@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 {Black2020,
	title = {AI-enabled recruiting: What is it and how should a manager use it?},
	journal = {Business Horizons},
	volume = {63},
	number = {2},
	year = {2020},
	pages = {215{\textendash}226},
	publisher = {Elsevier Ltd},
	abstract = {AI-enabled recruiting systems have evolved from nice to talk about to necessary to utilize. In this article, we outline the reasons underlying this development. First, as competitive advantages have shifted from tangible to intangible assets, human capital has transitioned from supporting cast to a starring role. Second, as digitalization has redesigned both the business and social landscapes, digital recruiting of human capital has moved from the periphery to center stage. Third, recent and near-future advances in AI-enabled recruiting have improved recruiting efficiency to the point that managers ignore them or procrastinate their utilization at their own peril. In addition to explaining the forces that have pushed AI-enabled recruiting systems from nice to necessary, we outline the key strategic steps managers need to take in order to capture its main benefits.},
	keywords = {AI-enabled recruiting, artificial intelligence, Digital recruiting technology, Human resources},
	issn = {00076813},
	doi = {10.1016/j.bushor.2019.12.001},
	url = {https://doi.org/10.1016/j.bushor.2019.12.001},
	author = {Black, J Stewart and van Esch, Patrick}
}
@conference {Sushina2020,
	title = {Artificial Intelligence in the Criminal Justice System: Leading Trends and Possibilities},
	booktitle = {Proceedings of the 6th International Conference on Social, economic, and academic leadership (ICSEAL-6-2019)},
	volume = {441},
	year = {2020},
	pages = {432{\textendash}437},
	publisher = {Atlantis Press},
	organization = {Atlantis Press},
	address = {Paris, France},
	keywords = {artificial intelligence, criminal justice system, digital technologies, Leadership},
	isbn = {978-94-6252-974-8},
	doi = {10.2991/assehr.k.200526.062},
	url = {https://www.atlantis-press.com/article/125940991},
	author = {Sushina, Tatyana and Sobenin, Andrew}
}
@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 {Reid-musson2020,
	title = {Feminist economic geography and the future of work},
	journal = {EPA: Economy and Space},
	year = {2020},
	pages = {1{\textendash}12},
	keywords = {corresponding author, department of geography, emily reid-musson, feminist economic geography, memorial university of newfoundland, newfoundland and labrador a1c, social reproduction, subjectivity, technology, work},
	doi = {10.1177/0308518X20947101},
	author = {Reid-musson, Emily and Cockayne, Daniel and Frederiksen, Lia and Worth, Nancy}
}
@article {Abeliansky2020,
	title = {The Future of Work: Challenges for Job Creation Due to Global Demographic Change and Automation},
	journal = {IZA Discussion Paper Series},
	number = {12962},
	year = {2020},
	keywords = {demography, labor, unemployment},
	url = {www.iza.org},
	author = {Abeliansky, Ana and Algur, Eda and Bloom, David E and Prettner, Klaus}
}
@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}
}
@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 {Kernbach2020,
	title = {Machine learning-based clinical prediction modeling {\textendash} A practical guide for clinicians},
	journal = {Artificial Intelligence in Precision Health},
	number = {June},
	year = {2020},
	pages = {257{\textendash}278},
	publisher = {Elsevier Inc.},
	keywords = {Alzheimers disease detection, artificial intelligence, Convolutional neural networks, Deep neural networks, Ensemble machine learning methods},
	isbn = {9780128171332},
	doi = {10.1016/b978-0-12-817133-2.00011-2},
	url = {https://arxiv.org/abs/2006.15069v1 http://dx.doi.org/10.1016/B978-0-12-817133-2.00011-2},
	author = {Kernbach, Julius M. and Staartjes, Victor E.}
}
@article {Seeber2020,
	title = {Machines as teammates: A research agenda on AI in team collaboration},
	journal = {Information and Management},
	volume = {57},
	number = {2},
	year = {2020},
	pages = {103174},
	publisher = {Elsevier},
	abstract = {What if artificial intelligence (AI) machines became teammates rather than tools? This paper reports on an international initiative by 65 collaboration scientists to develop a research agenda for exploring the potential risks and benefits of machines as teammates (MaT). They generated 819 research questions. A subteam of 12 converged them to a research agenda comprising three design areas {\textendash} Machine artifact, Collaboration, and Institution {\textendash} and 17 dualities {\textendash} significant effects with the potential for benefit or harm. The MaT research agenda offers a structure and archetypal research questions to organize early thought and research in this new area of study.},
	keywords = {artificial intelligence, Design, Duality, Research agenda, Team collaboration},
	issn = {03787206},
	doi = {10.1016/j.im.2019.103174},
	url = {https://doi.org/10.1016/j.im.2019.103174},
	author = {Seeber, Isabella and Bittner, Eva and Briggs, Robert O and de Vreede, Triparna and de Vreede, Gert Jan and Elkins, Aaron and Maier, Ronald and Merz, Alexander B and Oeste-Rei{\ss}, Sarah and Randrup, Nils and Schwabe, Gerhard and S{\"o}llner, Matthias}
}
@article {Petersen2020,
	title = {The Role of Discretion in the Age of Automation},
	journal = {Computer Supported Cooperative Work: CSCW: An International Journal},
	volume = {29},
	number = {3},
	year = {2020},
	pages = {303{\textendash}333},
	abstract = {This paper examines the nature of discretion in social work in order to debunk myths dominating prevalent debates on digitisation and automation in the public sector. Social workers have traditionally used their discretion widely and with great autonomy, but discretion has increasingly come under pressure for its apparent subjectivity and randomness. In Denmark, our case in point, the government recently planned to standardise laws to limit or remove discretion where possible in order for automation of case management to gain a foothold. Recent studies have focused on discretion in the public sector, but few have examined it explicitly and as part of real cases. As a consequence, they often leave the myths about discretion unchallenged. Inspired by the literature on discretion and CSCW research on rules in action, this study reports on an empirical investigation of discretion in child protection services in Denmark. The results of our analysis provide a new understanding of discretion as a cooperative endeavour, based on consultation and skill, rather than an arbitrary or idiosyncratic choice. In this manner, our study contradicts the myth of discretion inherent in the automation agenda. Correspondingly, we ask for attention to be given to systems that integrate discretion with technology rather than seek to undermine it directly or get around it surreptitiously. In this age of automation, this is not only an important but also an urgent task for CSCW researchers to fulfil.},
	keywords = {Administrative work, automation, Casework, Decision-Making, Digital-ready legislation, Digitisation, Discretion, Rules in action, Social work},
	issn = {15737551},
	doi = {10.1007/s10606-020-09371-3},
	author = {Petersen, Anette C.M. and Christensen, Lars Rune and Hildebrandt, Thomas T.}
}
@article {Krupiy2020,
	title = {A vulnerability analysis : Theorising the impact of artificial intelligence decision-making processes on individuals , society and human diversity from a social justice perspective},
	journal = {Computer Law \& Security Review: The International Journal of Technology Law and Practice},
	volume = {38},
	year = {2020},
	pages = {105429},
	publisher = {Elsevier Ltd},
	keywords = {artificial intelligence, data science, Decision-maki},
	issn = {0267-3649},
	doi = {10.1016/j.clsr.2020.105429},
	url = {https://doi.org/10.1016/j.clsr.2020.105429},
	author = {Krupiy, Tetyana Tanya}
}
@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 {2018,
	title = {Artificial intelligence, machine learning and the evolution of healthcare A bright future or cause for concern?},
	journal = {British Journal of Radiology},
	volume = {7},
	year = {2018},
	pages = {223-225},
	type = {Editorial},
	keywords = {artificial intelligence, deep learning, machine learning},
	author = {L.D. Jones and D. Golan and S. A. Hanna and M. Ramachandran}
}
@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 {2017,
	title = {How big data is empowering AI and machine learning at scale},
	year = {2017},
	month = {05/2017},
	keywords = {data and analytics},
	url = {https://sloanreview.mit.edu/article/how-big-data-is-empowering-ai-and-machine-learning-at-scale/},
	author = {Randy Bean}
}
@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 {2013,
	title = {A Comprehensive Survey of Data Mining-based Fraud Detection Research},
	year = {2013},
	keywords = {adversarial detection, automated fraud detection, Data mining applications},
	url = {https://arxiv.org/ftp/arxiv/papers/1009/1009.6119.pdf},
	author = {Clifton Phua and Vincent Lee and Kate Smith and Ross Gayler}
}
