@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 {2019,
	title = {Economic, Social Impacts and Operation of Smart Factories in Industry 4.0 Focusing on Simulation and Artificial Intelligence of Collaborating Robots},
	journal = {Social Sciences},
	volume = {8},
	year = {2019},
	month = {Jan-05-2019},
	pages = {143},
	doi = {10.3390/socsci8050143},
	author = {Benotsmane, Rabab and Kov{\'a}cs, Gy{\"o}rgy and Dud{\'a}s, L{\'a}szl{\'o}}
}
@book {2019,
	title = {Educating those most impacted by artificial intelligence},
	volume = {11626},
	year = {2019},
	pages = {344 - 349},
	publisher = {Springer International Publishing},
	organization = {Springer International Publishing},
	address = {Cham},
	isbn = {978-3-030-23206-1},
	issn = {0302-9743},
	doi = {10.1007/978-3-030-23207-8_63},
	author = {Gemmell, Laura and Wenham, Lucy and Hauert, Sabine},
	editor = {Isotani, Seiji and Mill{\'a}n, Eva and Ogan, Amy and Hastings, Peter and McLaren, Bruce and Luckin, Rose}
}
@book {2019,
	title = {The emergence of complexity},
	year = {2019},
	publisher = {Springer International Publishing},
	organization = {Springer International Publishing},
	address = {Cham},
	isbn = {978-3-030-31837-6},
	issn = {2366-1658},
	doi = {10.1007/978-3-030-31839-0},
	author = {Hager, Paul and Beckett, David}
}
@article {2019,
	title = {Emotional processes in human-robot interaction during brief cognitive testing},
	journal = {Computers in Human Behavior},
	volume = {90},
	year = {2019},
	month = {Jan-01-2019},
	pages = {331 - 342},
	issn = {07475632},
	doi = {10.1016/j.chb.2018.08.013},
	author = {Desideri, Lorenzo and Ottaviani, Cristina and Malavasi, Massimiliano and di Marzio, Roberto and Bonifacci, Paola}
}
@article {2019,
	title = { Employment Transformation through Artificial Intelligence },
	year = {2019},
	note = {We all are moving at pace towards innovative technologies and adopting these technologies, human are being entered into the digital world, where they are going to be facilitated by transformed traditional systems into modern systems. In next few years, most of systems will be smart and able to do anything as human can do. This transformation will be a reason to bring the human into very comfort zone where they will take the advantages of these modern facilities. This transformation will help to government in developing the new aspects of developments in their country .As today, the traditional systems are being smart and intelligence along with that cities are also being smart day by day. This transformation will be a cause of bringing a big revolution for the human{\textquoteright}s life across the world. On another side, this transformation will have positive and negative impact on employability in different sectors. India is essentially entering into a new industrial revolution and it is going to wipe out millions of jobs in India. Innovative transformation through industry revolution will restructure the infrastructure and working environment in services as well as in manufacturing industries. Productivity and revenue of industries will be up after replacing existing methods with innovative methods. Basically, these innovative methods will replace the human with intellectual artificial (AI) machines which will transform the working environment of industries partially or entirely. AI Machines will be responsible for transformation in employability across the world. Machine will take control over the human work means in future most of the work will be executed by the Artificial..},
	edition = {International Journal of Applied Engineering Research},
	url = {https://scholar.google.co.in/citations?user=5wxReHAAAAAJ\&hl=en$\#$d=gs_md_cita-d\&u=\%2Fcitations\%3Fview_op\%3Dview_citation\%26hl\%3Den\%26user\%3D5wxReHAAAAAJ\%26citation_for_view\%3D5wxReHAAAAAJ\%3Ad1gkVwhDpl0C\%26tzom\%3D300},
	author = {Dheeraj Singh, and Geetali Tilak}
}
@article {2019,
	title = {Examples of artificial intelligence in education},
	year = {2019},
	keywords = {process automation},
	url = {https://emerj.com/ai-sector-overviews/examples-of-artificial-intelligence-in-education/},
	author = {Daniel Faggella}
}
@article {2019,
	title = {Exploring and developing policies to future proof Washington{\textquoteright}s workers and businesses},
	year = {2019},
	institution = {Workforce Training and Education Coordinating Board},
	url = {http://www.wtb.wa.gov/Documents/FutureofWork2018Report.pdf},
	author = {Joe Wilcox and Lew McMurran}
}
@article {2019,
	title = {An Extensive Review on Recent Emerging Applications of Artificial Intelligence},
	journal = {Asia-pacific Journal of Convergent Research Interchange},
	volume = {5},
	year = {2019},
	month = {Jun-06-2021},
	pages = {79 - 88},
	issn = {25089080},
	doi = {10.21742/apjcri10.21742/apjcri.2019.0610.21742/apjcri.2019.06.09},
	url = {http://www.apjcri.org/papers/v5n2/9.pdf},
	author = {Harini, B}
}
@article {2018,
	title = {Economic policy for Artificial Intelligence},
	year = {2018},
	institution = {National Bureau of Economic Research},
	address = {Cambridge, MA},
	doi = {10.3386/w24690},
	author = {Agrawal, Ajay and Gans, Joshua and Goldfarb, Avi}
}
@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}
}
@article {2018,
	title = {The economics of artificial intelligence: Implications for the future of work},
	year = {2018},
	isbn = {978-92-2-031137-0},
	issn = {978-92-2-031138-7},
	url = {https://www.ilo.org/wcmsp5/groups/public/---dgreports/---cabinet/documents/publication/wcms_647306.pdf},
	author = {Ekkehard Ernst and Rossana Merola and Daniel Samaan}
}
@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 = {The effects of automation},
	year = {2018},
	url = {https://www.dropbox.com/sh/8sxki5mwikjxlte/AAB6zvW5F0s2FIJ6jUmEW7P-a/Popular\%20press\%20about\%20impacts?dl=0\&preview=effects+of+automation.pdf\&subfolder_nav_tracking=1},
	author = {Jim L. Smith}
}
@book {2018,
	title = {eHealth - Making Health Care SmarterUse of Artificial Intelligence in Healthcare Delivery},
	year = {2018},
	publisher = {InTech},
	organization = {InTech},
	isbn = {978-1-78923-522-7},
	doi = {http://dx.doi.org/10.5772/intechopen.74714},
	author = {Reddy, Sandeep},
	editor = {Heston, Thomas F.}
}
@article {2018,
	title = {Embracing the new world of work},
	year = {2018},
	url = {https://sfmagazine.com/post-entry/june-2018-embracing-the-new-world-of-work/},
	author = {John M. Lewin}
}
@article {2018,
	title = {Embracing the sobering reality of technological influences on jobs, employment and human resource development},
	journal = {European Journal of Training and Development},
	volume = {42},
	year = {2018},
	month = {Mar-09-2018},
	pages = {400 - 416},
	issn = {2046-9012},
	doi = {10.1108/EJTD-03-2018-0030},
	author = {Chuang, Szufang and Graham, Carroll Marion}
}
@article {2018,
	title = {Ethics of using Artificial Intelligence to augment drafting legal documents},
	journal = { Texas A\&M Journal of Property Law},
	volume = {4},
	year = {2018},
	edition = {3},
	url = {https://scholarship.law.tamu.edu/cgi/viewcontent.cgi?article=1080\&context=journal-of-property-law},
	author = {David Hricik Hri and Asya-Lorrene S. Morgan and Kyle H. Williams}
}
@article {2018,
	title = {The evolving role of ICT in the economy},
	year = {2018},
	month = {06/2018},
	keywords = {consulting reports},
	url = {http://www.lse.ac.uk/business-and-consultancy/consulting/consulting-reports/the-evolving-role-of-ict-in-the-economy},
	author = {Mirko Draca and Ralf Martin and Rosa Sanchis-Guarner}
}
@mastersthesis {2018,
	title = {Examination of cognitive load in the human-machine teaming context},
	year = {2018},
	month = {06/2018},
	abstract = {The Department of Defense (DoD) is increasingly hoping to employ unmanned systems and artificial intelligence to achieve a strategic advantage over adversaries. While some tasks may be suitable for machine substitution, many parts of the DoD{\textquoteright}s mission continue to require boots on the ground and humans in the loop working in interdependent human-machine teams. The commercial unmanned systems marketplace and active UxS and autonomous systems offer military research and acquisitions professionals promising technical solutions, but may integrate poorly in a human-machine team application. The authors developed a framework for analyzing task-to-technology matches and team design for military human-machine teams. The framework is grounded in the cognitive theories of situational awareness and decision making, team dynamics, and functional allocation literature. Additionally, the research recommends developing a shared DoD-wide understanding of autonomous systems terms and taxonomy, and educating operational leaders, acquisitions staff, and executives about realistic expectations and employment of autonomous systems in human-machine environments.},
	url = {https://hdl.handle.net/10945/59638},
	author = {Clarke, Alan J. and Knudson, Daniel F. III}
}
@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 = {Experimental evidence on productivity complementarities},
	number = {18-065},
	year = {2018},
	publisher = {Harvard Business School Working Paper},
	keywords = {Human Capital, Performance Productivity, Technological Innovation, Technology Adoption},
	url = {https://www.hbs.edu/faculty/Pages/item.aspx?num=53855},
	author = {Prithwiraj Choudhury}
}
@article {2018,
	title = {Explaining the decline in the u. S. Employment-to-population ratio: A review of the evidence},
	year = {2018},
	institution = {National Bureau of Economic Research},
	address = {Cambridge, MA},
	doi = {10.3386/w24333},
	author = {Abraham, Katharine and Kearney, Melissa}
}
@article {2018,
	title = {Explanation to Avert Surprise},
	journal = {IUI Workshops},
	year = {2018},
	url = {https://www.semanticscholar.org/paper/Explanation-to-Avert-Surprise-Gervasio-Myers/8e3b3d9e9075095a87c96fa9690d2ccbf127234e},
	author = {Melinda Gervasio and Karen Myers and Eric Yeh and Boone Adkins}
}
@article {2018,
	title = {Exploiting ability for human adaptation to facilitate improved human-robot interaction and acceptance},
	journal = {The Information Society},
	volume = {34},
	year = {2018},
	month = {Mar-05-2020},
	pages = {153 - 165},
	issn = {0197-2243},
	doi = {10.1080/01972243.2018.1444255},
	author = {Caleb-Solly, Praminda and Dogramadzi, Sanja and Huijnen, Claire A.G.J. and Heuvel, Herjan van den}
}
@article {2017,
	title = {Elon Musk Lays Out Worst-Case Scenario for AI Threat},
	year = {2017},
	url = {https://www.wsj.com/articles/elon-musk-warns-nations-governors-of-looming-ai-threat-calls-for-regulations-1500154345},
	author = {Tim Higgins}
}
@mastersthesis {2017,
	title = {An empirical analysis of the impacts of robotization on employment in the Norwegian manufacturing industry},
	year = {2017},
	type = {master thesis},
	abstract = {Rapid advances in robotics, artificial intelligence, and digital technologies have introduced renewed concern that labor will become redundant. The aim of this thesis is to assess whether there exists a relationship between robotization and employment in the time periods 1996-2005 and 2008-2015 in Norwegian manufacturing industries. We exploit data on operational robots from the International Federation of Robotics and individual level data from the Norwegian Labour Force Survey, to assess a potential relationship between increased robotization and the probability of being employed within the manufacturing industries. Utilizing linear probability models, we find no negative relationship between increased robotization and the probability of being employed in Norwegian manufacturing industries. Further, we find indications of a relationship between increased robotization and skill-biases. However, the relationships are of no economic significance. Our findings are consistent with previous research on the impacts of robotization on employment outcomes. Further, we find that robotization is distinct and weakly correlated to import density and capital density.},
	url = {https://www.semanticscholar.org/paper/Will-robots-replace-us-\%3A-an-Empirical-analysis-of-Gr\%C3\%B8ndahl-Eriksen/e4e22bf2498e42d6308d81cc7483b5a0b8ba48e7},
	author = {Fredrik Gr{\o}ndahl and Gina Hegland Eriksen}
}
@article {2017,
	title = {Employment, inequality and ethics in the digital age},
	journal = {The IPPR Commission on Economic Justice},
	year = {2017},
	month = {12/2017},
	url = {https://www.ippr.org/publications/managing-automation},
	author = {Mathew Lawrence and Carys Roberts and Loren King}
}
@article {2017,
	title = {Empowerment As Replacement for the Three Laws of Robotics},
	journal = {Frontiers in Robotics and AI},
	volume = {4},
	year = {2017},
	month = {May-06-2019},
	doi = {10.3389/frobt.2017.00025},
	author = {Salge, Christoph and Polani, Daniel}
}
@article {2017,
	title = {Evaluating Assessments in the Age of Big Data and AI},
	year = {2017},
	url = {https://www.ibm.com/downloads/cas/D5GQD70R},
	author = {Nigel Guenole and Sheri Feinzig}
}
@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}
}
@conference {RN30645,
	title = {Examining crowd work and gig work through the historical lens of piecework},
	booktitle = {Proceedings of the CHI Conference on Human Factors in Computing Systems},
	year = {2017},
	pages = {4599-4616},
	publisher = {ACM},
	organization = {ACM},
	type = {Conference Proceedings},
	isbn = {1450346553},
	author = {Alkhatib, Ali and Michael S. Bernstein and Levi, Margaret}
}
@article {2017,
	title = {An experimental comparison of Chatbot and Human task partners},
	journal = {Computers in Human Behavior},
	volume = {75},
	year = {2017},
	month = {Jan-10-2017},
	pages = {461 - 468},
	issn = {07475632},
	doi = {10.1016/j.chb.2017.05.045},
	author = {Fryer, Luke K. and Ainley, Mary and Thompson, Andrew and Gibson, Aaron and Sherlock, Zelinda}
}
@article {2017,
	title = {Exploring the tension between transparency and datification effects of open government IS through the lens of Complex Adaptive Systems},
	journal = {The Journal of Strategic Information Systems},
	volume = {26},
	year = {2017},
	month = {Jan-09-2017},
	pages = {210 - 232},
	issn = {09638687},
	doi = {10.1016/j.jsis.2017.07.001},
	author = {Marjanovic, Olivera and Cecez-Kecmanovic, Dubravka}
}
@mastersthesis {2016,
	title = {Exploring design principles for human-machine symbiosis: Insights from constructing an air transportation logistics artifact},
	year = {2016},
	keywords = {air transportation logistics, design science research, heuristic theorizing, huma n - machine symbiosis},
	url = {https://www.semanticscholar.org/paper/Artificial-Intelligence-and-its-Role-in-Near-Future-Shabbir-Anwer/b93d9995f9ce3b15f4c4855ae62f0bf6f9bc041f},
	author = {Daniel A. D{\"o}ppner and Detlef Schoder and Robert Wayne Gregory and Honorata Siejka}
}
@article {2015,
	title = {An executive{\textquoteright}s guide to machine learning},
	journal = {McKinsey Quarterly},
	year = {2015},
	type = {Technology, Media \& Telecommunications},
	url = {https://www.mckinsey.com/industries/technology-media-and-telecommunications/our-insights/an-executives-guide-to-machine-learning},
	author = {Dorian Pyle and Cristina San Jose}
}
@article {2013,
	title = {Ethical algorithms},
	year = {2013},
	url = {https://www.sharrockandanderson.co.uk/wp-content/uploads/2017/04/Ethical-Algorithms.pdf},
	author = {R.J. Anderson and W.W. Sharrock}
}
@article {1989,
	title = {Expert systems for configuration at digital: xcon and beyond},
	volume = {32},
	year = {1989},
	chapter = {298-318},
	doi = {10.1145/62065.62067},
	author = {Virginia E. Barker and Dennis E. O{\textquoteright}Connor}
}
