From Immigrants to Robots: The Changing Locus of Substitutes for Workers

Borjas, George J.; Freeman, Richard

doi:10.2139/ssrn.3315244

Cited by 4 publications

(12 citation statements)

References 6 publications

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“…Many of the items our participants flagged as essential for living a good life are covered by the composite measures, we gave to the participants such as basic needs including food and water, forming relationships, social interactions, support system, financial stability, socioeconomic status, and various forms of health. Other social and ethical issues mentioned in the AI/ML literature could be added as indicators of the ability to have a good life, such as freedom of thought, to live out one’s purpose, mindset, contentment, being happy, privacy, data protection, technological deskilling (Vesnic-Alujevic et al 2020 ), solidarity (European Group on Ethics in Science and New Technologies 2018 ; The IEEE Global Initiative on Ethics of Autonomous and Intelligent Systems 2019 ), equity and equality (European Group on Ethics in Science and New Technologies 2018 ; The IEEE Global Initiative on Ethics of Autonomous and Intelligent Systems 2019 ; Yuste et al 2017 ), respecting (Malti et al 2020 ), being respected (Steckermeier and Delhey 2019 ), dignity, health equity (Wolbring 2021 ), ethnic, gender, and social bias (Allen and Dreyer 2019 ; Pham et al 2021 ; Straw 2020 ; Tat et al 2020 ; Walsh 2019 ; Weissglass 2021 ), and various types of well-being that are noted to be impacted by AI/ML such as emotional well-being (Borjas and Freeman 2019 ; Fratczak et al 2019 ; Khosla and Chu 2013 ; West 2018 ), sense of well-being and identity (Abeles 2016 ), economic well-being (Borjas and Freeman 2019 ; Fratczak et al 2019 ; Press 1982 ; Ullrich et al 2016 ; West 2018 ) and societal well-being (Reddy 2006 ). Making one big list of the indicators allows for obtaining insight into the views of participants on the impact of AI/ML on the ability to have a good life and for that matter many other technologies.…”

Section: Discussionmentioning

confidence: 99%

Section: Ai/ml and The Ability To Have A Good Lifementioning

confidence: 99%

“…Justice, solidarity, equity, and equality are concepts mentioned in many AI governance documents that influence the ability to have a good life (Lillywhite and Wolbring 2020 ). AI/ML impact various forms of well-being that reflect facets of the ability to have a good life such as emotional well-being (Borjas and Freeman 2019 ; Fratczak et al 2019 ; Khosla and Chu 2013 ; West 2018 ), sense of well-being and identity (Abeles 2016 ), economic well-being (Borjas and Freeman 2019 ; Fratczak et al 2019 ; West 2018 ), the general well-being of a nation's economy (Press 1982 ; Ullrich et al 2016 ), well-being of society (Reddy 2006 ), and societal well-being (Aluaş and Bolboacă, 2019 ; National Academies of Sciences 2018 ). The report, ETHICALLY ALIGNED DESIGN A Vision for Prioritizing Human Well-being with Autonomous and Intelligent Systems focuses on how well-being including “societal and environmental well-being” can be improved (The IEEE Global Initiative on Ethics of Autonomous and Intelligent Systems 2019 , p. 1) and suggests various measures.…”

Section: Introductionmentioning

confidence: 99%

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Auditing the impact of artificial intelligence on the ability to have a good life: using well-being measures as a tool to investigate the views of undergraduate STEM students

Lillywhite

Wolbring

2023

AI & Soc

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AI/ML increasingly impacts the ability of humans to have a good life. Various sets of indicators exist to measure well-being/the ability to have a good life. Students play an important role in AI/ML discussions. The purpose of our study using an online survey was to learn about the perspectives of undergraduate STEM students on the impact of AI/ML on well-being/the ability to have a good life. Our study revealed that many of the abilities participants perceive to be needed for having a good life were part of the well-being/ability to have a good life indicator lists we gave to participants. Participants perceived AI/ML to have and continue to have the most positive impact on the ability to have a good life for disabled people, elderly people, and individuals with a high income and the least positive impact for people of low income and countries from the global south. Regarding indicators of well-being and the ability to have a good life given to participants, we found a significant techno-positive sentiment. 30% of respondents selected the purely positive box for 28 of the indicators and none did so for the purely negative box. For 52 indicators, the purely negative was below 10% (not counting the 0%) and for 10 indicators, none selected purely negative. Our findings suggest that our questions might be valuable tools to develop an inventory of STEM and other students’ perspectives on the implications of AI/ML on the ability to have a good life.

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Section: Discussionmentioning

confidence: 99%

Section: Ai/ml and The Ability To Have A Good Lifementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Auditing the impact of artificial intelligence on the ability to have a good life: using well-being measures as a tool to investigate the views of undergraduate STEM students

Lillywhite

Wolbring

2023

AI & Soc

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“…The IFR estimates the operational stock of industrial robots from annual robot shipments, by assuming that a robot depreciates at a rate of 100% after 12 years of use. Since we encountered several problems with the original stock data, we follow Borjas and Freeman (2019), Graetz and Michaels (2018) and others in reconstructing the robot stock ourselves based on the annual shipment data and a yearly depreciation rate of 10%. Our results do not change qualitatively if we use depreciation rates of 5% or 15% or assume full depreciation after 12 years.…”

Section: Methodsmentioning

confidence: 99%

“…De Backer et al (2018) analyse the period 2000–2014 and find a positive correlation between robots and employment in developed countries (depending on the years analysed) and no correlation for developing countries. Borjas and Freeman (2019) use data from the American Community Survey (ACS) on employment and find that between 2004 and 2016 there has been a negative correlation between robots and employment, in particular low-skill employment, in the US.…”

Section: Previous Literature On Robots and Employmentmentioning

confidence: 99%

Do robots really destroy jobs? Evidence from Europe

Klenert

Fernández‐Macías

Antón

2022

Economic and Industrial Democracy

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While citizen opinion polls reveal that Europeans are concerned about the labour market consequences of technological progress, our understanding of the actual significance of this association is still imperfect. In this article, the authors assess the relationship between robot adoption and employment in Europe. Combining industry-level data on employment by skill type with data on robot adoption and using different sets of fixed-effects techniques, the study finds that robot use is associated with an increase in aggregate employment. Contrary to some previous studies, the authors do not find evidence of robots reducing the share of low-skill workers across Europe. Since the overwhelming majority of industrial robots are used in manufacturing, the findings should not be interpreted outside of the manufacturing context. However, the results still hold when including non-manufacturing sectors and they are robust across a wide range of assumptions and econometric specifications.

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Conceptualising the robotisation of manufacturing work: a thematic analysis of the literature using soft systems thinking as lens

Stingl,

Christiansen,

Hansen

et al. 2024

JMTM

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PurposeThe introduction of robots as value-adding “workers” on the shop floor triggers complex changes to manufacturing work. Such changes involve highly entangled relationships between technology, organisation and people. Understanding such entanglements requires a holistic assessment of contemporary robotised manufacturing work, to anticipate the dynamically emerging opportunities and risks of robotised work.Design/methodology/approachA systematic literature review of 87 papers was conducted to capture relevant themes of change in robotised manufacturing work. The literature was analysed using a thematic analysis approach, with Checkland’s soft systems thinking as an analytical framework.FindingsBased on the literature analysis, the authors present a systemic conceptualisation of robotised manufacturing work. Specifically, the conceptualisation highlights four entangled themes of change: work, organisation of labour, workers’ (experiences) and the firm’s environment. Moreover, the authors discuss the complex patterns of interactions between these objects as relationships that defy straightforward cause–effect models.Practical implicationsThe findings draw attention to complex interactions between robotisation and manufacturing work. It can, therefore, inform strategic decisions and support projects for robotisation from a holistic perspective.Originality/valueThe authors present a novel approach to studying and designing robotised manufacturing work as a conceptual system. In particular, the paper shifts the focus towards crucial properties of the system, which are subject to complex changes alongside the introduction of robot technology in manufacturing. Soft systems thinking enables new research avenues to explain complex phenomena at the intersection of robotisation and manufacturing work.

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From Immigrants to Robots: The Changing Locus of Substitutes for Workers

Cited by 4 publications

References 6 publications

Auditing the impact of artificial intelligence on the ability to have a good life: using well-being measures as a tool to investigate the views of undergraduate STEM students

Auditing the impact of artificial intelligence on the ability to have a good life: using well-being measures as a tool to investigate the views of undergraduate STEM students

Do robots really destroy jobs? Evidence from Europe

Conceptualising the robotisation of manufacturing work: a thematic analysis of the literature using soft systems thinking as lens

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