@article {Noonpakdee2020,
	title = {The Adoption of Artificial Intelligence for Financial Investment Service},
	journal = {2020 22nd International Conference on Advanced Communication Technology (ICACT)},
	year = {2020},
	pages = {396{\textendash}400},
	publisher = {Global IT Research Institute - GIRI},
	keywords = {AI, artificial intelligence, data, financial, fintech, investment service, Technology Adoption, to investment companies, to offer customers accessibility},
	isbn = {9791188428045},
	author = {Noonpakdee, Wasinee}
}
@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 {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 {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}
}
@booklet {Grimshaw2020,
	title = {International organisations and the future of work: How new technologies and inequality shaped the narratives in 2019},
	howpublished = {Journal of Industrial Relations},
	volume = {62},
	number = {3},
	year = {2020},
	pages = {477{\textendash}507},
	abstract = {In a critical review of seven prominent flagship reports from five international organisations {\textendash} the International Labour Organization (ILO), Organisation for Economic Co-operation and Development (OECD), United Nations Industrial Development Organization (UNIDO), United Nations Development Programme (UNDP) and World Bank {\textendash} this article explores how the policy narratives set out during 2019 and early 2020 have characterised the major future of work challenges associated with new technologies and inequality. It identifies some similarities in viewpoints, including about the unevenness of job changes caused by new technologies and about the declining labour income share, a key measure of inequality. However, there are major points of differentiation. The ILO, OECD and UNDP express serious concerns about the interaction between new technologies and growing inequalities, on the one hand, and a rise in precarious work, concentration of corporate power and erosion of labour bargaining power on the other. Also, UNIDO emphasises the inequalities in technological capacities between developed and developing countries, which make it difficult for markets to distribute the gains from growth evenly. While the World Bank makes some concessions, it remains less open to real-world heterodox evidence about how labour markets function in society. The World Bank aside, there is a growing consensus that labour institutions around the world need to be reinvigorated in order to respond to the challenges facing the future of work.},
	keywords = {future of work, Inequality, International Labour Organization, international organisations, labour income share, new technologies},
	issn = {14729296},
	doi = {10.1177/0022185620913129},
	author = {Grimshaw, Damian}
}
@article {Capatina2020,
	title = {Matching the future capabilities of an artificial intelligence-based software for social media marketing with potential users{\textquoteright} expectations},
	journal = {Technological Forecasting and Social Change},
	volume = {151},
	number = {June 2019},
	year = {2020},
	pages = {119794},
	publisher = {Elsevier},
	abstract = {The increasing use of Artificial Intelligence (AI) in Social Media Marketing (SMM) triggered the need for this research to identify and further analyze such expectations of potential users of an AI-based software for Social Media Marketing; a software that will be developed in the next two years, based on its future capabilities. In this research, we seek to discover how the potential users of this AI-based software (owners and employees from digital agencies based in France, Italy and Romania, as well as freelancers from these countries, with expertise in SMM) perceive the capabilities that we offer, as a way to differentiate our technological solution from other available in the market. We propose a causal model to find out which expected capabilities of the future AI-based software can explain potential users{\textquoteright} intention to test and use this innovative technological solution for SMM, based on integer valued regression models. With this purpose, R software is used to analyze the data provided by the respondents. We identify different causal configurations of upcoming capabilities of the AI-based software, classified in three categories (audience, image and sentiment analysis), and will trigger potential users{\textquoteright} intention to test and use the software, based on an fsQCA approach.},
	keywords = {artificial intelligence, Audience analysis, Image analysis, machine learning, Sentiment analysis, Social media marketing},
	issn = {00401625},
	doi = {10.1016/j.techfore.2019.119794},
	url = {https://doi.org/10.1016/j.techfore.2019.119794},
	author = {Capatina, Alexandru and Kachour, Maher and Lichy, Jessica and Micu, Adrian and Micu, Angela Eliza and Codignola, Federica}
}
@article {Spencer2020,
	title = {No automation please, we{\textquoteright}re British: Technology and the prospects for work},
	journal = {Cambridge Journal of Regions, Economy and Society},
	volume = {13},
	number = {1},
	year = {2020},
	pages = {117{\textendash}134},
	abstract = {This article assesses the impact and probably limits of automation. It looks, in particular, at the case of the UK economy. The prospects for automation are seen as necessarily uncertain and potentially regressive in their effects, with technology likely to sustain a large number of low-quality jobs. The deep-seated problems of the UK economy-low-investment, low-productivity and low-real wages-are seen as key impediments to forms of automation that work for all in society. It is argued that, without wider institutional reform, the UK will be unable to reap the full potential of automation.},
	keywords = {automation, investment, robots, technology, work},
	issn = {17521386},
	doi = {10.1093/cjres/rsaa003},
	author = {Spencer, David and Slater, Gary}
}
@booklet {Willcocks2020,
	title = {Robo-Apocalypse cancelled? Reframing the automation and future of work debate},
	howpublished = {Journal of Information Technology},
	number = {2016},
	year = {2020},
	abstract = {Robotics and the automation of knowledge work, often referred to as AI (artificial intelligence), are presented in the media as likely to have massive impacts, for better or worse, on jobs skills, organizations and society. The article deconstructs the dominant hype-and-fear narrative. Claims on net job loss emerge as exaggerated, but there will be considerable skills disruption and change in the major global economies over the next 12 years. The term AI has been hijacked, in order to suggest much more going on technologically than can be the case. The article reviews critically the research evidence so far, including the author{\textquoteright}s own, pointing to eight major qualifiers to the dominant discourse of major net job loss from a seamless, overwhelming AI wave sweeping fast through the major economies. The article questions many assumptions: that automation creates few jobs short or long term; that whole jobs can be automated; that the technology is perfectible; that organizations can seamlessly and quickly deploy AI; that humans are machines that can be replicated; and that it is politically, socially and economically feasible to apply these technologies. A major omission in all studies is factoring in dramatic increases in the amount of work to be done. Adding in ageing populations, productivity gaps and skills shortages predicted across many G20 countries, the danger might be too little, rather than too much labour. The article concludes that, if there is going to be a Robo-Apocalypse, this will be from a collective failure to adjust to skills change over the next 12 years. But the debate needs to be widened to the impact of eight other technologies that AI insufficiently represents in the popular imagination and that, in combination, could cause a techno-apocalypse.},
	keywords = {AI, automation, cognitive automation, future of work, Information Technology, Jobs, robotic process automation, skills},
	isbn = {0268396220925},
	issn = {14664437},
	doi = {10.1177/0268396220925830},
	author = {Willcocks, Leslie}
}
@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 {2019,
	title = {Digitalization and the future of work: Macroeconomic consequences},
	year = {2019},
	publisher = {ZEW - Leibniz-Zentrum f{\"u}r Europ{\"a}ische Wirtschaftsforschung},
	abstract = {Computing power continues to grow at an enormous rate. Simultaneously, more and better data is increasingly available and Machine Learning methods have seen significant breakthroughs in the recent past. All this pushes further the boundary of what machines can do. Nowadays increasingly complex tasks are automatable at a precision which seemed infeasible only few years ago. The examples range from voice and image recognition, playing Go, to self-driving vehicles. Machines are able to perform more and more manual and also cognitive tasks that previously only humans could do. As a result of these developments, some argue that large shares of jobs are "at risk of automation", spurring public fears of massive job-losses and technological unemployment. This chapter discusses how new digital technologies might affect the labor market in the near future. First, the chapter discusses estimates of automation potentials, showing that many estimates are severely upward biased because they ignore that workers in seemingly automatable occupations already take over hard-to-automate tasks. Secondly, it highlights that these numbers only refer to what theoretically could be automated and that this must not be equated with job-losses or employment effects - a mistake that is done often in the public debate. Thirdly, the chapter develops scenarios on how digitalization is likely to affect the German labor market in the next five years and derives implications for policy makers on how to shape the future of work. Germany is an interesting case to study, as it is a developed country at the technological frontier. In particular, the main challenge will not be the number, but the structure of jobs and the corresponding need for supply side adjustments to meet the shift in demand both within and between occupations and sectors.},
	keywords = {automation, Digitalization, Inequality, unemployment},
	url = {http://hdl.handle.net/10419/200063},
	author = {Melanie Arntz and Terry Gregory and Ulrich Zierahn}
}
@article {2019,
	title = {In the age of the smart artificial intelligence: AI{\textquoteright}s dual capacities for automating and informating work},
	journal = {Business Information Review},
	year = {2019},
	month = {Dec-10-2020},
	pages = {026638211988399},
	publisher = {Sage},
	abstract = {Recent developments in artificial intelligence (AI) have generated tidal waves, which are shaking the foundation of organizations and businesses. Even though AI is considered an unprecedented disruptive force for work automation, much can be learned from current research on the computerization of work. Drawing on the seminal work of Shoshana Zuboff, this article provides a balanced perspective on the dual affordances of AI systems for automating and informating work. Whereas AI offers unique capacities for automating cognitive work that once required high-skill workers, it may be a source of unintended consequences such as cognitive complacency or de-skilling workers. To overcome such effects, the informating capacities of AI systems can be invoked to augment work, generate a more comprehensive perspective on organization, and finally equip workers with new sets of intellectual skills.

},
	keywords = {Algorithmic management, artificial intelligence, augmentation, automating, informating, intelligent machine},
	issn = {0266-3821},
	doi = {10.1177/0266382119883999},
	url = {https://journals.sagepub.com/doi/abs/10.1177/0266382119883999},
	attachments = {https://waim.network/sites/crowston.syr.edu/files/In\%20the\%20Age\%20of\%20the\%20Smart\%20Artificial\%20Intelligence\%20AI\%E2\%80\%99s\%20Dual\%20Capacities\%20for\%20Automating\%20and\%20Informating.pdf},
	author = {Jarrahi, Mohammad Hossein}
}
@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, taxes and transfers with international rivalry},
	year = {2018},
	publisher = {Australian National University},
	keywords = {automation, global modelling, income distribution, taxes, transfers},
	issn = {2206-0332},
	url = {https://cama.crawford.anu.edu.au/sites/default/files/publication/cama_crawford_anu_edu_au/2018-09/44_2018_tyers_zhou.pdf},
	author = {Rod Tyers and Yixiao Zhou}
}
@article {2018,
	title = {{\textquoteleft}The beginning of a wave{\textquoteright}: A.I. Tiptoes into the workplace},
	journal = {The NewYork Times},
	year = {2018},
	keywords = {AI, impacts},
	url = {https://www.nytimes.com/2018/08/05/technology/workplace-ai.html},
	author = {Steve Lohr}
}
@article {2018,
	title = {Beyond r\&d: The role of embodied technological change in affecting employment},
	year = {2018},
	keywords = {Innovation; R\&D; Embodied Technological Change; Employment; GMM-SY},
	issn = {2284-0400},
	url = {https://ideas.repec.org/p/ssa/lemwps/2018-15.html},
	author = {Gabriele Pelleegrino and Mariacristina Piva and Marco Vivarelli}
}
@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 future of work in the light of technological change},
	volume = {UDC: 005.32:005.95/.96},
	year = {2018},
	type = {Original Scientific Paper},
	abstract = {Abstract: Technological unemployment, a phenomenon that has been relevant for decades, is now
reaching a new dimension. There is a growing number of discussions about whether technology is the
main culprit for the rising trend of unemployment rates around the world, therefore, the paper discusses the impact of technological changes on the labour market. We conducted a survey in Slovenian
companies with more than 100 employees in order to find out their view on replacing workers with
technology, as well as the reasons and consequences of new technology. We discussed the results of our
research and the views, findings and suggestions of various authors. We have found that technological
unemployment is not a simple problem, as this phenomenon is intertwined with various issues, and
that technology presents various dangers which may at first seem less visible.},
	keywords = {Impact of technology on the labour market, Labour market, Technological unemployment},
	url = {http://media3.novi.economicsandlaw.org/2017/07/Vol23/IJEAL-23-09.pdf},
	author = {Vesna Novak and Denis Dizdarevic}
}
@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}
}
@proceedings {2018,
	title = {A literature Analysis of Research on Artificial Intelligence in Management Information System (MIS)},
	year = {2018},
	abstract = {This article presents an overview of Artificial Intelligence (AI) research applied in the Management Information System field by analyzing the databases of the AIS journal basket list representing the major international journal on MIS. AN initial set of 438 published papers was identified based on our search criteria. From those, 74 were selected because of their appropriate fit with the research questions. They were organized into domains, type of research, data collection strategy and AI techniques. We found; (1) MIS Quarterly published 42\% of the papers; (2) 50\% of studies were on Information Systems applications, followed by 15\% on Knowledge Management; and (3) 7 AI techniques were presented. This paper provides an overview of applied AI in Management, highlights the most studies related topics and techniques and contributes to a research agenda on the subject.},
	keywords = {artificial intelligence, Information Systems, Literature Analysis},
	author = {Alexandre Moreira Nascimento and Maria Alexandra V. C. da Cunha and Fernando de Souza Meirelles and Eusebio Scornavacca and Vinicius Veloso de Melo}
}
@article {2018,
	title = {New education models for the future of work force},
	number = {IZA Policy Paper No. 143},
	year = {2018},
	month = {10/2018},
	publisher = {Global Labor Organization },
	keywords = {industry 4.0; robotics; sequential versus dual education systems; human resources management and policy},
	url = {http://ftp.iza.org/pp143.pdf},
	author = {Francesco Pastore}
}
@conference {Malone:2017:PPB:2998181.2998343,
	title = {Putting the Pieces Back Together Again: Contest Webs for Large-Scale Problem Solving},
	booktitle = {Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing},
	year = {2017},
	pages = {1661{\textendash}1674},
	publisher = {ACM},
	organization = {ACM},
	address = {New York, NY, USA},
	keywords = {climate change, collective intelligence, contest webs, contests, Coordination, incentives, knowledge reuse},
	isbn = {978-1-4503-4335-0},
	doi = {10.1145/2998181.2998343},
	url = {http://doi.acm.org/10.1145/2998181.2998343},
	author = {Malone, Thomas W. and Jeffrey V Nickerson and Laubacher, Robert J. and Fisher, Laur Hesse and de Boer, Patrick and Han, Yue and Towne, W. Ben}
}
