@article {Gentili2020,
	title = {Are machines stealing our jobs?},
	journal = {Cambridge Journal of Regions, Economy and Society},
	volume = {13},
	number = {1},
	year = {2020},
	pages = {153{\textendash}173},
	abstract = {This study aims to contribute empirical evidence to the debate about the future of work in an increasingly robotised world. We implement a data-driven approach to study the technological transition in six leading Organisation for Economic Co-operation and Development (OECD) countries. First, we perform a cross-country and cross-sector cluster analysis based on the OECD-STAN database. Second, using the International Federation of Robotics database, we bridge these results with those regarding the sectoral density of robots. We show that the process of robotisation is industry- and country-sensitive. In the future, participants in the political and academic debate may be split into optimists and pessimists regarding the future of human labour; however, the two stances may not be contradictory.},
	keywords = {cluster analysis, e24, e66, j24, jel classifications, labour dislocation, robotisation},
	issn = {1752-1378},
	doi = {10.1093/cjres/rsz025},
	author = {Gentili, Andrea and Compagnucci, Fabiano and Gallegati, Mauro and Valentini, Enzo}
}
@article {Johnson2020,
	title = {The benefits of eHRM and AI for talent acquisition},
	journal = {Journal of Tourism Futures},
	year = {2020},
	abstract = {Purpose : The hospitality and tourism industry faces a number of workforce challenges, especially the high turnover rates and associated replacement costs associated with continually identifying and hiring new employees. The purpose of this paper is to discuss how hospitality and tourism organizations can use electronic human resource management (eHRM) and artificial intelligence (AI) to help recruit and select qualified employees, increase individual retention rates and decrease the time needed to replace employees. Specifically, it discusses how e-recruiting and e-selection and AI tools can help hospitality and tourism organizations improve recruiting and selection outcomes. Design/methodology/approach: Research on eHRM, AI, employee recruitment and employee selection are applied to the hospitality and tourism industry and insights for how eHRM and AI can be applied to the industry are discussed. Findings: eHRM and AI have the potential to transform how the hospitality and tourism industry recruit and select employees. However, care must be taken to ensure that the insights gained and the decisions made are well received by employees and lead to better employee and organizational outcomes. Research limitations/implications: This paper represents the first research that integrates research from eHRM and AI and applies it to the hospitality and tourism industry. Originality/value: This paper represents the first research that integrates research from eHRM and AI and applies it to the hospitality and tourism industry.},
	keywords = {artificial intelligence, e-HRM, e-recruiting, e-selection, eHRM, Electronic human resource management, Employee selection, Recruitment, Selection},
	issn = {2055592X},
	doi = {10.1108/JTF-02-2020-0013},
	author = {Johnson, Richard D and Stone, Dianna L and Lukaszewski, Kimberly M}
}
@article {Huang2020,
	title = {Engaged to a Robot? The Role of AI in Service},
	journal = {Journal of Service Research},
	year = {2020},
	abstract = {This article develops a strategic framework for using artificial intelligence (AI) to engage customers for different service benefits. This framework lays out guidelines of how to use different AIs to engage customers based on considerations of nature of service task, service offering, service strategy, and service process. AI develops from mechanical, to thinking, and to feeling. As AI advances to a higher intelligence level, more human service employees and human intelligence (HI) at the intelligence levels lower than that level should be used less. Thus, at the current level of AI development, mechanical service should be performed mostly by mechanical AI, thinking service by both thinking AI and HI, and feeling service mostly by HI. Mechanical AI should be used for standardization when service is routine and transactional, for cost leadership, and mostly at the service delivery stage. Thinking AI should be used for personalization when service is data-rich and utilitarian, for quality leadership, and mostly at the service creation stage. Feeling AI should be used for relationalization when service is relational and high touch, for relationship leadership, and mostly at the service interaction stage. We illustrate various AI applications for the three major AI benefits, providing managerial guidelines for service providers to leverage the advantages of AI as well as future research implications for service researchers to investigate AI in service from modeling, consumer, and policy perspectives.},
	keywords = {artificial intelligence, augmentation, automation, engagement, feeling AI, human intelligence, mechanical AI, personalization, relationalization, replacement, robots, service process, service strategy, standardization, thinking AI},
	issn = {15527379},
	doi = {10.1177/1094670520902266},
	author = {Huang, Ming Hui and Rust, Roland T}
}
@article {GomezdeAgreda2020,
	title = {Ethics of autonomous weapons systems and its applicability to any AI systems},
	journal = {Telecommunications Policy},
	volume = {5},
	number = {5},
	year = {2020},
	pages = {101953},
	publisher = {Elsevier Ltd},
	abstract = {Most artificial intelligence technologies are dual-use. They are incorporated into both peaceful civilian applications and military weapons systems. Most of the existing codes of conduct and ethical principles on artificial intelligence address the former while largely ignoring the latter. But when these technologies are used to power systems specifically designed to cause harm, the question must be asked as to whether the ethics applied to military autonomous systems should also be taken into account for all artificial intelligence technologies susceptible of being used for those purposes. However, while a freeze in investigations is neither possible nor desirable, neither is the maintenance of the current status quo. Comparison between general-purpose ethical codes and military ones concludes that most ethical principles apply to human use of artificial intelligence systems as long as two characteristics are met: that the way algorithms work is understood and that humans retain enough control. In this way, human agency is fully preserved and moral responsibility is retained independently of the potential dual-use of artificial intelligence technology.},
	keywords = {AI ethics, Autonomous weapons, CCW, Dual-use AI, Explainability, Meaningful human control},
	issn = {03085961},
	doi = {10.1016/j.telpol.2020.101953},
	url = {https://doi.org/10.1016/j.telpol.2020.101953},
	author = {G{\'o}mez de {\'A}greda, {\'A}ngel}
}
@article {Hacker2020,
	title = {Explainable AI under contract and tort law: legal incentives and technical challenges},
	journal = {Artificial Intelligence and Law},
	number = {0123456789},
	year = {2020},
	publisher = {Springer Netherlands},
	abstract = {This paper shows that the law, in subtle ways, may set hitherto unrecognized incentives for the adoption of explainable machine learning applications. In doing so, we make two novel contributions. First, on the legal side, we show that to avoid liability, professional actors, such as doctors and managers, may soon be legally compelled to use explainable ML models. We argue that the importance of explainability reaches far beyond data protection law, and crucially influences questions of contractual and tort liability for the use of ML models. To this effect, we conduct two legal case studies, in medical and corporate merger applications of ML. As a second contribution, we discuss the (legally required) trade-off between accuracy and explainability and demonstrate the effect in a technical case study in the context of spam classification.},
	keywords = {Contract law, Corporate takeovers, Explainability, Explainability-accuracy trade-off, Explainable AI, Interpretable machine learning, Medical malpractice, Tort law},
	isbn = {0123456789},
	issn = {15728382},
	doi = {10.1007/s10506-020-09260-6},
	url = {https://doi.org/10.1007/s10506-020-09260-6},
	author = {Hacker, Philipp and Krestel, Ralf and Grundmann, Stefan and Naumann, Felix}
}
@article {Reid-musson2020,
	title = {Feminist economic geography and the future of work},
	journal = {EPA: Economy and Space},
	year = {2020},
	pages = {1{\textendash}12},
	keywords = {corresponding author, department of geography, emily reid-musson, feminist economic geography, memorial university of newfoundland, newfoundland and labrador a1c, social reproduction, subjectivity, technology, work},
	doi = {10.1177/0308518X20947101},
	author = {Reid-musson, Emily and Cockayne, Daniel and Frederiksen, Lia and Worth, Nancy}
}
@article {EganadelSol2020,
	title = {The Future of Work in Developing Economies},
	journal = {MIT Sloan Management Review},
	volume = {61},
	number = {2},
	year = {2020},
	pages = {1{\textendash}3},
	abstract = {<p>Much has been written about the rise of automation in developed countries. Economists have been busily creating models seeking to quantify the likely impact of automation on employment. However, far less has been written about the potential effects on work in developing nations. This is surprising, given that automation may be especially troublesome for developing economies. Here, del Sol and Joyce examine the effects of large-scale automation on workers in developing countries.</p>},
	keywords = {Armenia, Asia, Austria, automation, Bolivia, Business And Economics{\textendash}Management, China, Developing countries{\textendash}LDCs, Employment, future, Georgia (country), Ghana, Impact analysis, Kenya, Kuala Lumpur Malaysia, Laos, Republic of North Macedonia, South Korea, Sri Lanka, United States{\textendash}US, Vietnam, Workers},
	issn = {15329194},
	author = {Egana del Sol, Pablo and Joyce, Connor and Del Sol, Pablo Ega{\~n}a and Joyce, Connor}
}
@article {Jung2020,
	title = {Industrial robots, employment growth, and labor cost: A simultaneous equation analysis},
	journal = {Technological Forecasting and Social Change},
	volume = {159},
	number = {June},
	year = {2020},
	pages = {120202},
	publisher = {Elsevier},
	abstract = {In recent years, the global rapid expansion of industrial robots has induced ever-increasing concerns for the cause and effect of such growth, particularly with regard to its relationship with labor. This paper analyzes the factors underlying the adoption of industrial robots, employment growth and structure, and labor costs, taking into account the two-way causalities between these variables. For the empirical analysis, we use the three-stage least squares (3SLS) method for the system of simultaneous equations and apply it to the panel data constructed for 42 countries. Explanatory variables for each equation include the dependent variables of other equations and exogenous variables, such as the labor market environment, physical and human capital, and country-specific social environment. The empirical results of the present study indicate that the increase in both unit labor costs and hourly compensation level induces an extensive application of industrial robots. Subsequently, the expansion of industrial robots leads to a reduction of unit labor costs; however, the hourly compensation level increases, implying that the productivity-enhancing effect exceeds the wage-increasing effect of industrial robots. The extensive use of industrial robots tends to suppress employment growth, confirming the labor-substituting effect of industrial robots; the observed trend disproportionately affects low-skilled labor.},
	keywords = {Compensation level, Employment growth, Industrial robots, Labor cost, Simultaneous equation analysis},
	issn = {00401625},
	doi = {10.1016/j.techfore.2020.120202},
	url = {https://doi.org/10.1016/j.techfore.2020.120202},
	author = {Jung, Jin Hwa and Lim, Dong Geon}
}
@article {Kernbach2020,
	title = {Machine learning-based clinical prediction modeling {\textendash} A practical guide for clinicians},
	journal = {Artificial Intelligence in Precision Health},
	number = {June},
	year = {2020},
	pages = {257{\textendash}278},
	publisher = {Elsevier Inc.},
	keywords = {Alzheimers disease detection, artificial intelligence, Convolutional neural networks, Deep neural networks, Ensemble machine learning methods},
	isbn = {9780128171332},
	doi = {10.1016/b978-0-12-817133-2.00011-2},
	url = {https://arxiv.org/abs/2006.15069v1 http://dx.doi.org/10.1016/B978-0-12-817133-2.00011-2},
	author = {Kernbach, Julius M. and Staartjes, Victor E.}
}
@article {McLeay2020,
	title = {Replaced by a Robot: Service Implications in the Age of the Machine},
	journal = {Journal of Service Research},
	year = {2020},
	abstract = {Service organizations, emboldened by the imperative to innovate, are increasingly introducing robots to frontline service encounters. However, as they augment or substitute human employees with robots, they may struggle to convince a distrusting public of their brand{\textquoteright}s ethical credentials. Consequently, this article develops and tests a holistic framework to ascertain a deeper understanding of customer perceptions of frontline service robots (FLSRs) than has previously been attempted. Our experimental studies investigate the effects of the (1) role (augmentation or substitution of human employees or no involvement) and (2) type (humanoid FLSR vs. self-service machine) of FLSRs under the following service contexts: (a) value creation model (asset-builder, service provider) and (b) service type (experience, credence). By empirically establishing our framework, we highlight how customers{\textquoteright} personal characteristics (openness-to-change and preference for ethical/responsible service provider) and cognitive evaluations (perceived innovativeness, perceived ethical/societal reputation, and perceived innovativeness-responsibility fit) influence the impact that FLSRs have on service experience and brand usage intent. Our findings operationalize and empirically support seminal frameworks from extant literature, as well as elaborate on the positive and negative implications of using robots to complement or replace service employees. Further, we consider managerial and policy implications for service in the age of machines.},
	keywords = {brand usage intent, ethical/societal reputation, service experience, service innovativeness, service robots},
	issn = {15527379},
	doi = {10.1177/1094670520933354},
	author = {McLeay, Fraser and Osburg, Victoria Sophie and Yoganathan, Vignesh and Patterson, Anthony}
}
@article {2019,
	title = {The impact of automation technologies for employment in Northern Ireland},
	year = {2019},
	publisher = {Nevin Economic Research Institute},
	keywords = {economics of automation},
	url = {https://www.nerinstitute.net/research/the-future-of-work-the-impact-of-automation-techno-1/},
	author = {Lisa Wilson and Paul Mac Flynn}
}
@article {2019,
	title = {Integrating ethical values and economic value to steer progress in Artificial Intelligenc},
	year = {2019},
	month = {08/2019},
	keywords = {ethics},
	url = {https://www.nber.org/papers/w26130},
	author = {Anton Korinek}
}
@article {2019,
	title = {A Review of the Social Impacts and Ethical Implications of Artificial Intelligence},
	year = {2019},
	publisher = {Global AI Ethics},
	keywords = {ethics},
	url = {https://arxiv.org/ftp/arxiv/papers/1907/1907.07892.pdf},
	author = {Alexa Hagerty and Igor Rubinov}
}
@article {2019,
	title = {Is this time different? A note on automation and labour in the fourth industrial revolution},
	journal = {Journal of Industrial and Business Economics},
	volume = {46},
	year = {2019},
	month = {Jan-09-2019},
	pages = {323 - 331},
	keywords = {economics of automation},
	issn = {0391-2078},
	doi = {10.1007/s40812-019-00123-z},
	author = {Marengo, Luigi}
}
@article {2019,
	title = {Towards an AI economy that works for all},
	year = {2019},
	month = {02/2019},
	keywords = {ethics},
	url = {https://www.keystoneresearch.org/sites/default/files/FOW_TowardAIEconomyForAllFinalEdit.pdf},
	author = {Stephen Herzenberg and John Alic}
}
@article {2018,
	title = {Artificial Intelligence in Medicine and Radiation Oncology},
	journal = {Cureus},
	year = {2018},
	month = {Jan-04-2019},
	abstract = {Artificial Intelligence (AI) was reviewed with a focus on its potential applicability to radiation oncology. The improvement of process efficiencies and the prevention of errors were found to be the most significant contributions of AI to radiation oncology. It was found that the prevention of errors is most effective when data transfer processes were automated and operational decisions were based on logical or learned evaluations by the system. It was concluded that AI could greatly improve the efficiency and accuracy of radiation oncology operations.},
	keywords = {artificial intelligence, big data, error analysis, error prevention, machine learning, process efficiency, process optimization, quality improvement, radiation oncology},
	doi = {10.7759/cureus.2475},
	url = {https://www.cureus.com/articles/11443-artificial-intelligence-in-medicine-and-radiation-oncology},
	author = {Weidlich, Vincent and Weidlich, Georg A.}
}
@article {2018,
	title = {Artificial intelligence, jobs,  inequality and productivity:  Does aggregate demand matter},
	number = {ISSN 1871-9872},
	year = {2018},
	publisher = {Maastricht University},
	keywords = {artificial intelligence, economics of automation, growth theory, innovation, labour demand, productivity, technology},
	url = {http://ftp.iza.org/dp12005.pdf},
	author = {Thomas Gries and Wim Naude}
}
@article {2018,
	title = {Automation and the future of jobs in India},
	year = {2018},
	month = {11/2018},
	publisher = {University of Pennsylvania},
	type = {Economy, Politics, Science and Technology},
	keywords = {economics of automation},
	url = {https://casi.sas.upenn.edu/iit/kuriakoseiyer},
	author = {Francis Kuriakose and Deepa Iyer}
}
@article {2018,
	title = {Economic policy for artificial intelligence},
	number = {24690},
	year = {2018},
	month = {06/2018},
	abstract = {Recent progress in artificial intelligence (AI) {\textendash} a general purpose technology affecting many industries - has been focused on advances in machine learning, which we recast as a quality-adjusted drop in the price of prediction. How will this sharp drop in price impact society? Policy will influence the impact on two key dimensions: diffusion and consequences. First, in addition to subsidies and IP policy that will influence the diffusion of AI in ways similar to their effect on other technologies, three policy categories - privacy, trade, and liability - may be uniquely salient in their influence on the diffusion patterns of AI. Second, labor and antitrust policies will influence the consequences of AI in terms of employment, inequality, and competition.},
	keywords = {economics of automation},
	url = {https://econpapers.repec.org/paper/nbrnberwo/24690.htm},
	author = {Ajay Agrawal and Joshua Gans and Avi Goldfarb}
}
@mastersthesis {2018,
	title = {Economies of the future: Robots and Artificial Intelligence, the new economic motor or downfall of the working class?},
	year = {2018},
	month = {11/2018},
	type = {master thesis},
	abstract = {Technological progress and innovation have significantly contributed to global economic growth, societal advancement, and higher living standards. However, there is growing concern over the future that lies ahead because of increasing robotisation and progress in artificial intelligence (AI), which are feared to cause significant loss of labour demand. The body of posterior economic scientific work addressing this topic mostly concludes on a positive note. Namely, recent technological advancements have resulted in a net increase in labour demand, but this demand is redistributed to different tasks and occupations. Yet, future oriented research, most notably by Frey and Osborne (2017), has sparked a debate on the future of work due to estimations that indicate that over 40\% of jobs will become automatable in the next 20 years. Therefore, the societal question remains: Robots and Artificial Intelligence, the new economic motor or downfall of the working class?},
	keywords = {economics of automation},
	url = {https://repository.tudelft.nl/islandora/object/uuid\%3Af30b5d2e-d48d-4c90-8780-3d55a2e1a7d3},
	author = {Koen Spaanderman}
}
@article {2018,
	title = {Experimental evidence on complimentarities between human capital and machine learning},
	year = {2018},
	month = {01/2018},
	keywords = {economics of automation},
	url = {https://hbswk.hbs.edu/item/different-strokes-for-different-folks-experimental-evidence-on-complementarities-between-human-capital-and-machine-learning},
	author = {Prithwiraj Choudhury and Evan Starr and Rajshree Agarwal}
}
@article {2018,
	title = {How real is the impact of artificial intelligence? The business information survey 2018},
	journal = {Business Information Review},
	volume = {35},
	year = {2018},
	month = {12/2019},
	pages = {99 - 115},
	keywords = {Artificial Intelligence (AI), blockchain, chatbot, cybersecurity, data economy, data governance, data lakes, data literacy, data quality, data trusts, data value, ethics, information literacy, intelligent virtual agents, machine learning (ML), Robotics},
	issn = {0266-3821},
	doi = {10.1177/0266382118790150},
	url = {http://journals.sagepub.com/doi/10.1177/0266382118790150},
	author = {Carter, Denise}
}
@book {2018,
	title = {How unequal? Insights on inequality },
	series = {CEDA {\textendash} the Committee for Economic Development of Australia},
	year = {2018},
	month = {04/2018},
	keywords = {ethics},
	isbn = {0 85801 318 5},
	url = {https://www.ceda.com.au/CEDA/media/General/Publication/PDFs/CEDA-How-unequal-Insights-on-inequality-April-2018-FINAL_WEB.pdf}
}
@article {2018,
	title = { The impact of industrial robots on eu employment and wages: A local labour market approach},
	year = {2018},
	month = {04/2018},
	publisher = {bruegel},
	keywords = {economics of automation},
	url = {https://bruegel.org/2018/04/the-impact-of-industrial-robots-on-eu-employment-and-wages-a-local-labour-market-approach/},
	author = {Francesco Chiacchio and Georgios Petropoulos and David Pichler}
}
@article {2018,
	title = {The internet and jobs opportunities and ambiguous trends},
	year = {2018},
	month = {02/2018},
	keywords = {economics of automation},
	url = {https://www.ceps.eu/system/files/PI2018_06_LP-EN-LW_InternetAndJobs.pdf},
	author = {Lorenzo Pupillo and Eli Noam and Leonard Waverman}
}
@proceedings {2018,
	title = {Recent advances in social \& cognitive robotics and imminent ethical challenges},
	volume = {211},
	year = {2018},
	keywords = {ethics},
	url = {https://www.atlantis-press.com/proceedings/rais-18/25902731},
	author = {Ali Meghdari and Minoo Alemi}
}
@article {2018,
	title = { Robots worldwide: The impact of automation on employment and trade},
	number = {36},
	year = {2018},
	month = {10/2018},
	keywords = {economics of automation, Employment, off-shoring, re-shoring, robot, technology},
	url = {https://www.ilo.org/wcmsp5/groups/public/---dgreports/---inst/documents/publication/wcms_648063.pdf},
	author = {Francesco Carnonero and Ekkehard Ernst and Enzo Weber}
}
@conference {2018,
	title = {Work that Enables Care: Understanding Tasks, Automation, and the National Health Service},
	booktitle = {iConference},
	year = {2018},
	publisher = {Springer},
	organization = {Springer},
	abstract = {Automation of jobs is discussed as a threat to many job occupations, but in the UK healthcare sector many view technology and automation as a way to save a threatened system. However, existing quantitative models that rely on occupation-level measures of the likelihood of automation suggest that few healthcare occupations are susceptible to automation. In order to improve these quantitative models, we focus on the potential impacts of task-level automation on health work, using qualitative ethnographic research to understand the mundane information work in general practices. By understanding the detailed tasks and variations of information work, we are building a more complete and accurate understanding of how healthcare staff work and interact with technology and with each other, often mediated by technology.},
	keywords = {automation, Ethnography, Primary care, Sociotechnical},
	doi = {10.1007/978-3-319-78105-1_60},
	author = {Matt WIllis and Eric T. Meyer}
}
@article {2017,
	title = {Artificial intelligence and the modern productivity paradox: a clash of expectations and statistics},
	number = {24001},
	year = {2017},
	month = {11/2017},
	keywords = {economics of automation},
	url = {http://www.nber.org/papers/w24001},
	author = {Erik Brynjolfsson and Daniel Rock and Chad Syverson}
}
@article {2017,
	title = {Automation, computerisation and future employment in Singapore},
	journal = {Journal of Southeast Asian Economies},
	volume = {34},
	year = {2017},
	keywords = {economics of automation},
	url = {https://mpra.ub.uni-muenchen.de/79961/},
	author = {King Fuei Lee}
}
@mastersthesis {2017,
	title = {Evaluating the effects of industrial robots on the European labour market},
	volume = {Bergen, Fall, 2017},
	year = {2017},
	keywords = {economics of automation},
	url = {https://pdfs.semanticscholar.org/4e19/3a0a02315803d799520b094cce36a1888a94.pdf},
	author = {Elena Natalie and Cagnol Hveem}
}
@article {2017,
	title = {Will Life Be Worth Living in a World Without Work? Technological Unemployment and the Meaning of Life},
	journal = {Science and Engineering Ethics},
	volume = {23},
	year = {2017},
	publisher = {Springer},
	chapter = {41-64},
	abstract = {Suppose we are about to enter an era of increasing technological unemployment. What implications does this have for society? Two distinct ethical/social issues would seem to arise. The first is one of distributive justice: how will the (presumed) efficiency gains from automated labour be distributed through society? The second is one of personal fulfillment and meaning: if people no longer have to work, what will they do with their lives? In this article, I set aside the first issue and focus on the second. In doing so, I make three arguments. First I argue that there are good reasons to embrace non-work and that these reasons become more compelling in an era of technological unemployment. Second, I argue that the technological advances that make widespread technological unemployment possible could still threaten or undermine human flourishing and meaning, especially if (as is to be expected) they do not remain confined to the economic sphere. And third, I argue that this threat could be contained if we adopt an integrative approach to our relationship with technology. In advancing these arguments, I draw on three distinct literatures: (1) the literature on technological unemployment and workplace automation; (2) the antiwork critique - which I argue gives reasons to embrace technological unemployment; and (3) the philosophical debate about the conditions for meaning in life - which I argue gives reasons for concern.},
	keywords = {Antiwork, automation, Egalitarianism, Freedom, Meaning of life, Technological unemployment, Transhumanism},
	doi = {10.1007s/11948-016-9770-5},
	author = {John Danaher}
}
@article {2014,
	title = {A transdisciplinary perspective on hedonomic sustainability design},
	year = {2014},
	keywords = {environmental efficacy, environmental sustainability, hedonomics, sustainable design, transdisciplinary research},
	doi = {10.1177\%2F1064804613516762},
	url = {https://journals.sagepub.com/doi/abs/10.1177/1064804613516762?journalCode=erga},
	author = {Stephen M. Fiore and Elizabeth Philips and Brittany C. Sellers}
}
