TY - JOUR T1 - AI governance in the public sector: Three tales from the frontiers of automated decision-making in democratic settings JF - Telecommunications Policy Y1 - 2020 A1 - Kuziemski, Maciej A1 - Misuraca, Gianluca KW - Algorithmic accountability KW - artificial intelligence KW - Automated decision making KW - Public sector innovation AB - 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'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' 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; “optimising” the employment services” 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 – or undermine - trust in governance systems and democracy. PB - Elsevier Ltd VL - 44 UR - https://doi.org/10.1016/j.telpol.2020.101976 ER - TY - JOUR T1 - Competing with Robots: Firm-Level Evidence from France JF - AEA Papers and Proceedings Y1 - 2020 A1 - Acemoglu, Daron A1 - Lelarge, Claire A1 - Restrepo, Pascual KW - automation KW - competition KW - j23 KW - j24 KW - jel codes KW - l11 KW - labor share KW - manufacturing KW - productivity KW - reallocation KW - robots KW - tasks AB - 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. VL - 110 ER - TY - JOUR T1 - Engaged to a Robot? The Role of AI in Service JF - Journal of Service Research Y1 - 2020 A1 - Huang, Ming Hui A1 - Rust, Roland T KW - artificial intelligence KW - augmentation KW - automation KW - engagement KW - feeling AI KW - human intelligence KW - mechanical AI KW - personalization KW - relationalization KW - replacement KW - robots KW - service process KW - service strategy KW - standardization KW - thinking AI AB - 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. ER - TY - CONF T1 - Key Advantages and Risks of Implementing Artificial Intelligence in the Activities of Professional Communicators T2 - Proceedings of the 2020 IEEE Communication Strategies in Digital Society Seminar, ComSDS 2020 Y1 - 2020 A1 - Azarova, Liudmila A1 - Kudryavtseva, Maria A1 - Sharakhina, Larisa KW - AI technologies risks KW - artificial intelligence KW - digital technologies KW - professional communicators AB - 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. JF - Proceedings of the 2020 IEEE Communication Strategies in Digital Society Seminar, ComSDS 2020 SN - 9781728164410 ER - TY - JOUR T1 - The nature of the Artificially Intelligent Firm - An economic investigation into changes that AI brings to the firm JF - Telecommunications Policy Y1 - 2020 A1 - Wagner, Dirk Nicolas KW - artificial intelligence KW - Asymmetric information KW - machine learning KW - Principal-agent problem KW - Theory of the firm AB - 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). PB - Elsevier Ltd VL - 44 UR - https://doi.org/10.1016/j.telpol.2020.101954 ER - TY - JOUR T1 - Think with me, or think for me? On the future role of artificial intelligence in marketing strategy formulation JF - The TQM Journal Y1 - 2020 A1 - Theresa, Eriksson A1 - Alessandro, Bigi A1 - Michelle, Bonera A1 - Eriksson, Theresa A1 - Bigi, Alessandro A1 - Bonera, Michelle A1 - Theresa, Eriksson A1 - Alessandro, Bigi A1 - Michelle, Bonera KW - AI KW - artificial intelligence KW - creativity KW - marketing strategy KW - marketing synergy KW - paper type research paper KW - rationality KW - tqm AB - 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' organizational model. A key consideration is a “creative-possibility perspective,” 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 “creative-possibility perspective.”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. VL - ahead-of-p SN - 1754-2731 UR - https://doi.org/10.1108/TQM-12-2019-0303 ER - TY - MGZN T1 - Examples of artificial intelligence in education Y1 - 2019 A1 - Daniel Faggella KW - process automation JF - emerj UR - https://emerj.com/ai-sector-overviews/examples-of-artificial-intelligence-in-education/ ER - TY - JOUR T1 - Artificial Intelligence in Medicine and Radiation Oncology JF - Cureus Y1 - 2018 A1 - Weidlich, Vincent A1 - Weidlich, Georg A. KW - artificial intelligence KW - big data KW - error analysis KW - error prevention KW - machine learning KW - process efficiency KW - process optimization KW - quality improvement KW - radiation oncology AB - 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. UR - https://www.cureus.com/articles/11443-artificial-intelligence-in-medicine-and-radiation-oncology ER - TY - Generic T1 - Artificial intelligence, jobs, inequality and productivity: Does aggregate demand matter Y1 - 2018 A1 - Thomas Gries A1 - Wim Naude KW - artificial intelligence KW - economics of automation KW - growth theory KW - innovation KW - labour demand KW - productivity KW - technology JF - Maastricht Economic and social Research institute on Innovation and Technology PB - Maastricht University UR - http://ftp.iza.org/dp12005.pdf ER - TY - Generic T1 - Experimental evidence on productivity complementarities Y1 - 2018 A1 - Prithwiraj Choudhury KW - Human Capital KW - Performance Productivity KW - Technological Innovation KW - Technology Adoption PB - Harvard Business School Working Paper UR - https://www.hbs.edu/faculty/Pages/item.aspx?num=53855 ER - TY - JOUR T1 - Robots and Organization Studies: Why Robots Might Not Want to Steal Your Job JF - Organization Studies Y1 - 2018 A1 - Fleming, Peter KW - artificial intelligence KW - bounded automation KW - neoliberalism KW - public organization studies KW - Robotics KW - unemployment KW - work AB - 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't in the near future. To explain why, some basic insights from organization studies can make a contribution. I propose the concept of 'bounded automation' 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. UR - http://journals.sagepub.com/doi/10.1177/0170840618765568 ER - TY - CONF T1 - Work that Enables Care: Understanding Tasks, Automation, and the National Health Service T2 - iConference Y1 - 2018 A1 - Matt WIllis A1 - Eric T. Meyer KW - automation KW - Ethnography KW - Primary care KW - Sociotechnical AB - 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. JF - iConference PB - Springer ER - TY - CONF T1 - Robots, ai, and the question of 'e-persons' T2 - Journal of science communication Y1 - 2017 A1 - Michael zollosy KW - bots KW - Public perception of science and technology KW - Public understanding of science and technology KW - Science and policy-making JF - Journal of science communication UR - http://eprints.whiterose.ac.uk/124830/ ER - TY - JOUR T1 - Speculations and concerns on robots status in society JF - Journal of science communication Y1 - 2017 A1 - Erik Stengler A1 - Jimena Escudero Perez KW - bots KW - Participation and science governance KW - Public engagement with science and technology KW - Science and policy-making UR - https://jcom.sissa.it/sites/default/files/documents/JCOM_1604_2017_C06.pdf ER - TY - JOUR T1 - Design concepts of computer-aided integrated manufacturing systems: Work-psychological concepts and empirical findings JF - International Journal of Industrial Ergonomics Y1 - 1994 A1 - C. Kirsh A1 - O. Strohm A1 - E. Ulich KW - Computer-Integrated-Manufacturing CIM KW - Organizational design KW - Production design concepts KW - Socio-technical system approach KW - Work psychology KW - Work-orientation AB - 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. PB - Elsevier VL - 17 ER - TY - BOOK T1 - The Principles of Scientific Management Y1 - 1911 A1 - Taylor, F. W. KW - Productionmanagement PB - Norton & Company CY - New York ER -