@article {Kuziemski2020,
	title = {AI governance in the public sector: Three tales from the frontiers of automated decision-making in democratic settings},
	journal = {Telecommunications Policy},
	volume = {44},
	number = {6},
	year = {2020},
	pages = {101976},
	publisher = {Elsevier Ltd},
	abstract = {The rush to understand new socio-economic contexts created by the wide adoption of AI is justified by its far-ranging consequences, spanning almost every walk of life. Yet, the public sector{\textquoteright}s predicament is a tragic double bind: its obligations to protect citizens from potential algorithmic harms are at odds with the temptation to increase its own efficiency - or in other words - to govern algorithms, while governing by algorithms. Whether such dual role is even possible, has been a matter of debate, the challenge stemming from algorithms{\textquoteright} intrinsic properties, that make them distinct from other digital solutions, long embraced by the governments, create externalities that rule-based programming lacks. As the pressures to deploy automated decision making systems in the public sector become prevalent, this paper aims to examine how the use of AI in the public sector in relation to existing data governance regimes and national regulatory practices can be intensifying existing power asymmetries. To this end, investigating the legal and policy instruments associated with the use of AI for strenghtening the immigration process control system in Canada; {\textquotedblleft}optimising{\textquotedblright} the employment services{\textquotedblright} in Poland, and personalising the digital service experience in Finland, the paper advocates for the need of a common framework to evaluate the potential impact of the use of AI in the public sector. In this regard, it discusses the specific effects of automated decision support systems on public services and the growing expectations for governments to play a more prevalent role in the digital society and to ensure that the potential of technology is harnessed, while negative effects are controlled and possibly avoided. This is of particular importance in light of the current COVID-19 emergency crisis where AI and the underpinning regulatory framework of data ecosystems, have become crucial policy issues as more and more innovations are based on large scale data collections from digital devices, and the real-time accessibility of information and services, contact and relationships between institutions and citizens could strengthen {\textendash} or undermine - trust in governance systems and democracy.},
	keywords = {Algorithmic accountability, artificial intelligence, Automated decision making, Public sector innovation},
	issn = {03085961},
	doi = {10.1016/j.telpol.2020.101976},
	url = {https://doi.org/10.1016/j.telpol.2020.101976},
	author = {Kuziemski, Maciej and Misuraca, Gianluca}
}
@article {Acemoglu2020,
	title = {Competing with Robots: Firm-Level Evidence from France},
	journal = {AEA Papers and Proceedings},
	volume = {110},
	year = {2020},
	pages = {383{\textendash}388},
	abstract = {We study the firm-level implications of robot adoption in France. Of 55,390 firms in our sample, 598 adopted robots between 2010 and 2015, but these firms accounted for 20 percent of manufacturing employment. Adopters experienced significant declines in labor shares, the share of production workers in employment, and increases in value added and productivity. They expand their overall employment as well. However, this expansion comes at the expense of competitors, leading to an overall negative association between adoption and employment. Robot adoption has a large impact on the labor share because adopters are larger and grow faster than their competitors.},
	keywords = {automation, competition, j23, j24, jel codes, l11, labor share, manufacturing, productivity, reallocation, robots, tasks},
	issn = {2574-0768},
	doi = {10.1257/pandp.20201003},
	author = {Acemoglu, Daron and Lelarge, Claire and Restrepo, Pascual}
}
@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}
}
@conference {Azarova2020,
	title = {Key Advantages and Risks of Implementing Artificial Intelligence in the Activities of Professional Communicators},
	booktitle = {Proceedings of the 2020 IEEE Communication Strategies in Digital Society Seminar, ComSDS 2020},
	year = {2020},
	pages = {82{\textendash}86},
	abstract = {Nowadays we observe a wide penetration of digital technologies into communication experts practice. Literature review demonstrates a great interest of both technical and humanitarian scholars to this subject. The research results, obtained by opinion survey (young adults of 19-24 years old), illustrate possible pragmatic and ethical effects of AI applications as well as their advantages and risks.},
	keywords = {AI technologies risks, artificial intelligence, digital technologies, professional communicators},
	isbn = {9781728164410},
	doi = {10.1109/ComSDS49898.2020.9101238},
	author = {Azarova, Liudmila and Kudryavtseva, Maria and Sharakhina, Larisa}
}
@article {Wagner2020,
	title = {The nature of the Artificially Intelligent Firm - An economic investigation into changes that AI brings to the firm},
	journal = {Telecommunications Policy},
	volume = {44},
	number = {6},
	year = {2020},
	pages = {101954},
	publisher = {Elsevier Ltd},
	abstract = {With the arrival of Artificial Intelligence (AI), the nature of the firm is changing and economic theory can provide guidance to businesses as well as to politics when formulating adequate strategies for this unknown terrain. By interpreting AI as a new type of agent within the firm, the theory of the firm can serve as a lingua franca to connect computer sciences and social sciences when dealing with the interdisciplinary phenomenon of AI. To achieve this, this paper adopts the perspective of the economic theory of the firm to systematically explore the changes that AI brings to the institution of the firm. In total, five interrelated propositions are discussed that are rooted in the traditional theory but trace the nature of the Artificially Intelligent Firm: AI intensifies the effects of economic rationality on the firm (1). AI introduces a new type of information asymmetry (2). AI can perforate the boundaries of the firm (3). AI can create triangular agency relationships (4) and AI has the potential to remove traditional limits of integration (5).},
	keywords = {artificial intelligence, Asymmetric information, machine learning, Principal-agent problem, Theory of the firm},
	issn = {03085961},
	doi = {10.1016/j.telpol.2020.101954},
	url = {https://doi.org/10.1016/j.telpol.2020.101954},
	author = {Wagner, Dirk Nicolas}
}
@article {Theresa2020,
	title = {Think with me, or think for me? On the future role of artificial intelligence in marketing strategy formulation},
	journal = {The TQM Journal},
	volume = {ahead-of-p},
	number = {ahead-of-print},
	year = {2020},
	month = {jan},
	abstract = {Purpose This paper explores if and how Artificial Intelligence can contribute to marketing strategy formulation.Design/methodology/approach Qualitative research based on exploratory in-depth interviews with industry experts currently working with artificial intelligence tools.Findings Key themes include: (1) Importance of AI in strategic marketing decision management; (2) Presence of AI in strategic decision management; (3) Role of AI in strategic decision management; (4) Importance of business culture for the use of AI; (5) Impact of AI on the business{\textquoteright} organizational model. A key consideration is a {\textquotedblleft}creative-possibility perspective,{\textquotedblright} highlighting the future potential to use AI not only for rational but also for creative thinking purposes.Research limitations/implications This work is focused only on strategy creation as a deliberate process. For this, AI can be used as an effective response to the external contingencies of high volumes of data and uncertain environmental conditions, as well as being an effective response to the external contingencies of limited managerial cognition. A key future consideration is a {\textquotedblleft}creative-possibility perspective.{\textquotedblright}Practical implications A practical extension of the Gartner Analytics Ascendancy Model (Maoz, 2013).Originality/value This paper aims to contribute knowledge relating to the role of AI in marketing strategy formulation and explores the potential avenues for future use of AI in the strategic marketing process. This is explored through the lens of contingency theory, and additionally, findings are expressed using the Gartner analytics ascendancy model.},
	keywords = {AI, artificial intelligence, creativity, marketing strategy, marketing synergy, paper type research paper, rationality, tqm},
	isbn = {1754-2731},
	doi = {10.1108/TQM-12-2019-0303},
	url = {https://doi.org/10.1108/TQM-12-2019-0303},
	author = {Theresa, Eriksson and Alessandro, Bigi and Michelle, Bonera and Eriksson, Theresa and Bigi, Alessandro and Bonera, Michelle and Theresa, Eriksson and Alessandro, Bigi and Michelle, Bonera}
}
@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 {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 = {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 = {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}
}
@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}
}
@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 {1994,
	title = {Design concepts of computer-aided integrated manufacturing systems: Work-psychological concepts and empirical findings},
	journal = {International Journal of Industrial Ergonomics},
	volume = {17},
	year = {1994},
	publisher = {Elsevier},
	chapter = {11-19},
	abstract = {The research project "GRIPS" is investigating the design of computer-aided integrated manufacturing systems from a work psychological perspective. The goal is to develop and empirically support adequate design concepts. The project consists of three phases. Evidence from a broad questionnaire survey indicates that most CIM implementations fail to meet expectations associated therewith. Based on the assumption that only the joint optimization of social and technical system results in humane working conditions and economic efficiency, implementations and use of CIM systems has been investigated in 60 companies in Switzerland. THe conceptual framework distinguishes technically-oriented and work-oriented design concepts on four levels; the enterprise, the organizational unit, the group and the individual. Work-oriented manufacturing systems - as opposed to technically-oriented ones - are characterized by decentralization, functional integration, work in self-regulated groups and complete and challenging tasks. The findings support the hypothesis that work-oriented design concepts are related to higher efficiency and better achievement of goals and pursued with the use of new technologies. In the third phase 12 companies have been selected for detailed case studies: The companies are comparable concerning product range and manufacturing conditions but different on the level of work-orientation.},
	keywords = {Computer-Integrated-Manufacturing CIM, Organizational design, Production design concepts, Socio-technical system approach, Work psychology, Work-orientation},
	author = {C. Kirsh and O. Strohm and E. Ulich}
}
@book {1911,
	title = {The Principles of Scientific Management},
	year = {1911},
	publisher = {Norton \& Company},
	organization = {Norton \& Company},
	address = {New York},
	keywords = {Productionmanagement},
	author = {Taylor, F. W.}
}
