within a city’s job network. US cities with greater job connectivity experienced lower unemployment during the Great Recession. Further, cities that increase their job connectivity see increasing wage bills, and workers of embedded occupations enjoy higher wages than their peers elsewhere. Finally, we show how job connectivity may clarify the augmenting and deleterious impact of automation in US cities. Policies that promote labor connectivity may grow labor markets and promote economic resilience.},
language = {en},
number = {1},
urldate = {2023-05-21},
journal = {Nature Communications},
author = {Moro, Esteban and Frank, Morgan R. and Pentland, Alex and Rutherford, Alex and Cebrian, Manuel and Rahwan, Iyad},
month = mar,
year = {2021},
note = {Number: 1
Publisher: Nature Publishing Group},
keywords = {Applied mathematics, Environmental economics, Interdisciplinary studies, Labor},
pages = {1972},
file = {Full Text PDF:C\:\\Users\\jonas\\Zotero\\storage\\7FW52FLF\\Moro et al. - 2021 - Universal resilience patterns in labor markets.pdf:application/pdf},
}
@article{alabdulkareem_unpacking_2018,
title = {Unpacking the polarization of workplace skills},
volume = {4},
url = {https://www.science.org/doi/10.1126/sciadv.aao6030},
doi = {10.1126/sciadv.aao6030},
abstract = {Economic inequality is one of the biggest challenges facing society today. Inequality has been recently exacerbated by growth in high- and low-wage occupations at the expense of middle-wage occupations, leading to a “hollowing” of the middle class. Yet, our understanding of how workplace skills drive this process is limited. Specifically, how do skill requirements distinguish high- and low-wage occupations, and does this distinction constrain the mobility of individuals and urban labor markets? Using unsupervised clustering techniques from network science, we show that skills exhibit a striking polarization into two clusters that highlight the specific social-cognitive skills and sensory-physical skills of high- and low-wage occupations, respectively. The connections between skills explain various dynamics: how workers transition between occupations, how cities acquire comparative advantage in new skills, and how individual occupations change their skill requirements. We also show that the polarized skill topology constrains the career mobility of individual workers, with low-skill workers “stuck” relying on the low-wage skill set. Together, these results provide a new explanation for the persistence of occupational polarization and inform strategies to mitigate the negative effects of automation and offshoring of employment. In addition to our analysis, we provide an online tool for the public and policy makers to explore the skill network: skillscape.mit.edu.},
number = {7},
urldate = {2023-05-21},
journal = {Science Advances},
author = {Alabdulkareem, Ahmad and Frank, Morgan R. and Sun, Lijun and AlShebli, Bedoor and Hidalgo, César and Rahwan, Iyad},
month = jul,
year = {2018},
note = {Publisher: American Association for the Advancement of Science},
keywords = {Labor},
pages = {eaao6030},
file = {Full Text PDF:C\:\\Users\\jonas\\Zotero\\storage\\5PGGZVMF\\Alabdulkareem et al. - 2018 - Unpacking the polarization of workplace skills.pdf:application/pdf},
}
@article{lyu_soft_2021,
title = {Soft skills, hard skills: {What} matters most? {Evidence} from job postings},
volume = {300},
issn = {0306-2619},
shorttitle = {Soft skills, hard skills},
url = {https://www.sciencedirect.com/science/article/pii/S0306261921007194},
doi = {10.1016/j.apenergy.2021.117307},
abstract = {Using a proprietary database of online job postings from 2010 to 2019, we find that job vacancies in the U.S. energy sector increasingly require high levels of “soft” skills (such as social, cognitive, people management, project management, and customer service skill), showing an “upskilling” pattern in the past decade. We further examine skill requirements across and within four major professional occupations in the U.S. energy sector and find substantial variations. Meanwhile, in the energy sector, although cognitive and social skills are the most frequently required skills, they do not positively contribute to firm productivity. Although the requirement for “hard” skills (such as products and marketing, engineering, and general computer skill) stays relatively flat, “hard” skills actually matter most in the energy sector, especially products and marketing and general computer skills are two most valuable skills, contributing the highest to energy firms. Our results indicate that energy firms should pay more attention to “hard” skills in human resource management, while not following the increasing trend of “soft” skills in hiring.},
language = {en},
urldate = {2023-05-21},
journal = {Applied Energy},
author = {Lyu, Wenjing and Liu, Jin},
month = oct,
year = {2021},
keywords = {firm productivity, labor, labor demand, skill requirements, soft skills, hard skills, energy sector},
pages = {117307},
file = {ScienceDirect Snapshot:C\:\\Users\\jonas\\Zotero\\storage\\TQPN5MGX\\S0306261921007194.html:text/html},
}
@article{park_data-driven_2022,
title = {A data-driven exploration of the race between human labor and machines in the 21 $^{\textrm{st}}$ century},
volume = {65},
issn = {0001-0782, 1557-7317},
url = {https://dl.acm.org/doi/10.1145/3488376},
doi = {10.1145/3488376},
abstract = {To understand automation and the future of work, this study explores how human labor competes, or cooperates, with technology in performing a range of tasks.},
language = {en},
number = {5},
urldate = {2023-05-21},
journal = {Communications of the ACM},
author = {Park, Jiyong and Kim, Jongho},
month = apr,
year = {2022},
pages = {79--87},
file = {Full Text PDF:C\:\\Users\\jonas\\Zotero\\storage\\XYS2T2J3\\Park and Kim - 2022 - A data-driven exploration of the race between huma.pdf:application/pdf},
}
@techreport{noauthor_impact_2021,
type = {{OECD} {Social}, {Employment} and {Migration} {Working} {Papers}},
title = {The impact of {Artificial} {Intelligence} on the labour market: {What} do we know so far?},
shorttitle = {The impact of {Artificial} {Intelligence} on the labour market},
url = {https://www.oecd-ilibrary.org/social-issues-migration-health/the-impact-of-artificial-intelligence-on-the-labour-market_7c895724-en},
abstract = {Recent developments in Artificial Intelligence (AI) have stoked new fears about large-scale job loss, stemming from its ability to automate a rapidly expanding set of tasks (including non-routine cognitive tasks), and its potential to affect every sector of the economy. Furthermore, there are concerns about employee well-being and the broader work environment, linked to the idea that AI may soon become pervasive in the workplace and threaten and undermine humans’ place in it. However, AI also has the potential to complement and augment human capabilities, leading to higher productivity, greater demand for human labour and improved job quality.},
language = {en},
number = {256},
urldate = {2023-06-20},
month = jan,
year = {2021},
doi = {10.1787/7c895724-en},
note = {Series: OECD Social, Employment and Migration Working Papers
Volume: 256},
keywords = {background},
file = {2021 - The impact of Artificial Intelligence on the labou.pdf:C\:\\Users\\jonas\\Zotero\\storage\\46VK2CXV\\2021 - The impact of Artificial Intelligence on the labou.pdf:application/pdf},
}
@article{czarnitzki_artificial_2023,
title = {Artificial intelligence and firm-level productivity},
volume = {211},
issn = {01672681},
url = {https://linkinghub.elsevier.com/retrieve/pii/S0167268123001531},
doi = {10.1016/j.jebo.2023.05.008},
language = {en},
urldate = {2023-06-20},
journal = {Journal of Economic Behavior \& Organization},
author = {Czarnitzki, Dirk and Fernández, Gastón P. and Rammer, Christian},
month = jul,
year = {2023},
keywords = {AI, firm productivity},
pages = {188--205},
file = {Czarnitzki et al. - 2023 - Artificial intelligence and firm-level productivit.pdf:C\:\\Users\\jonas\\Zotero\\storage\\6A8GV383\\Czarnitzki et al. - 2023 - Artificial intelligence and firm-level productivit.pdf:application/pdf},
}
@article{martens_will_2018,
title = {Will {This} {Time} {Be} {Different}? {A} {Review} of the {Literature} on the {Impact} of {Artificial} {Intelligence} on {Employment}, {Incomes} and {Growth}},
issn = {1556-5068},
shorttitle = {Will {This} {Time} {Be} {Different}?},
url = {https://www.ssrn.com/abstract=3290708},
doi = {10.2139/ssrn.3290708},
language = {en},
urldate = {2023-06-20},
journal = {SSRN Electronic Journal},
author = {Martens, Bertin and Tolan, Songül},
year = {2018},
file = {Martens and Tolan - 2018 - Will This Time Be Different A Review of the Liter.pdf:C\:\\Users\\jonas\\Zotero\\storage\\ZNG89S8J\\Martens and Tolan - 2018 - Will This Time Be Different A Review of the Liter.pdf:application/pdf},
}
@article{furman_ai_nodate,
title = {{AI} and the {Economy}},
url = {https://www.journals.uchicago.edu/doi/epdf/10.1086/699936},
language = {en},
author = {Furman, Jason and Seamans, Robert},
file = {699936.pdf:C\:\\Users\\jonas\\Downloads\\699936.pdf:application/pdf},
}
@article{montobbio_empirics_2022,
title = {The {Empirics} of {Technology}, {Employment} and {Occupations}: {Lessons} {Learned} and {Challenges} {Ahead}},
issn = {1556-5068},
shorttitle = {The {Empirics} of {Technology}, {Employment} and {Occupations}},
url = {https://www.ssrn.com/abstract=4281286},
doi = {10.2139/ssrn.4281286},
language = {en},
urldate = {2023-06-20},
journal = {SSRN Electronic Journal},
author = {Montobbio, Fabio and Staccioli, Jacopo and Virgillito, Maria and Vivarelli, Marco},
year = {2022},
file = {Montobbio et al. - 2022 - The Empirics of Technology, Employment and Occupat.pdf:C\:\\Users\\jonas\\Zotero\\storage\\CMAUDL8K\\Montobbio et al. - 2022 - The Empirics of Technology, Employment and Occupat.pdf:application/pdf},
}
@article{hanson_economic_nodate,
title = {Economic {Growth} {Given} {Machine} {Intelligence}},
abstract = {A simple exogenous growth model gives conservative estimates of the economic implications of machine intelligence. Machines complement human labor when they become more productive at the jobs they perform, but machines also substitute for human labor by taking over human jobs. At first, expensive hardware and software does only the few jobs where computers have the strongest advantage over humans. Eventually, computers do most jobs. At first, complementary effects dominate, and human wages rise with computer productivity. But eventually substitution can dominate, making wages fall as fast as computer prices now do. An intelligence population explosion makes per-intelligence consumption fall this fast, while economic growth rates rise by an order of magnitude or more. These results are robust to automating incrementally, and to distinguishing hardware, software, and human capital from other forms of capital.},
language = {en},
author = {Hanson, Robin},
keywords = {todo},
file = {Hanson - Economic Growth Given Machine Intelligence.pdf:C\:\\Users\\jonas\\Zotero\\storage\\QLB22DKD\\Hanson - Economic Growth Given Machine Intelligence.pdf:application/pdf},
}
@book{agrawal_economics_2019,
title = {The {Economics} of {Artificial} {Intelligence}: {An} {Agenda}},
isbn = {978-0-226-61333-8 978-0-226-61347-5},
shorttitle = {The {Economics} of {Artificial} {Intelligence}},
url = {https://www.bibliovault.org/BV.landing.epl?ISBN=9780226613475},
abstract = {We interpret recent developments in the field of artificial intelligence (AI) as improvements in prediction technology. In this paper, we explore the consequences of improved prediction in decision-making. To do so, we adapt existing models of decision-making under uncertainty to account for the process of determining payoffs. We label this process of determining the payoffs ‘judgment.’ There is a risky action, whose payoff depends on the state, and a safe action with the same payoff in every state. Judgment is costly; for each potential state, it requires thought on what the payoff might be. Prediction and judgment are complements as long as judgment is not too difficult. We show that in complex environments with a large number of potential states, the effect of improvements in prediction on the importance of judgment depend a great deal on whether the improvements in prediction enable automated decision-making. We discuss the implications of improved prediction in the face of complexity for automation, contracts, and firm boundaries.},
language = {en},
urldate = {2023-08-19},
publisher = {University of Chicago Press},
author = {Agrawal, Ajay and Gans, Joshua and Goldfarb, Avi},
year = {2019},
doi = {10.7208/chicago/9780226613475.001.0001},
file = {Agrawal et al. - 2019 - The Economics of Artificial Intelligence An Agend.pdf:C\:\\Users\\jonas\\Zotero\\storage\\BEJ4ELAT\\Agrawal et al. - 2019 - The Economics of Artificial Intelligence An Agend.pdf:application/pdf},
}
@article{kromann_automation_2019,
title = {Automation and productivity—a cross-country, cross-industry comparison},
issn = {0960-6491, 1464-3650},
url = {https://academic.oup.com/icc/advance-article/doi/10.1093/icc/dtz039/5540937},
doi = {10.1093/icc/dtz039},
abstract = {Abstract
We investigate the effects of automation on total factor productivity (TFP). Using industry-level panel data for nine countries, we find that more intensive use of industrial robots has a significantly positive effect on TFP. Specifically, an increase of one standard deviation in the robot intensity is associated with more than 6\% higher TFP. Moreover, we find that the robot intensity increases with Chinese import competition and that automation is associated with higher wages and unchanged or higher employment.},
language = {en},
urldate = {2023-08-19},
journal = {Industrial and Corporate Change},
author = {Kromann, Lene and Malchow-Møller, Nikolaj and Skaksen, Jan Rose and Sørensen, Anders},
month = jul,
year = {2019},
keywords = {todo},
pages = {dtz039},
file = {Kromann et al. - 2019 - Automation and productivity—a cross-country, cross.pdf:C\:\\Users\\jonas\\Zotero\\storage\\YVJNWQKN\\Kromann et al. - 2019 - Automation and productivity—a cross-country, cross.pdf:application/pdf},
}
@techreport{arntz_risk_2016,
address = {Paris},
title = {The {Risk} of {Automation} for {Jobs} in {OECD} {Countries}: {A} {Comparative} {Analysis}},
shorttitle = {The {Risk} of {Automation} for {Jobs} in {OECD} {Countries}},
url = {https://www.oecd-ilibrary.org/social-issues-migration-health/the-risk-of-automation-for-jobs-in-oecd-countries_5jlz9h56dvq7-en},
abstract = {In recent years, there has been a revival of concerns that automation and digitalisation might after all result in a jobless future. The debate has been fuelled by studies for the US and Europe arguing that a substantial share of jobs is at “risk of computerisation”. These studies follow an occupation-based approach proposed by Frey and Osborne (2013), i.e. they assume that whole occupations rather than single job-tasks are automated by technology. As we argue, this might lead to an overestimation of job automatibility, as occupations labelled as high-risk occupations often still contain a substantial share of tasks that are hard to automate. Our paper serves two purposes. Firstly, we estimate the job automatibility of jobs for 21 OECD countries based on a task-based approach. In contrast to other studies, we take into account the heterogeneity of workers’ tasks within occupations. Overall, we find that, on average across the 21 OECD countries, 9 \% of jobs are automatable. The threat from technological advances thus seems much less pronounced compared to the occupation-based approach. We further find heterogeneities across OECD countries. For instance, while the share of automatable jobs is 6 \% in Korea, the corresponding share is 12 \% in Austria. Differences between countries may reflect general differences in workplace organisation, differences in previous investments into automation technologies as well as differences in the education of workers across countries.},
language = {en},
urldate = {2023-10-02},
institution = {OECD},
author = {Arntz, Melanie and Gregory, Terry and Zierahn, Ulrich},
month = may,
year = {2016},
doi = {10.1787/5jlz9h56dvq7-en},
keywords = {used},
file = {Full Text PDF:C\:\\Users\\jonas\\Zotero\\storage\\T9MKWQT2\\Arntz et al. - 2016 - The Risk of Automation for Jobs in OECD Countries.pdf:application/pdf},
}
@book{ford_rise_2016,
address = {New York},
edition = {First paperback edition},
title = {Rise of the robots: technology and the threat of a jobless future},
isbn = {978-0-465-09753-1},
shorttitle = {Rise of the robots},
language = {eng},
publisher = {Basic Books},
author = {Ford, Martin},
year = {2016},
}
@misc{noauthor_every_nodate,
title = {Every study we could find on what automation will do to jobs, in one chart},
url = {https://www.technologyreview.com/2018/01/25/146020/every-study-we-could-find-on-what-automation-will-do-to-jobs-in-one-chart/},
abstract = {There are about as many opinions as there are experts.},
language = {en},
urldate = {2023-10-02},
journal = {MIT Technology Review},
file = {Snapshot:C\:\\Users\\jonas\\Zotero\\storage\\6DV59RYL\\every-study-we-could-find-on-what-automation-will-do-to-jobs-in-one-chart.html:text/html},
}
@article{gaggl_short-run_2014,
title = {A {Short}-{Run} {View} of {What} {Computers} {Do}: {Evidence} from a {UK} {Tax} {Incentive}},
issn = {1755-5361},
shorttitle = {A {Short}-{Run} {View} of {What} {Computers} {Do}},
url = {https://ideas.repec.org//p/esx/essedp/10012.html},
abstract = {We study the short-run, causal effect of Information and Communication Technology (ICT) adoption on the employment and wage distribution, providing direct insight into how ICT alters the demand for work within the firm. We exploit a unique natural experiment generated by a generous tax allowance on ICT investments for small UK firms and find that the primary short-run effect of ICT is to complement non-routine congnitive-intensive work. At the same time, we find less extensive substitution for routine cognitive work, a result at odds with existing long-run extimates. We find no effect of ICT on manual work in the short run. Overall, ICT raises average labor productivity within the firm.},
language = {en},
number = {752},
urldate = {2023-10-02},
journal = {Economics Discussion Papers},
author = {Gaggl, P. and Wright, G. C.},
year = {2014},
note = {Number: 10012
Publisher: University of Essex, Department of Economics},
keywords = {todo},
file = {dp752.pdf:C\:\\Users\\jonas\\Zotero\\storage\\YYWTTQ2V\\dp752.pdf:application/pdf;Snapshot:C\:\\Users\\jonas\\Zotero\\storage\\KFRLK2IV\\10012.html:text/html},
}
@misc{bessen_how_2016,
address = {Rochester, NY},
type = {{SSRN} {Scholarly} {Paper}},
title = {How {Computer} {Automation} {Affects} {Occupations}: {Technology}, {Jobs}, and {Skills}},
shorttitle = {How {Computer} {Automation} {Affects} {Occupations}},
url = {https://papers.ssrn.com/abstract=2690435},
doi = {10.2139/ssrn.2690435},
abstract = {This paper investigates basic relationships between technology and occupations. Building a general occupational model, I look at detailed occupations since 1980 to explore whether computers are related to job losses or other sources of wage inequality. Occupations that use computers grow faster, not slower. This is true even for highly routine and mid-wage occupations. Estimates reject computers as a source of significant net technological unemployment or job polarization. But computerized occupations substitute for other occupations, shifting employment and requiring new skills. Because new skills are costly to learn, computer use is associated with substantially greater within-occupation wage inequality.},
language = {en},
urldate = {2023-10-02},
author = {Bessen, James E.},
month = oct,
year = {2016},
keywords = {automation, human capital, job polarization, occupations, technology, wage inequality},
file = {Full Text PDF:C\:\\Users\\jonas\\Zotero\\storage\\SLLNGM4I\\Bessen - 2016 - How Computer Automation Affects Occupations Techn.pdf:application/pdf},
}
@misc{mann_benign_2018,
address = {Rochester, NY},
type = {{SSRN} {Scholarly} {Paper}},
title = {Benign {Effects} of {Automation}: {New} {Evidence} from {Patent} {Texts}},
shorttitle = {Benign {Effects} of {Automation}},
url = {https://papers.ssrn.com/abstract=2959584},
doi = {10.2139/ssrn.2959584},
abstract = {We provide a new measure of automation based on patents and study its employment effects. Classifying all U.S. patents granted between 1976 and 2014 as automation or non-automation patents, we document a strong rise in both the absolute number and the share of automation patents. We link patents to the industries of their use and, through local industry structure, to commuting zones. According to our estimates, advances in national automation technology have a positive influence on employment in local labor markets. Manufacturing employment declines, but this is more than compensated by service sector job growth. Commuting zones with more people working in routine occupations fare worse. Our findings are robust to weighting patents by the number of their citations or focusing exclusively on patents by governments, research institutions or foreign assignees.},
language = {en},
urldate = {2023-10-02},
author = {Mann, Katja and Püttmann, Lukas},
month = aug,
year = {2018},
keywords = {employment, labor demand, automation, innovation, local labor markets, patents, used},
file = {Full Text PDF:C\:\\Users\\jonas\\Zotero\\storage\\QKVRX3BL\\Mann and Püttmann - 2018 - Benign Effects of Automation New Evidence from Pa.pdf:application/pdf},
}
@article{bessen_automation_2019,
title = {Automation and jobs: {When} technology boosts employment},
volume = {34},
doi = {https://doi.org/10.1093/epolic/eiaa001},
number = {100},
journal = {Economic Policy},
author = {Bessen, James},
year = {2019},
note = {Publisher: Oxford University Press},
pages = {589--626},
file = {Bessen - Automation and Jobs When Technology Boosts Employ.pdf:C\:\\Users\\jonas\\Zotero\\storage\\PIA27P83\\Bessen - Automation and Jobs When Technology Boosts Employ.pdf:application/pdf},
}
@article{autor_untangling_2015,
title = {Untangling {Trade} and {Technology}: {Evidence} from {Local} {Labour} {Markets}},
volume = {125},
issn = {00130133},
shorttitle = {Untangling {Trade} and {Technology}},
url = {https://search.ebscohost.com/login.aspx?direct=true&db=buh&AN=103146021&site=ehost-live},
doi = {10.1111/ecoj.12245},
abstract = {We juxtapose the effects of trade and technology on employment in US local labour markets between 1980 and 2007. Labour markets whose initial industry composition exposes them to rising Chinese import competition experience significant falls in employment, particularly in manufacturing and among non-college workers. Labour markets susceptible to computerisation due to specialisation in routine task-intensive activities instead experience occupational polarisation within manufacturing and non-manufacturing but do not experience a net employment decline. Trade impacts rise in the 2000s as imports accelerate, while the effect of technology appears to shift from automation of production activities in manufacturing towards computerisation of information-processing tasks in non-manufacturing.},
number = {584},
urldate = {2023-10-02},
journal = {Economic Journal},
author = {Autor, David H. and Dorn, David and Hanson, Gordon H.},
month = may,
year = {2015},
note = {Publisher: Oxford University Press / USA},
keywords = {AUTOMATION, EMPLOYMENT, INFORMATION storage \& retrieval systems, LABOR market, TECHNOLOGY research, UNITED States, UNITED States manufacturing industries},
pages = {621--646},
file = {EBSCO Full Text:C\:\\Users\\jonas\\Zotero\\storage\\NLVR4GF6\\Autor et al. - 2015 - Untangling Trade and Technology Evidence from Loc.pdf:application/pdf},
}
@article{frank_toward_2019,
title = {Toward understanding the impact of artificial intelligence on labor},
volume = {116},
url = {https://www.pnas.org/doi/full/10.1073/pnas.1900949116},
doi = {10.1073/pnas.1900949116},
abstract = {Rapid advances in artificial intelligence (AI) and automation technologies have the potential to significantly disrupt labor markets. While AI and automation can augment the productivity of some workers, they can replace the work done by others and will likely transform almost all occupations at least to some degree. Rising automation is happening in a period of growing economic inequality, raising fears of mass technological unemployment and a renewed call for policy efforts to address the consequences of technological change. In this paper we discuss the barriers that inhibit scientists from measuring the effects of AI and automation on the future of work. These barriers include the lack of high-quality data about the nature of work (e.g., the dynamic requirements of occupations), lack of empirically informed models of key microlevel processes (e.g., skill substitution and human–machine complementarity), and insufficient understanding of how cognitive technologies interact with broader economic dynamics and institutional mechanisms (e.g., urban migration and international trade policy). Overcoming these barriers requires improvements in the longitudinal and spatial resolution of data, as well as refinements to data on workplace skills. These improvements will enable multidisciplinary research to quantitatively monitor and predict the complex evolution of work in tandem with technological progress. Finally, given the fundamental uncertainty in predicting technological change, we recommend developing a decision framework that focuses on resilience to unexpected scenarios in addition to general equilibrium behavior.},
number = {14},
urldate = {2023-10-02},
journal = {Proceedings of the National Academy of Sciences},
author = {Frank, Morgan R. and Autor, David and Bessen, James E. and Brynjolfsson, Erik and Cebrian, Manuel and Deming, David J. and Feldman, Maryann and Groh, Matthew and Lobo, José and Moro, Esteban and Wang, Dashun and Youn, Hyejin and Rahwan, Iyad},
month = apr,
year = {2019},
note = {Publisher: Proceedings of the National Academy of Sciences},
keywords = {used},
pages = {6531--6539},
file = {Full Text PDF:C\:\\Users\\jonas\\Zotero\\storage\\G73T62QP\\Frank et al. - 2019 - Toward understanding the impact of artificial inte.pdf:application/pdf},
}
@article{cirera_effects_2019,
title = {The effects of innovation on employment in developing countries: evidence from enterprise surveys},
volume = {28},
issn = {0960-6491, 1464-3650},
shorttitle = {The effects of innovation on employment in developing countries},
url = {https://academic.oup.com/icc/article/28/1/161/5272481},
doi = {10.1093/icc/dty061},
abstract = {This article sheds light on the direct impact of technological as well as organizational innovation on firm-level employment growth using a global sample of over 15,000 firms in developing countries. The main findings suggest that new sales associated with product innovation are produced, on average, with just as much or higher levels of labor intensity than old products. However, the additionality to employment decreases with productivity, proxied by income per capita. In line with other studies, process innovation does not impact the additionality of employment, but there is some evidence of automation reducing the impact of product innovation on employment.},
language = {en},
number = {1},
urldate = {2023-10-02},
journal = {Industrial and Corporate Change},
author = {Cirera, Xavier and Sabetti, Leonard},
month = feb,
year = {2019},
keywords = {used},
pages = {161--176},
file = {Cirera and Sabetti - 2019 - The effects of innovation on employment in develop.pdf:C\:\\Users\\jonas\\Zotero\\storage\\QFYSV7HW\\Cirera and Sabetti - 2019 - The effects of innovation on employment in develop.pdf:application/pdf},
}
@article{acemoglu_modeling_2018,
title = {Modeling {Automation}},
volume = {108},
issn = {2574-0768},
url = {https://www.aeaweb.org/articles?id=10.1257/pandp.20181020},
doi = {10.1257/pandp.20181020},
abstract = {Modeling automation as factor-augmenting technological change has unappealing implications. Instead, modeling it as the process of machines replacing tasks previously performed by labor is both descriptively realistic and leads to distinct and plausible predictions. In contrast to factor-augmenting technological change, the automation of tasks always reduces the labor share and can reduce the equilibrium wage (for realistic parameter values). This approach to automation underscores the role of new tasks, changes in the comparative advantage of labor, the possibility that machines become more productive in automated tasks, and the elasticity of substitution and capital accumulation in the adjustment of the economy.},
language = {en},
urldate = {2023-10-02},
journal = {AEA Papers and Proceedings},
author = {Acemoglu, Daron and Restrepo, Pascual},
month = may,
year = {2018},
keywords = {Diffusion Processes, Factor Income Distribution, Human Capital, Labor Productivity, Wage Level and Structure, Occupational Choice, Skills, Wage Differentials, Technological Change: Choices and Consequences},
pages = {48--53},
file = {Full Text:C\:\\Users\\jonas\\Zotero\\storage\\LVCNXB8V\\Acemoglu and Restrepo - 2018 - Modeling Automation.pdf:application/pdf},
}
@misc{acemoglu_skills_2011,
title = {Skills, {Tasks} and {Technologies}: {Implications} for {Employment} and {Earnings}},
shorttitle = {Skills, {Tasks} and {Technologies}},
url = {https://www.sciencedirect.com/science/article/pii/S0169721811024105},
abstract = {A central organizing framework of the voluminous recent literature studying changes in the returns to skills and the evolution of earnings inequality is what we refer to as the canonical model, which elegantly and powerfully operationalizes the supply and demand for skills by assuming two distinct skill groups that perform two different and imperfectly substitutable tasks or produce two imperfectly substitutable goods. Technology is assumed to take a factor-augmenting form, which, by complementing either high or low skill workers, can generate skill biased demand shifts. In this paper, we argue that despite its notable successes, the canonical model is largely silent on a number of central empirical developments of the last three decades, including: (1) significant declines in real wages of low skill workers, particularly low skill males; (2) non-monotone changes in wages at different parts of the earnings distribution during different decades; (3) broad-based increases in employment in high skill and low skill occupations relative to middle skilled occupations (i.e., job “polarization’’); (4) rapid diffusion of new technologies that directly substitute capital for labor in tasks previously performed by moderately skilled workers; and (5) expanding offshoring in opportunities, enabled by technology, which allow foreign labor to substitute for domestic workers specific tasks. Motivated by these patterns, we argue that it is valuable to consider a richer framework for analyzing how recent changes in the earnings and employment distribution in the United States and other advanced economies are shaped by the interactions among worker skills, job tasks, evolving technologies, and shifting trading opportunities. We propose a tractable task-based model in which the assignment of skills to tasks is endogenous and technical change may involve the substitution of machines for certain tasks previously performed by labor. We further consider how the evolution of technology in this task-based setting may be endogenized. We show how such a framework can be used to interpret several central recent trends, and we also suggest further directions for empirical exploration.},
urldate = {2023-10-02},
publisher = {Elsevier},
author = {Acemoglu, Daron and Autor, David},
editor = {Card, David and Ashenfelter, Orley},
month = jan,
year = {2011},
doi = {10.1016/S0169-7218(11)02410-5},
keywords = {College premium, Directed technical change, Earnings inequality, Occupations, Returns to schooling, Skill biased technical change, Skill premium, Tasks, Wage inequality},
file = {ScienceDirect Full Text PDF:C\:\\Users\\jonas\\Zotero\\storage\\K87W8MXV\\Acemoglu and Autor - 2011 - Chapter 12 - Skills, Tasks and Technologies Impli.pdf:application/pdf;ScienceDirect Snapshot:C\:\\Users\\jonas\\Zotero\\storage\\GINVFF6N\\S0169721811024105.html:text/html;w16082.pdf:C\:\\Users\\jonas\\Zotero\\storage\\AGWGPTKP\\w16082.pdf:application/pdf},
}
@article{dauth_german_2017,
title = {German {Robots} - {The} {Impact} of {Industrial} {Robots} on {Workers}},
volume = {30/2017},
issn = {2195-2663},
url = {https://ssrn.com/abstract=3039031},
journal = {IAB Discussion Paper},
author = {Dauth, Wolfgang and Findeisen, Sebastian and Südekum, Jens and Woessner, Nicole},
year = {2017},
keywords = {used},
file = {Dauth et al. - German Robots – The Impact of Industrial Robots on.pdf:C\:\\Users\\jonas\\Zotero\\storage\\3R77WGNL\\Dauth et al. - German Robots – The Impact of Industrial Robots on.pdf:application/pdf},
}
@misc{autor_is_2018,
type = {Working {Paper}},
series = {Working {Paper} {Series}},
title = {Is {Automation} {Labor}-{Displacing}? {Productivity} {Growth}, {Employment}, and the {Labor} {Share}},
shorttitle = {Is {Automation} {Labor}-{Displacing}?},
url = {https://www.nber.org/papers/w24871},
doi = {10.3386/w24871},
abstract = {Many technological innovations replace workers with machines, but this capital-labor substitution need not reduce aggregate labor demand because it simultaneously induces four countervailing responses: own-industry output effects; cross-industry input–output effects; between-industry shifts; and final demand effects. We quantify these channels using four decades of harmonized cross-country and industry data, where we measure automation as industry-level movements in total factor productivity (TFP) that are common across countries. We find that automation displaces employment and reduces labor's share of value-added in the industries in which it originates (a direct effect). In the case of employment, these own-industry losses are reversed by indirect gains in customer industries and induced increases in aggregate demand. By contrast, own-industry labor share losses are not recouped elsewhere. Our framework can account for a substantial fraction of the reallocation of employment across industries and the aggregate fall in the labor share over the last three decades. It does not, however, explain why the labor share fell more rapidly during the 2000s},
urldate = {2023-10-02},
publisher = {National Bureau of Economic Research},
author = {Autor, David and Salomons, Anna},
month = jul,
year = {2018},
doi = {10.3386/w24871},
keywords = {labor replacement},
file = {Full Text PDF:C\:\\Users\\jonas\\Zotero\\storage\\MX92NBRD\\Autor and Salomons - 2018 - Is Automation Labor-Displacing Productivity Growt.pdf:application/pdf},
}
@techreport{jungmittag_impact_2019,
type = {Working {Paper}},
title = {The impact of robots on labour productivity: {A} panel data approach covering 9 industries and 12 countries},
shorttitle = {The impact of robots on labour productivity},
url = {https://www.econstor.eu/handle/10419/231332},
abstract = {Based on the expectation that the intensified use of robots contributes to the growth of labour productivity, this paper presents estimates of Cobb-Douglas production functions, using data for 12 EU countries and 9 manufacturing industries. The empirical results for the models pooling all available data confirm that stocks of robots per 1 million Euros non-ICT capital input contribute significantly to labour productivity growth in the period from 1995 to 2015. The results remain robust, when the whole observation period is split into two subsamples from 1995 to 2007 and from 2008 to 2015. Furthermore, the model is used to assess the impact of an increase of robots use on the labour productivity in each of the 9 manufacturing industries considered.},
language = {eng},
number = {2019/08},
urldate = {2023-10-02},
institution = {JRC Working Papers Series on Labour, Education and Technology},
author = {Jungmittag, Andre and Pesole, Annarosa},
year = {2019},
file = {Full Text PDF:C\:\\Users\\jonas\\Zotero\\storage\\NSSDAT9K\\Jungmittag and Pesole - 2019 - The impact of robots on labour productivity A pan.pdf:application/pdf},
}
@book{weltbank_changing_2019,
address = {Washington, D.C},
series = {World development report},
title = {The changing nature of work},
isbn = {978-1-4648-1328-3 978-1-4648-1342-9},
language = {eng},
number = {2019},
publisher = {International Bank for Recunstruction and Development/The World Bank},
editor = {Weltbank},
year = {2019},
doi = {10.1596/9781464813429},
file = {2019-WDR-Report.pdf:C\:\\Users\\jonas\\Zotero\\storage\\ESPNJXHF\\2019-WDR-Report.pdf:application/pdf;Table of Contents PDF:C\:\\Users\\jonas\\Zotero\\storage\\NQL4KD45\\Weltbank - 2019 - The changing nature of work.pdf:application/pdf},
}
@article{berge_automatic_2019,
title = {Automatic {Reaction} – {What} {Happens} to {Workers} at {Firms} that {Automate}?},
url = {https://ideas.repec.org//p/cpb/discus/390.html},
abstract = {We provide the first estimate of the impacts of automation on individual workers by combining Dutch micro-data with a direct measure of automation expenditures covering firms in all private non-financial industries over 2000-2016. Using an event study differences-indifferences design, we find that automation at the firm increases the probability of workers separating from their employers and decreases days worked, leading to a 5-year cumulative wage income loss of about 8\% of one year’s earnings for incumbent workers.},
language = {en},
urldate = {2023-10-02},
journal = {CPB Discussion Paper},
author = {Berge, Wiljan van den},
month = feb,
year = {2019},
note = {Number: 390
Publisher: CPB Netherlands Bureau for Economic Policy Analysis},
file = {Fullext PDF:C\:\\Users\\jonas\\Zotero\\storage\\MZKZW6SZ\\Berge - 2019 - Automatic Reaction – What Happens to Workers at Fi.pdf:application/pdf;Snapshot:C\:\\Users\\jonas\\Zotero\\storage\\3GDEQJHN\\390.html:text/html},
}
@misc{european_commission_proposal_2021,
title = {Proposal for a {REGULATION} {OF} {THE} {EUROPEAN} {PARLIAMENT} {AND} {OF} {THE} {COUNCIL}},
url = {https://eur-lex.europa.eu/legal-content/EN/TXT/HTML/?uri=CELEX:52021PC0206},
urldate = {2023-10-03},
author = {{European Commission}},
month = apr,
year = {2021},
file = {eur-lex.europa.eu/legal-content/EN/TXT/HTML/?uri=CELEX\:52021PC0206:C\:\\Users\\jonas\\Zotero\\storage\\BWUKHG8N\\HTML.html:text/html;resource.pdf:C\:\\Users\\jonas\\Zotero\\storage\\HDKW5K3G\\resource.pdf:application/pdf},
}
@misc{european_commission_annexes_2021,
title = {{ANNEXES} to the {Proposal} for a {Regulation} of the {European} {Parliament} and of the {Council}},
language = {en},
urldate = {2023-10-03},
author = {{European Commission}},
month = apr,
year = {2021},
file = {Radley-Gardner et al. - 2016 - Fundamental Texts On European Private Law.pdf:C\:\\Users\\jonas\\Zotero\\storage\\SMAU3FCD\\Radley-Gardner et al. - 2016 - Fundamental Texts On European Private Law.pdf:application/pdf},
}
@article{mccarthy_proposal_2006,
title = {A {Proposal} for the {Dartmouth} {Summer} {Research} {Project} on {Artificial} {Intelligence}, {August} 31, 1955},
volume = {27},
copyright = {Copyright (c)},
issn = {2371-9621},
url = {https://ojs.aaai.org/aimagazine/index.php/aimagazine/article/view/1904},
doi = {10.1609/aimag.v27i4.1904},
abstract = {The 1956 Dartmouth summer research project on artificial intelligence was initiated by this August 31, 1955 proposal, authored by John McCarthy, Marvin Minsky, Nathaniel Rochester, and Claude Shannon. The original typescript consisted of 17 pages plus a title page. Copies of the typescript are housed in the archives at Dartmouth College and Stanford University. The first 5 papers state the proposal, and the remaining pages give qualifications and interests of the four who proposed the study. In the interest of brevity, this article reproduces only the proposal itself, along with the short autobiographical statements of the proposers.},
language = {en},
number = {4},
urldate = {2023-10-03},
journal = {AI Magazine},
author = {McCarthy, John and Minsky, Marvin L. and Rochester, Nathaniel and Shannon, Claude E.},
month = dec,
year = {2006},
note = {Number: 4},
pages = {12--12},
file = {Full Text PDF:C\:\\Users\\jonas\\Zotero\\storage\\SZG852E4\\McCarthy et al. - 2006 - A Proposal for the Dartmouth Summer Research Proje.pdf:application/pdf},
}
@misc{mccarthy_proposal_1955,
title = {A {PROPOSAL} {FOR} {THE} {DARTMOUTH} {SUMMER} {RESEARCH} {PROJECT} {ON} {ARTIFICIAL} {INTELLIGENCE}},
language = {en},
author = {McCarthy, J and Minsky, M L and Rochester, N and Corporation, I B M and Shannon, C E},
month = aug,
year = {1955},
file = {McCarthy et al. - A PROPOSAL FOR THE DARTMOUTH SUMMER RESEARCH PROJE.pdf:C\:\\Users\\jonas\\Zotero\\storage\\SZERDYHP\\McCarthy et al. - A PROPOSAL FOR THE DARTMOUTH SUMMER RESEARCH PROJE.pdf:application/pdf},
}
@article{trajtenberg_penny_1990,
title = {A {Penny} for {Your} {Quotes}: {Patent} {Citations} and the {Value} of {Innovations}},
volume = {21},
issn = {07416261},
shorttitle = {A {Penny} for {Your} {Quotes}},
url = {http://doi.wiley.com/10.2307/2555502},
doi = {10.2307/2555502},
number = {1},
urldate = {2023-10-09},
journal = {The RAND Journal of Economics},
author = {Trajtenberg, Manuel},
year = {1990},
keywords = {methodology, used},
pages = {172},
file = {Trajtenberg - 1990 - A Penny for Your Quotes Patent Citations and the .pdf:C\:\\Users\\jonas\\Zotero\\storage\\HB35ZR83\\Trajtenberg - 1990 - A Penny for Your Quotes Patent Citations and the .pdf:application/pdf},
}
@misc{noauthor_frontier-review--impact--ai--workpdf_nodate,
title = {frontier-review-the-impact-of-{AI}-on-work.pdf},
url = {https://royalsociety.org/-/media/policy/projects/ai-and-work/frontier-review-the-impact-of-AI-on-work.pdf},
urldate = {2023-06-20},
file = {frontier-review-the-impact-of-AI-on-work.pdf:C\:\\Users\\jonas\\Zotero\\storage\\CB4YKVW5\\frontier-review-the-impact-of-AI-on-work.pdf:application/pdf},
}
@misc{acemoglu_harms_2021,
type = {Working {Paper}},
series = {Working {Paper} {Series}},
title = {Harms of {AI}},
url = {https://www.nber.org/papers/w29247},
doi = {10.3386/w29247},
abstract = {This essay discusses several potential economic, political and social costs of the current path of AI technologies. I argue that if AI continues to be deployed along its current trajectory and remains unregulated, it may produce various social, economic and political harms. These include: damaging competition, consumer privacy and consumer choice; excessively automating work, fueling inequality, inefficiently pushing down wages, and failing to improve worker productivity; and damaging political discourse, democracy's most fundamental lifeblood. Although there is no conclusive evidence suggesting that these costs are imminent or substantial, it may be useful to understand them before they are fully realized and become harder or even impossible to reverse, precisely because of AI's promising and wide-reaching potential. I also suggest that these costs are not inherent to the nature of AI technologies, but are related to how they are being used and developed at the moment - to empower corporations and governments against workers and citizens. As a result, efforts to limit and reverse these costs may need to rely on regulation and policies to redirect AI research. Attempts to contain them just by promoting competition may be insufficient.},
urldate = {2023-11-03},
publisher = {National Bureau of Economic Research},
author = {Acemoglu, Daron},
month = sep,
year = {2021},
doi = {10.3386/w29247},
keywords = {conclusion, discussion},
file = {Full Text PDF:C\:\\Users\\jonas\\Zotero\\storage\\XB4SZJIL\\Acemoglu - 2021 - Harms of AI.pdf:application/pdf},
}
@article{acemoglu_technical_2002,
title = {Technical {Change}, {Inequality}, and the {Labor} {Market}},
volume = {XL},
language = {en},
journal = {Journal of Economic Literature},
author = {Acemoglu, Daron},
month = mar,
year = {2002},
pages = {7--72},
file = {Acemoglu - 2002 - Technical Change, Inequality, and the Labor Market.pdf:C\:\\Users\\jonas\\Zotero\\storage\\Z25UWBD5\\Acemoglu - 2002 - Technical Change, Inequality, and the Labor Market.pdf:application/pdf},
}
@article{acemoglu_ais_2021,
title = {{AI}’s {Future} {Doesn}’t {Have} to {Be} {Dystopian}},
url = {https://www.bostonreview.net/forum/ais-future-doesnt-have-to-be-dystopian/},
abstract = {AI can be used to increase human productivity, create jobs and shared prosperity, and protect and bolster democratic freedoms—but only if we modify our approach.},
language = {en-US},
urldate = {2023-11-03},
journal = {Boston Review},
author = {Acemoglu, Daron},
month = may,
year = {2021},
keywords = {Democracy, Economy, Politics, Redesigning AI, Science and Technology},
file = {Snapshot:C\:\\Users\\jonas\\Zotero\\storage\\GJCFH6PX\\ais-future-doesnt-have-to-be-dystopian.html:text/html},
}
@article{noauthor_return_2014,
title = {Return of the {Solow} {Paradox}? {IT}, {Productivity}, and {Employment} in {US} {Manufacturing}},
volume = {104},
issn = {00028282},
shorttitle = {Return of the {Solow} {Paradox}?},
url = {https://search.ebscohost.com/login.aspx?direct=true&db=buh&AN=96037272&site=ehost-live},
doi = {10.1257/aer.104.5.394},
abstract = {An increasingly influential 'technological-discontinuity' paradigm suggests that IT-induced technological changes are rapidly raising productivity while making workers redundant. This paper explores the evidence for this view among the IT-using US manufacturing industries. There is some limited support for more rapid productivity growth in IT-intensive industries depending on the exact measures, though not since the late 1990s. Most challenging to this paradigm, and to our expectations, is that output contracts in IT-intensive industries relative to the rest of manufacturing. Productivity increases, when detectable, result from the even faster declines in employment.},
number = {5},
urldate = {2023-11-03},
journal = {American Economic Review},
month = may,
year = {2014},
note = {Publisher: American Economic Association},
keywords = {EMPLOYMENT, UNITED States, UNITED States manufacturing industries, ECONOMICS, INFORMATION technology, INFORMATION technology \& economics, LABOR productivity},
pages = {394--399},
file = {EBSCO Full Text:C\:\\Users\\jonas\\Zotero\\storage\\JJLX7RCT\\2014 - Return of the Solow Paradox IT, Productivity, and.pdf:application/pdf},
}
@misc{acemoglu_ai_2020,
type = {Working {Paper}},
series = {Working {Paper} {Series}},
title = {{AI} and {Jobs}: {Evidence} from {Online} {Vacancies}},
shorttitle = {{AI} and {Jobs}},
url = {https://www.nber.org/papers/w28257},
doi = {10.3386/w28257},
abstract = {We study the impact of AI on labor markets using establishment-level data on vacancies with detailed occupation and skill information comprising the near-universe of online vacancies in the US from 2010 onwards. There is rapid growth in AI related vacancies over 2010-2018 that is greater in AI-exposed establishments. AI-exposed establishments are reducing hiring in non-AI positions. We find no discernible relationship between AI exposure and employment or wage growth at the occupation or industry level, however, implying that AI is currently substituting for humans in a subset of tasks but it is not yet having detectable aggregate labor market consequences.},
urldate = {2023-11-03},
publisher = {National Bureau of Economic Research},
author = {Acemoglu, Daron and Autor, David and Hazell, Jonathon and Restrepo, Pascual},
month = dec,
year = {2020},
doi = {10.3386/w28257},
keywords = {AI, used, EFF},
file = {Full Text PDF:C\:\\Users\\jonas\\Zotero\\storage\\BYQCYTUD\\Acemoglu et al. - 2020 - AI and Jobs Evidence from Online Vacancies.pdf:application/pdf},
}
@article{ideas_turing_nodate,
title = {The {Turing} {Test} {Is} {Bad} for {Business}},
issn = {1059-1028},
url = {https://www.wired.com/story/artificial-intelligence-turing-test-economics-business/},
abstract = {Technology should focus on the complementarity game, not the imitation game.},
language = {en-US},
urldate = {2023-11-03},
journal = {Wired},
author = {Ideas, WIRED},
note = {Section: tags},
keywords = {innovation, artificial intelligence, business, economics, machine learning, opinion},
}
@article{acemoglu_competing_2020,
title = {Competing with {Robots}: {Firm}-{Level} {Evidence} from {France}},
volume = {110},
issn = {25740768},
shorttitle = {{EMPIRICAL} {RESEARCH} {ON} {AUTOMATION} {AND} "{SMART}" {TECHNOLOGIES}},
url = {https://search.ebscohost.com/login.aspx?direct=true&db=buh&AN=143256466&site=ehost-live},
doi = {10.1257/pandp.20201003},
abstract = {The article examines changes associated with the adoption of robotics and automated technologies in the industrial sector in France based on evidences gathered between 2010-2015. Topics discussed include impact of firm-level robot adoption including decline in labor shares and increase in productivity, increase in robot adoption and its impact on industry employment, and the market-level effects of automation.},
urldate = {2023-11-03},
journal = {AEA Papers \& Proceedings},
author = {Acemoglu, Daron and Lelarge, Claire and Restrepo, Pascual},
month = may,
year = {2020},
note = {Publisher: American Economic Association},
keywords = {AUTOMATION, EMPLOYMENT, TECHNOLOGICAL innovations, LABOR productivity, FRANCE, INDUSTRIAL robots, used},
pages = {383--388},
file = {EBSCO Full Text:C\:\\Users\\jonas\\Zotero\\storage\\M7A57RL7\\Acemoglu et al. - 2020 - EMPIRICAL RESEARCH ON AUTOMATION AND SMART TECHN.pdf:application/pdf},
}
@article{acemoglu_race_2018,
title = {The {Race} between {Man} and {Machine}: {Implications} of {Technology} for {Growth}, {Factor} {Shares}, and {Employment}},
volume = {108},
issn = {00028282},
shorttitle = {The {Race} between {Man} and {Machine}},
url = {https://search.ebscohost.com/login.aspx?direct=true&db=buh&AN=129997173&site=ehost-live},
doi = {10.1257/aer.20160696},
abstract = {We examine the concerns that new technologies will render labor redundant in a framework in which tasks previously performed by labor can be automated and new versions of existing tasks, in which labor has a comparative advantage, can be created. In a static version where capital is fixed and technology is exogenous, automation reduces employment and the labor share, and may even reduce wages, while the creation of new tasks has the opposite effects. Our full model endogenizes capital accumulation and the direction of research toward automation and the creation of new tasks. If the long-run rental rate of capital relative to the wage is sufficiently low, the long-run equilibrium involves automation of all tasks. Otherwise, there exists a stable balanced growth path in which the two types of innovations go hand-in-hand. Stability is a consequence of the fact that automation reduces the cost of producing using labor, and thus discourages further automation and encourages the creation of new tasks. In an extension with heterogeneous skills, we show that inequality increases during transitions driven both by faster automation and the introduction of new tasks, and characterize the conditions under which inequality stabilizes in the long run. (JEL D63, E22, E23, E24, J24, O33, O41)},
number = {6},
urldate = {2023-11-03},
journal = {American Economic Review},
author = {Acemoglu, Daron and Restrepo, Pascual},
month = jun,
year = {2018},
note = {Publisher: American Economic Association},
keywords = {AUTOMATION, ATTITUDES toward technology, ECONOMIC equilibrium, HUMAN-machine relationship, INNOVATION adoption, SAVINGS, used},
pages = {1488--1542},
file = {EBSCO Full Text:C\:\\Users\\jonas\\Zotero\\storage\\9RRB8UDX\\Acemoglu and Restrepo - 2018 - The Race between Man and Machine Implications of .pdf:application/pdf},
}
@incollection{acemoglu_artificial_2018,
title = {Artificial {Intelligence}, {Automation}, and {Work}},
url = {https://www.nber.org/books-and-chapters/economics-artificial-intelligence-agenda/artificial-intelligence-automation-and-work},
urldate = {2023-11-03},
booktitle = {The {Economics} of {Artificial} {Intelligence}: {An} {Agenda}},
publisher = {University of Chicago Press},
author = {Acemoglu, Daron and Restrepo, Pascual},
month = jan,
year = {2018},
keywords = {used},
pages = {197--236},
file = {Full Text PDF:C\:\\Users\\jonas\\Zotero\\storage\\CM5LP5E3\\Acemoglu and Restrepo - 2018 - Artificial Intelligence, Automation, and Work.pdf:application/pdf},
}
@article{acemoglu_automation_2019,
title = {Automation and {New} {Tasks}: {How} {Technology} {Displaces} and {Reinstates} {Labor}},
volume = {33},
issn = {08953309},
shorttitle = {Automation and {New} {Tasks}},
url = {https://search.ebscohost.com/login.aspx?direct=true&db=buh&AN=138424172&site=ehost-live},
doi = {10.1257/jep.33.2.3},
abstract = {We present a framework for understanding the effects of automation and other types of technological changes on labor demand, and use it to interpret changes in US employment over the recent past. At the center of our framework is the allocation of tasks to capital and labor-the task content of production. Automation, which enables capital to replace labor in tasks it was previously engaged in, shifts the task content of production against labor because of a displacement effect. As a result, automation always reduces the labor share in value added and may reduce labor demand even as it raises productivity. The effects of automation are counterbalanced by the creation of new tasks in which labor has a comparative advantage. The introduction of new tasks changes the task content of production in favor of labor because of a reinstatement effect, and always raises the labor share and labor demand. We show how the role of changes in the task content of production-due to automation and new tasks-can be inferred from industrylevel data. Our empirical decomposition suggests that the slower growth of employment over the last three decades is accounted for by an acceleration in the displacement effect, especially in manufacturing, a weaker reinstatement effect, and slower growth of productivity than in previous decades.},
number = {2},
urldate = {2023-11-03},
journal = {Journal of Economic Perspectives},
author = {Acemoglu, Daron and Restrepo, Pascual},
year = {2019},
note = {Publisher: American Economic Association},
keywords = {AUTOMATION, EMPLOYMENT, LABOR productivity, LABOR demand, RESOURCE allocation},
pages = {3--29},
file = {EBSCO Full Text:C\:\\Users\\jonas\\Zotero\\storage\\CVLYQQGM\\Acemoglu and Restrepo - 2019 - Automation and New Tasks How Technology Displaces.pdf:application/pdf},
}
@article{acemoglu_robots_2020,
title = {Robots and {Jobs}: {Evidence} from {US} {Labor} {Markets}},
volume = {128},
issn = {00223808},
shorttitle = {Robots and {Jobs}},
url = {https://search.ebscohost.com/login.aspx?direct=true&db=buh&AN=143381831&site=ehost-live},
doi = {10.1086/705716},
abstract = {We study the effects of industrial robots on US labor markets. We show theoretically that robots may reduce employment and wages and that their local impacts can be estimated using variation in exposure to robots—defined from industry-level advances in robotics and local industry employment. We estimate robust negative effects of robots on employment and wages across commuting zones. We also show that areas most exposed to robots after 1990 do not exhibit any differential trends before then, and robots' impact is distinct from other capital and technologies. One more robot per thousand workers reduces the employment-to-population ratio by 0.2 percentage points and wages by 0.42\%.},
number = {6},
urldate = {2023-11-03},
journal = {Journal of Political Economy},
author = {Acemoglu, Daron and Restrepo, Pascual},
month = jun,
year = {2020},
note = {Publisher: University of Chicago},
keywords = {LABOR market, INDUSTRIAL robots, ROBOT industry, ROBOTS, used},
pages = {2188--2244},
file = {EBSCO Full Text:C\:\\Users\\jonas\\Zotero\\storage\\M3LAVV9B\\Acemoglu and Restrepo - 2020 - Robots and Jobs Evidence from US Labor Markets.pdf:application/pdf},
}
@article{acemoglu_unpacking_2020,
title = {Unpacking {Skill} {Bias}: {Automation} and {New} {Tasks}},
volume = {110},
issn = {25740768},
shorttitle = {Unpacking {Skill} {Bias}},
url = {https://search.ebscohost.com/login.aspx?direct=true&db=buh&AN=143256517&site=ehost-live},
doi = {10.1257/pandp.20201063},
abstract = {The article employs a conceptual framework to study the impact of technological changes on the productivity and wages of skilled and non-skilled workers in the U.S. Topics discussed include comparison of productivity between skilled workers and less-skilled workers, changes in the demand for skills, and the association between automation and inequality.},
urldate = {2023-11-03},
journal = {AEA Papers \& Proceedings},
author = {Acemoglu, Daron and Restrepo, Pascual},
month = may,
year = {2020},
note = {Publisher: American Economic Association},
keywords = {AUTOMATION, UNITED States, TECHNOLOGICAL innovations, LABOR productivity, EFFECT of technological innovations on wages, EQUALITY, SKILLED labor, used},
pages = {356--361},
file = {EBSCO Full Text:C\:\\Users\\jonas\\Zotero\\storage\\4SD4NQ7E\\Acemoglu and Restrepo - 2020 - Unpacking Skill Bias Automation and New Tasks.pdf:application/pdf},
}
@article{acemoglu_demographics_2022,
title = {Demographics and {Automation}},
volume = {89},
issn = {00346527},
url = {https://search.ebscohost.com/login.aspx?direct=true&db=buh&AN=154928623&site=ehost-live},
doi = {10.1093/restud/rdab031},
abstract = {We argue theoretically and document empirically that aging leads to greater (industrial) automation, because it creates a shortage of middle-aged workers specializing in manual production tasks. We show that demographic change is associated with greater adoption of robots and other automation technologies across countries and with more robotics-related activities across U.S. commuting zones. We also document more automation innovation in countries undergoing faster aging. Our directed technological change model predicts that the response of automation technologies to aging should be more pronounced in industries that rely more on middle-aged workers and those that present greater opportunities for automation and that productivity should improve and the labor share should decline relatively in industries that are more amenable to automation. The evidence supports all four of these predictions.},
number = {1},
urldate = {2023-11-03},
journal = {Review of Economic Studies},
author = {Acemoglu, Daron and Restrepo, Pascual},
month = jan,
year = {2022},
note = {Publisher: Oxford University Press / USA},
keywords = {AUTOMATION, LABOR productivity, ROBOT industry, BLUE collar workers, DEMOGRAPHIC change},
pages = {1--44},
file = {EBSCO Full Text:C\:\\Users\\jonas\\Zotero\\storage\\KRKC5ZIB\\Acemoglu and Restrepo - 2022 - Demographics and Automation.pdf:application/pdf},
}
@article{acemoglu_tasks_2022,
title = {Tasks, {Automation}, and the {Rise} in {U}.{S}. {Wage} {Inequality}},
volume = {90},
copyright = {© 2022 The Authors. Econometrica published by John Wiley \& Sons Ltd on behalf of The Econometric Society},
issn = {1468-0262},
url = {https://onlinelibrary.wiley.com/doi/abs/10.3982/ECTA19815},
doi = {10.3982/ECTA19815},
abstract = {We document that between 50\% and 70\% of changes in the U.S. wage structure over the last four decades are accounted for by relative wage declines of worker groups specialized in routine tasks in industries experiencing rapid automation. We develop a conceptual framework where tasks across industries are allocated to different types of labor and capital. Automation technologies expand the set of tasks performed by capital, displacing certain worker groups from jobs for which they have comparative advantage. This framework yields a simple equation linking wage changes of a demographic group to the task displacement it experiences. We report robust evidence in favor of this relationship and show that regression models incorporating task displacement explain much of the changes in education wage differentials between 1980 and 2016. The negative relationship between wage changes and task displacement is unaffected when we control for changes in market power, deunionization, and other forms of capital deepening and technology unrelated to automation. We also propose a methodology for evaluating the full general equilibrium effects of automation, which incorporate induced changes in industry composition and ripple effects due to task reallocation across different groups. Our quantitative evaluation explains how major changes in wage inequality can go hand-in-hand with modest productivity gains.},
language = {en},
number = {5},
urldate = {2023-11-03},
journal = {Econometrica},
author = {Acemoglu, Daron and Restrepo, Pascual},
year = {2022},
note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.3982/ECTA19815},
keywords = {productivity, automation, technology, Tasks, inequality, wages, used},
pages = {1973--2016},
file = {Full Text PDF:C\:\\Users\\jonas\\Zotero\\storage\\TA357DES\\Acemoglu and Restrepo - 2022 - Tasks, Automation, and the Rise in U.S. Wage Inequ.pdf:application/pdf;Snapshot:C\:\\Users\\jonas\\Zotero\\storage\\4QLRCLNI\\ECTA19815.html:text/html},
}
@misc{boustan_automation_2022,
type = {Working {Paper}},
series = {Working {Paper} {Series}},
title = {Automation {After} the {Assembly} {Line}: {Computerized} {Machine} {Tools}, {Employment} and {Productivity} in the {United} {States}},
shorttitle = {Automation {After} the {Assembly} {Line}},
url = {https://www.nber.org/papers/w30400},
doi = {10.3386/w30400},
abstract = {Since the 1970s, computerized machine tools have been replacing semi-skilled manufacturing workers, contributing to factory automation. We build a novel measure of exposure to computer numerical control (CNC) based on initial variation in tool types across industries and differential shifts toward CNC technology by tool type over time. Industries more exposed to CNC increased capital investment and experienced higher labor productivity. Total employment rose, with gains for college-educated workers and abstract tasks compensating for losses of less-educated workers and routine tasks. Employment gains were strongest for unionized jobs. Workers in exposed industries returned to school and relevant degree programs expanded.},
urldate = {2023-11-03},
publisher = {National Bureau of Economic Research},
author = {Boustan, Leah Platt and Choi, Jiwon and Clingingsmith, David},
month = aug,
year = {2022},
doi = {10.3386/w30400},
keywords = {used},
file = {Full Text PDF:C\:\\Users\\jonas\\Zotero\\storage\\BCXJZT4F\\Boustan et al. - 2022 - Automation After the Assembly Line Computerized M.pdf:application/pdf},
}
@misc{chollet_measure_2019,
title = {On the {Measure} of {Intelligence}},
url = {http://arxiv.org/abs/1911.01547},
doi = {10.48550/arXiv.1911.01547},
abstract = {To make deliberate progress towards more intelligent and more human-like artificial systems, we need to be following an appropriate feedback signal: we need to be able to define and evaluate intelligence in a way that enables comparisons between two systems, as well as comparisons with humans. Over the past hundred years, there has been an abundance of attempts to define and measure intelligence, across both the fields of psychology and AI. We summarize and critically assess these definitions and evaluation approaches, while making apparent the two historical conceptions of intelligence that have implicitly guided them. We note that in practice, the contemporary AI community still gravitates towards benchmarking intelligence by comparing the skill exhibited by AIs and humans at specific tasks such as board games and video games. We argue that solely measuring skill at any given task falls short of measuring intelligence, because skill is heavily modulated by prior knowledge and experience: unlimited priors or unlimited training data allow experimenters to "buy" arbitrary levels of skills for a system, in a way that masks the system's own generalization power. We then articulate a new formal definition of intelligence based on Algorithmic Information Theory, describing intelligence as skill-acquisition efficiency and highlighting the concepts of scope, generalization difficulty, priors, and experience. Using this definition, we propose a set of guidelines for what a general AI benchmark should look like. Finally, we present a benchmark closely following these guidelines, the Abstraction and Reasoning Corpus (ARC), built upon an explicit set of priors designed to be as close as possible to innate human priors. We argue that ARC can be used to measure a human-like form of general fluid intelligence and that it enables fair general intelligence comparisons between AI systems and humans.},
urldate = {2023-11-03},
publisher = {arXiv},
author = {Chollet, François},
month = nov,
year = {2019},
note = {arXiv:1911.01547 [cs]},
keywords = {Computer Science - Artificial Intelligence},
file = {arXiv Fulltext PDF:C\:\\Users\\jonas\\Zotero\\storage\\MLYR2SGX\\Chollet - 2019 - On the Measure of Intelligence.pdf:application/pdf;arXiv.org Snapshot:C\:\\Users\\jonas\\Zotero\\storage\\VQ5IVF5U\\1911.html:text/html},
}
@article{dauth_adjustment_2021,
title = {The {Adjustment} of {Labor} {Markets} to {Robots}},
volume = {19},
issn = {15424766},
url = {https://search.ebscohost.com/login.aspx?direct=true&db=buh&AN=154512862&site=ehost-live},
doi = {10.1093/jeea/jvab012},
abstract = {We use detailed administrative data to study the adjustment of local labor markets to industrial robots in Germany. Robot exposure, as predicted by a shift-share variable, is associated with displacement effects in manufacturing, but those are fully offset by new jobs in services. The incidence mostly falls on young workers just entering the labor force. Automation is related to more stable employment within firms for incumbents, and this is driven by workers taking over new tasks in their original plants. Several measures indicate that those new jobs are of higher quality than the previous ones. Young workers also adapt their educational choices, and substitute away from vocational training towards colleges and universities. Finally, industrial robots have benefited workers in occupations with complementary tasks, such as managers or technical scientists.},
number = {6},
urldate = {2023-11-03},
journal = {Journal of the European Economic Association},
author = {Dauth, Wolfgang and Findeisen, Sebastian and Suedekum, Jens and Woessner, Nicole},
month = dec,
year = {2021},
note = {Publisher: Oxford University Press / USA},
keywords = {LABOR market, LABOR supply, INDUSTRIAL robots, ROBOTS, GERMANY, YOUNG workers, used},
pages = {3104--3153},
file = {EBSCO Full Text:C\:\\Users\\jonas\\Zotero\\storage\\QMIJH8QD\\Dauth et al. - 2021 - Adjustment of Labor Markets to Robots.pdf:application/pdf},
}
@article{frey_future_2017,
title = {The future of employment: {How} susceptible are jobs to computerisation?},
volume = {114},
issn = {0040-1625},
shorttitle = {The future of employment},
url = {https://www.sciencedirect.com/science/article/pii/S0040162516302244},
doi = {10.1016/j.techfore.2016.08.019},
abstract = {We examine how susceptible jobs are to computerisation. To assess this, we begin by implementing a novel methodology to estimate the probability of computerisation for 702 detailed occupations, using a Gaussian process classifier. Based on these estimates, we examine expected impacts of future computerisation on US labour market outcomes, with the primary objective of analysing the number of jobs at risk and the relationship between an occupations probability of computerisation, wages and educational attainment.},
urldate = {2023-11-03},
journal = {Technological Forecasting and Social Change},
author = {Frey, Carl Benedikt and Osborne, Michael A.},
month = jan,
year = {2017},
keywords = {Wage inequality, Employment, Occupational choice, Skill demand, Technological change, used},
pages = {254--280},
file = {ScienceDirect Snapshot:C\:\\Users\\jonas\\Zotero\\storage\\7KQ2IKKW\\S0040162516302244.html:text/html;Submitted Version:C\:\\Users\\jonas\\Zotero\\storage\\883WJIW4\\Frey and Osborne - 2017 - The future of employment How susceptible are jobs.pdf:application/pdf},
}
@article{graetz_robots_2018,
title = {Robots at {Work}},
volume = {100},
issn = {00346535},
url = {https://search.ebscohost.com/login.aspx?direct=true&db=buh&AN=133662884&site=ehost-live},
doi = {10.1162/rest_a_00754},
abstract = {We analyze for the first time the economic contributions of modern industrial robots, which are flexible, versatile, and autonomous machines. We use novel panel data on robot adoption within industries in seventeen countries from 1993 to 2007 and new instrumental variables that rely on robots' comparative advantage in specific tasks. Our findings suggest that increased robot use contributed approximately 0.36 percentage points to annual labor productivity growth, while at the same time raising total factor productivity and lowering output prices. Our estimates also suggest that robots did not significantly reduce total employment, although they did reduce low-skilled workers' employment share.},
number = {5},
urldate = {2023-11-03},
journal = {Review of Economics \& Statistics},
author = {Graetz, Georg and Michaels, Guy},
month = dec,
year = {2018},
note = {Publisher: MIT Press},
keywords = {LABOR productivity, INDUSTRIAL robots, ROBOTS, AUTOMATIC machinery, INDUSTRIAL productivity},
pages = {753--768},
file = {EBSCO Full Text:C\:\\Users\\jonas\\Zotero\\storage\\V48S8YKT\\Graetz and Michaels - 2018 - Robots at Work.pdf:application/pdf},
}
@article{karabarbounis_global_2014,
title = {The {Global} {Decline} of the {Labor} {Share}},
volume = {129},
issn = {1531-4650, 0033-5533},
url = {https://academic.oup.com/qje/article/129/1/61/1899422},
doi = {10.1093/qje/qjt032},
abstract = {Abstract
The stability of the labor share of income is a key foundation in macroeconomic models. We document, however, that the global labor share has significantly declined since the early 1980s, with the decline occurring within the large majority of countries and industries. We show that the decrease in the relative price of investment goods, often attributed to advances in information technology and the computer age, induced firms to shift away from labor and toward capital. The lower price of investment goods explains roughly half of the observed decline in the labor share, even when we allow for other mechanisms influencing factor shares, such as increasing profits, capital-augmenting technology growth, and the changing skill composition of the labor force. We highlight the implications of this explanation for welfare and macroeconomic dynamics.},
language = {en},
number = {1},
urldate = {2023-11-03},
journal = {The Quarterly Journal of Economics},
author = {Karabarbounis, Loukas and Neiman, Brent},
month = feb,
year = {2014},
keywords = {used},
pages = {61--103},
file = {Karabarbounis and Neiman - 2014 - The Global Decline of the Labor Share.pdf:C\:\\Users\\jonas\\Zotero\\storage\\IM7HX7F5\\Karabarbounis and Neiman - 2014 - The Global Decline of the Labor Share.pdf:application/pdf},
}
@article{mokyr_history_2015,
title = {The {History} of {Technological} {Anxiety} and the {Future} of {Economic} {Growth}: {Is} {This} {Time} {Different}?},
volume = {29},
issn = {08953309},
shorttitle = {The {History} of {Technological} {Anxiety} and the {Future} of {Economic} {Growth}},
url = {https://search.ebscohost.com/login.aspx?direct=true&db=buh&AN=108621573&site=ehost-live},
doi = {10.1257/jep.29.3.31},
abstract = {Technology is widely considered the main source of economic progress, but it has also generated cultural anxiety throughout history. The developed world is now suffering from another bout of such angst. Anxieties over technology can take on several forms, and we focus on three of the most prominent concerns. First, there is the concern that technological progress will cause widespread substitution of machines for labor, which in turn could lead to technological unemployment and a further increase in inequality in the short run, even if the long-run effects are beneficial. Second, there has been anxiety over the moral implications of technological process for human welfare, broadly defined. While, during the Industrial Revolution, the worry was about the dehumanizing effects of work, in modern times, perhaps the greater fear is a world where the elimination of work itself is the source of dehumanization. A third concern cuts in the opposite direction, suggesting that the epoch of major technological progress is behind us. Understanding the history of technological anxiety provides perspective on whether this time is truly different. We consider the role of these three anxieties among economists, primarily focusing on the historical period from the late 18th to the early 20th century, and then compare the historical and current manifestations of these three concerns.},
number = {3},
urldate = {2023-11-03},
journal = {Journal of Economic Perspectives},
author = {Mokyr, Joel and Vickers, Chris and Ziebarth, Nicolas L.},
year = {2015},
note = {Publisher: American Economic Association},
keywords = {UNEMPLOYMENT, ECONOMIC development research, PUBLIC welfare, TECHNOLOGICAL revolution, used},
pages = {31--50},
file = {EBSCO Full Text:C\:\\Users\\jonas\\Zotero\\storage\\JCXNARKA\\Mokyr et al. - 2015 - The History of Technological Anxiety and the Futur.pdf:application/pdf},
}
@article{zeira_workers_1998,
title = {Workers, {Machines}, and {Economic} {Growth}*},
volume = {113},
issn = {0033-5533},
url = {https://doi.org/10.1162/003355398555847},
doi = {10.1162/003355398555847},
abstract = {This paper analyzes a model of economic growth, with technological innovations that reduce labor requirements but raise capital requirements. The paper has two main results. The first is that such technological innovations are not everywhere adopted, but only in countries with high productivity. The second result is that technology adoption significantly amplifies differences in productivity between countries. This paper can, therefore, add to our understanding of large and persistent international differences in output per capita. The model also helps to explain other growth phenomena, like divergence or periods of rapid growth.},
number = {4},
urldate = {2023-11-03},
journal = {The Quarterly Journal of Economics},
author = {Zeira, Joseph},
month = nov,
year = {1998},
pages = {1091--1117},
file = {Full Text PDF:C\:\\Users\\jonas\\Zotero\\storage\\ZMVJZST7\\Zeira - 1998 - Workers, Machines, and Economic Growth.pdf:application/pdf;Snapshot:C\:\\Users\\jonas\\Zotero\\storage\\5Y78WK4R\\1916985.html:text/html},
}
@misc{anderson_automation_2017,
title = {Automation in {Everyday} {Life}},
url = {https://www.pewresearch.org/internet/2017/10/04/automation-in-everyday-life/},
abstract = {Although Americans expect certain positive outcomes from developments in automation, they are worried and concerned about the implications of these technologies for society as a whole.},
language = {en-US},
urldate = {2023-11-05},
journal = {Pew Research Center: Internet, Science \& Tech},
author = {Anderson, Aaron Smith {and} Monica},
month = oct,
year = {2017},
file = {Anderson - 2017 - Automation in Everyday Life.pdf:C\:\\Users\\jonas\\Zotero\\storage\\BYVSPHBJ\\Anderson - 2017 - Automation in Everyday Life.pdf:application/pdf;Snapshot:C\:\\Users\\jonas\\Zotero\\storage\\7YYIIZLV\\automation-in-everyday-life.html:text/html},
}
@article{autor_skill_2003,
title = {The {Skill} {Content} of {Recent} {Technological} {Change}: {An} {Empirical} {Exploration}*},
volume = {118},
issn = {0033-5533},
shorttitle = {The {Skill} {Content} of {Recent} {Technological} {Change}},
url = {https://doi.org/10.1162/003355303322552801},
doi = {10.1162/003355303322552801},
abstract = {We apply an understanding of what computers do to study how computerization alters job skill demands. We argue that computer capital (1) substitutes for workers in performing cognitive and manual tasks that can be accomplished by following explicit rules; and (2) complements workers in performing nonroutine problem-solving and complex communications tasks. Provided that these tasks are imperfect substitutes, our model implies measurable changes in the composition of job tasks, which we explore using representative data on task input for 1960 to 1998. We find that within industries, occupations, and education groups, computerization is associated with reduced labor input of routine manual and routine cognitive tasks and increased labor input of nonroutine cognitive tasks. Translating task shifts into education demand, the model can explain 60 percent of the estimated relative demand shift favoring college labor during 1970 to 1998. Task changes within nominally identical occupations account for almost half of this impact.},
number = {4},
urldate = {2023-11-06},
journal = {The Quarterly Journal of Economics},
author = {Autor, David H. and Levy, Frank and Murnane, Richard J.},
month = nov,
year = {2003},
pages = {1279--1333},
file = {Full Text PDF:C\:\\Users\\jonas\\Zotero\\storage\\EI2SK384\\Autor et al. - 2003 - The Skill Content of Recent Technological Change .pdf:application/pdf;Snapshot:C\:\\Users\\jonas\\Zotero\\storage\\WU4DD2ZG\\1925105.html:text/html},
}
@misc{webb_impact_2019,
address = {Rochester, NY},
type = {{SSRN} {Scholarly} {Paper}},
title = {The {Impact} of {Artificial} {Intelligence} on the {Labor} {Market}},
url = {https://papers.ssrn.com/abstract=3482150},
doi = {10.2139/ssrn.3482150},
abstract = {I develop a new method to predict the impacts of a technology on occupations. I use the overlap between the text of job task descriptions and the text of patents to construct a measure of the exposure of tasks to automation. I first apply the method to historical cases such as software and industrial robots. I establish that occupations I measure as highly exposed to previous automation technologies saw declines in employment and wages over the relevant periods. I use the fitted parameters from the case studies to predict the impacts of artificial intelligence. I find that, in contrast to software and robots, AI is directed at high-skilled tasks. Under the assumption that the historical pattern of long-run substitution will continue, I estimate that AI will reduce 90:10 wage inequality, but will not affect the top 1\%.},
language = {en},
urldate = {2023-11-06},
author = {Webb, Michael},
month = nov,
year = {2019},
keywords = {occupations, technology, patents, artificial intelligence, robotics, used},
file = {Full Text PDF:C\:\\Users\\jonas\\Zotero\\storage\\7KPWV7NV\\Webb - 2019 - The Impact of Artificial Intelligence on the Labor.pdf:application/pdf},
}