@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 {Reim2020,
	title = {Implementation of Artificial Intelligence (AI): A Roadmap for Business Model Innovation},
	journal = {AI},
	volume = {1},
	number = {2},
	year = {2020},
	pages = {180{\textendash}191},
	abstract = {Technical advancements within the subject of artificial intelligence (AI) leads towards development of human-like machines, able to operate autonomously and mimic our cognitive behavior. The progress and interest among managers, academics and the public has created a hype among many industries, and many firms are investing heavily to capitalize on the technology through business model innovation. However, managers are left with little support from academia when aiming to implement AI in their firm{\textquoteright}s operations, which leads to an increased risk of project failure and unwanted results. This paper aims to provide a deeper understanding of AI and how it can be used as a catalyst for business model innovation. Due to the increasing range and variety of the available published material, a literature review has been performed to gather current knowledge within AI business model innovation. The results are presented in a roadmap to guide the implementation of AI to firm{\textquoteright}s operations. Our presented findings suggest four steps when implementing AI: (1) understand AI and organizational capabilities needed for digital transformation; (2) understand current BM, potential for BMI, and business ecosystem role; (3) develop and refine capabilities needed to implement AI; and (4) reach organizational acceptance and develop internal competencies.},
	keywords = {artificial intelligence, business model innovation, business models, implementation},
	issn = {2673-2688},
	doi = {10.3390/ai1020011},
	author = {Reim, Wiebke and {\r A}str{\"o}m, Josef and Eriksson, Oliver}
}
@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 {Arduengo2020,
	title = {The Robot Economy : Here It Comes},
	journal = {International Journal of Social Robotics},
	number = {July},
	year = {2020},
	publisher = {Springer Netherlands},
	keywords = {blockchain, Cloud robotics, Intelligent robots, IoRT, Robot economy},
	issn = {1875-4805},
	doi = {10.1007/s12369-020-00686-1},
	url = {https://doi.org/10.1007/s12369-020-00686-1},
	author = {Arduengo, Miguel and Sentis, Luis}
}
@article {Clifton2020,
	title = {When machines think for us: The consequences for work and place},
	journal = {Cambridge Journal of Regions, Economy and Society},
	volume = {13},
	number = {1},
	year = {2020},
	pages = {3{\textendash}23},
	abstract = {The relationship between technology and work, and concerns about the displacement effects of technology and the organisation of work, have a long history. The last decade has seen the proliferation of academic papers, consultancy reports and news articles about the possible effects of Artificial Intelligence (AI) on work-creating visions of both utopian and dystopian workplace futures. AI has the potential to transform the demand for labour, the nature of work and operational infrastructure by solving complex problems with high efficiency and speed. However, despite hundreds of reports and studies, AI remains an enigma, a newly emerging technology, and its rate of adoption and implications for the structure of work are still only beginning to be understood. The current anxiety about labour displacement anticipates the growth and direct use of AI. Yet, in many ways, at present AI is likely being overestimated in terms of impact. Still, an increasing body of research argues the consequences for work will be highly uneven and depend on a range of factors, including place, economic activity, business culture, education levels and gender, among others. We appraise the history and the blurry boundaries around the definitions of AI. We explore the debates around the extent of job augmentation, substitution, destruction and displacement by examining the empirical basis of claims, rather than mere projections. Explorations of corporate reactions to the prospects of AI penetration, and the role of consultancies in prodding firms to embrace the technology, represent another perspective onto our inquiry. We conclude by exploring the impacts of AI changes in the quantity and quality of labour on a range of social, geographic and governmental outcomes.},
	keywords = {artificial intelligence, automation, bias in machine learning, geography of technology, job displacement and growth},
	issn = {17521386},
	doi = {10.1093/cjres/rsaa004},
	author = {Clifton, Judith and Clifton, Judith and Glasmeier, Amy and Gray, Mia}
}
@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 = {Cognitive and technological aspects of e-learning in context of robotization},
	journal = {Cognitive Science {\textendash} New Media {\textendash} Education},
	volume = {3},
	year = {2018},
	month = {Mar-06-2020},
	pages = {65},
	abstract = {The development of e-learning education led to the emergence of two main problems of such form of education, which are the user-system interaction from the cognitive prospective, and the analysis of massive data received out of students{\textquoteright} activity.  The development of artificial intelligence concepts and robotic process automation (RPA) tools, both problems might be solved in a more efficient way. The article presents the intelligent system of feedbacks, realized as JavaScript extension to Moodle platform, which intends to strength cognitive output of the preformed learning activity, creating an illusion of the trainer{\textquoteright}s presence and, therefore, contribute to the resolution of the first problem. The resolution of the second problem is proposed using artificial intelligence worker built in Blue Prism RPA platform, which performs validation of test questions upon strict criteria of selection. Such validation process allows to select the questions which are coherent with the index of complexity and the index of differentiation capacity.},
	keywords = {artificial intelligence worker, Blue Prism automation, intelligent system of feedbacks, robotic process automation},
	issn = {2543-506X},
	doi = {10.12775/CSNME.2017.013},
	url = {http://apcz.umk.pl/czasopisma/index.php/CSNME/article/view/CSNME.2017.013},
	author = {Shvets, Anna and Shvets, Valentyna}
}
@article {2018,
	title = {The discourse approach to boundary identification and corpus construction for theory review articles},
	journal = {Journal of the Association for Information Systems},
	year = {2018},
	keywords = {article identification, boundary identification, citation search, keyword search, literature review, machine learning, research review, review article},
	url = {https://www.researchgate.net/publication/325215971_Understanding_the_Elephant_The_Discourse_Approach_to_Boundary_Identification_and_Corpus_Construction_for_Theory_Review_Articles},
	author = {Kai R. Larsen and Dirik S. Hovorka and Alan R. Dennis and Jevin D. West}
}
@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}
}
@article {2018,
	title = {Robot vs. tax inspector or how the fourth industrial revolution will change the tax system: a review of problems and solutions},
	journal = {Journal of Tax Reform},
	volume = {4},
	year = {2018},
	month = {Jan-01-2018},
	pages = {6 - 26},
	abstract = {The fourth Industiral Revolution and the accelerated development of cyber-physical technologies lead to essential changes in national tax systems and international taxation. The main areas in which taxation meets cyber-physical technologies are digitization, robotization, M2M and blockchain technologies. Each of these areas has its own opportunities and problems. Three main approaches towards possible solutions for these new problems are identified. The first is to try to apply taxation to new cyber-physical technologies and products of their application. This approach includes the OECD{\textquoteright}s Action 1 plan on Base Erosion and Profit Shifting. It also includes the spread of traditional taxes on new objects - personal data, cryptocurrencies, imputed income of robots. The second is to replace digital transactions and shortfalls in revenues by traditional objects of taxation in the form of tangible assets and people and / or increase tax pressure (including by improving tax administration with use of Big Data) and the degree of progressiveness of taxes already levied on such objects. The third approach is to set a course on building a new tax space with smart taxes based on real-time principles, smart contracts and Big Data. This implies a transition to automatic taxation using blockchain technologies, which focus on the functions of applying distributed ledgers of business transactions in real-time. At present, the general trends are such that the first and second are prevalent, which is manifested in an increase in the relative importance of property, sales and employment taxes. Concerning the third approach, any movement in this direction is still facing a number oftechnical and other problems and is thus being discussed mainly at the conceptual level},
	keywords = {blockchain, cyber-physical technologies, digitization, taxes in Big Data, taxes on cryptocurrencies, taxes on digital goods, taxes on robots},
	issn = {24128872},
	doi = {10.15826/jtr.2018.4.1.042},
	url = {https://jtr.urfu.ru/en/archive/journal/95/article/1113/},
	author = {Vishnevsky, Valentine P. and Chekina, Viktoriia D.}
}
@article {2018,
	title = {Robots and Organization Studies: Why Robots Might Not Want to Steal Your Job},
	journal = {Organization Studies},
	year = {2018},
	month = {04/2018},
	pages = {017084061876556},
	edition = {2},
	abstract = {A number of recent high-profile studies of robotics and artificial intelligence (or AI) in economics and sociology have predicted that many jobs will soon disappear due to automation, with few new ones replacing them. While techno-optimists and techno-pessimists contest whether a jobless future is a positive development or not, this paper points to the elephant in the room. Despite successive waves of computerization (including advanced machine learning), jobs have not disappeared. And probably won{\textquoteright}t in the near future. To explain why, some basic insights from organization studies can make a contribution. I propose the concept of {\textquoteright}bounded automation{\textquoteright} to demonstrate how organizational forces mould the application of technology in the employment sector. If work does not vanish in the age of AI, then poorly paid jobs will most certainly proliferate, I argue. Finally, a case is made for the scholarly community to engage with wider social justice concerns. This I term public organization studies.},
	keywords = {artificial intelligence, bounded automation, neoliberalism, public organization studies, Robotics, unemployment, work},
	issn = {0170-8406},
	doi = {10.1177/0170840618765568},
	url = {http://journals.sagepub.com/doi/10.1177/0170840618765568},
	author = {Fleming, Peter}
}
@inbook {2017,
	title = {Agents as collaborating team members},
	year = {2017},
	month = {09/2017},
	publisher = {EBSCO},
	organization = {EBSCO},
	keywords = {bots},
	url = {https://www.taylorfrancis.com/books/e/9781315593166/chapters/10.1201/9781315593166-7},
	author = {Abhijit V. Deshmukh and Sara A.McComb and Christian Wernz}
}
@conference {2017,
	title = {Robots, ai, and the question of {\textquoteright}e-persons{\textquoteright}},
	booktitle = {Journal of science communication},
	year = {2017},
	month = {07/2017},
	keywords = {bots, Public perception of science and technology, Public understanding of science and technology, Science and policy-making},
	url = {http://eprints.whiterose.ac.uk/124830/},
	author = {Michael zollosy}
}
@article {2017,
	title = {Speculations and concerns on robots status in society},
	journal = {Journal of science communication},
	year = {2017},
	keywords = {bots, Participation and science governance, Public engagement with science and technology, Science and policy-making},
	url = {https://jcom.sissa.it/sites/default/files/documents/JCOM_1604_2017_C06.pdf},
	author = {Erik Stengler and Jimena Escudero Perez}
}
@article {2016,
	title = {Hire a UR robot - pay for it by the hour},
	year = {2016},
	month = {07/2016},
	keywords = {bots},
	url = {https://blog.universal-robots.com/hire-a-ur-robot-pay-for-it-by-the-hour},
	author = {Mahew Bush}
}
@conference {2013,
	title = {Survey of metrics for human-robot interaction},
	booktitle = {IEEE International Conference},
	year = {2013},
	keywords = {bots},
	url = {https://ieeexplore.ieee.org/document/6483569},
	author = {Robin R. Murphy and Debra Schreckenghost}
}
