@article {Gentili2020,
	title = {Are machines stealing our jobs?},
	journal = {Cambridge Journal of Regions, Economy and Society},
	volume = {13},
	number = {1},
	year = {2020},
	pages = {153{\textendash}173},
	abstract = {This study aims to contribute empirical evidence to the debate about the future of work in an increasingly robotised world. We implement a data-driven approach to study the technological transition in six leading Organisation for Economic Co-operation and Development (OECD) countries. First, we perform a cross-country and cross-sector cluster analysis based on the OECD-STAN database. Second, using the International Federation of Robotics database, we bridge these results with those regarding the sectoral density of robots. We show that the process of robotisation is industry- and country-sensitive. In the future, participants in the political and academic debate may be split into optimists and pessimists regarding the future of human labour; however, the two stances may not be contradictory.},
	keywords = {cluster analysis, e24, e66, j24, jel classifications, labour dislocation, robotisation},
	issn = {1752-1378},
	doi = {10.1093/cjres/rsz025},
	author = {Gentili, Andrea and Compagnucci, Fabiano and Gallegati, Mauro and Valentini, Enzo}
}
@article {Bessen2020,
	title = {Automation: A Guide for Policymakers},
	year = {2020},
	institution = {Brookings Institute},
	abstract = {<p>\ldots evidence that automation is causing mass unemployment, perhaps things are about to change. Some people, such as Martin Ford (2015), argue that {\textquotedblleft}this time is different.{\textquotedblright} Perhaps the rate of technological change is much more rapid with new artificial intelligence technologies \ldots</p>},
	url = {https://www.brookings.edu/research/automation-a-guide-for-policymakers/},
	author = {Bessen, James and Goos, Maarten and Salomons, Anna and van den Berge, Wiljan}
}
@conference {Gerber2020,
	title = {Conceptualization of the Human-Machine Symbiosis {\textendash} A Literature Review},
	booktitle = {Proceedings of the 53rd Hawaii International Conference on System Sciences},
	volume = {3},
	year = {2020},
	pages = {289{\textendash}298},
	abstract = {The vision of a symbiotic partnership between humans and machines has existed since the 1960s. With this paper we provide the first conceptualization of the human-machine symbiosis (HMS) and make three important contributions: we present the fundamentals of HMS by focusing on objectives, requirements, and boundaries; we propose a framework for the design of HMS; and we review HMS research and, specifically, what the literature says with respect to whether HMS has already been achieved.},
	isbn = {9780998133133},
	doi = {10.24251/hicss.2020.036},
	author = {Gerber, Alina and Derckx, Patrick and D{\"o}ppner, Daniel A and Schoder, Detlef}
}
@conference {Martnez-Plumed2020,
	title = {Does AI qualify for the job? A bidirectional model mapping labour and AI intensities},
	booktitle = {AIES 2020 - Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society},
	year = {2020},
	pages = {94{\textendash}100},
	abstract = {In this paper we present a setting for examining the relation between the distribution of research intensity in AI research and the relevance for a range of work tasks (and occupations) in current and simulated scenarios. We perform a mapping between labour and AI using a set of cognitive abilities as an intermediate layer. This setting favours a two-way interpretation to analyse (1) what impact current or simulated AI research activity has or would have on labour-related tasks and occupations, and (2) what areas of AI research activity would be responsible for a desired or undesired effect on specific labour tasks and occupations. Concretely, in our analysis we map 59 generic labour-related tasks from several worker surveys and databases to 14 cognitive abilities from the cognitive science literature, and these to a comprehensive list of 328 AI benchmarks used to evaluate progress in AI techniques. We provide this model and its implementation as a tool for simulations. We also show the effectiveness of our setting with some illustrative examples.},
	keywords = {AI benchmarks, AI impact, AI intensity, Labour market, Simulation, tasks},
	isbn = {9781450371100},
	doi = {10.1145/3375627.3375831},
	author = {Mart{\textquoteright}nez-Plumed, Fernando and Tolan, Song{\textquoteright}l and Pesole, Annarosa and Hern{\textquoteright}ndez-Orallo, Jos{\'e} and Fern{\textquoteright}ndez-Mac{\textquoteright}as, Enrique and G{\textquoteright}mez, Emilia}
}
@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 {2020,
	title = {How the FDA regulates AI},
	journal = {Academic Radiology},
	volume = {27},
	year = {2020},
	month = {Jan-01-2020},
	pages = {58 - 61},
	issn = {10766332},
	doi = {10.1016/j.acra.2019.09.017},
	author = {Harvey, H. Benjamin and Gowda, Vrushab}
}
@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 {Brundage2020,
	title = {Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims},
	year = {2020},
	pages = {1{\textendash}9},
	abstract = {With the recent wave of progress in artificial intelligence (AI) has come a growing awareness of the large-scale impacts of AI systems, and recognition that existing regulations and norms in industry and academia are insufficient to ensure responsible AI development. In order for AI developers to earn trust from system users, customers, civil society, governments, and other stakeholders that they are building AI responsibly, they will need to make verifiable claims to which they can be held accountable. Those outside of a given organization also need effective means of scrutinizing such claims. This report suggests various steps that different stakeholders can take to improve the verifiability of claims made about AI systems and their associated development processes, with a focus on providing evidence about the safety, security, fairness, and privacy protection of AI systems. We analyze ten mechanisms for this purpose{\textendash}spanning institutions, software, and hardware{\textendash}and make recommendations aimed at implementing, exploring, or improving those mechanisms.},
	url = {http://arxiv.org/abs/2004.07213},
	author = {Brundage, Miles and Avin, Shahar and Wang, Jasmine and Belfield, Haydn and Krueger, Gretchen and Hadfield, Gillian and Khlaaf, Heidy and Yang, Jingying and Toner, Helen and Fong, Ruth and Maharaj, Tegan and Koh, Pang Wei and Hooker, Sara and Leung, Jade and Trask, Andrew and Bluemke, Emma and Lebensold, Jonathan and O{\textquoteright}Keefe, Cullen and Koren, Mark and Ryffel, Th{\'e}o and Rubinovitz, JB and Besiroglu, Tamay and Carugati, Federica and Clark, Jack and Eckersley, Peter and de Haas, Sarah and Johnson, Maritza and Laurie, Ben and Ingerman, Alex and Krawczuk, Igor and Askell, Amanda and Cammarota, Rosario and Lohn, Andrew and Krueger, David and Stix, Charlotte and Henderson, Peter and Graham, Logan and Prunkl, Carina and Martin, Bianca and Seger, Elizabeth and Zilberman, Noa and H{\'E}igeartaigh, Se{\'a}n {\'O} and Kroeger, Frens and Sastry, Girish and Kagan, Rebecca and Weller, Adrian and Tse, Brian and Barnes, Elizabeth and Dafoe, Allan and Scharre, Paul and Herbert-Voss, Ariel and Rasser, Martijn and Sodhani, Shagun and Flynn, Carrick and Gilbert, Thomas Krendl and Dyer, Lisa and Khan, Saif and Bengio, Yoshua and Anderljung, Markus}
}
@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 {2019,
	title = {AI{\textquoteright}s path to the present and the painful transitions along the way},
	journal = {Digital Policy, Regulation and Governance},
	volume = {21},
	year = {2019},
	month = {Jan-05-2020},
	pages = {305 - 321},
	issn = {2398-50382398-5038},
	doi = {10.1108/DPRG-09-2018-0051},
	author = {Garcia-Murillo, Martha and MacInnes, Ian}
}
@article {2019,
	title = {AI-Based Digital Assistants},
	journal = {Business \& Information Systems Engineering},
	volume = {61},
	year = {2019},
	month = {Jan-08-2019},
	pages = {535 - 544},
	issn = {2363-7005},
	doi = {10.1007/s12599-019-00600-8},
	author = {Maedche, Alexander and Legner, Christine and Benlian, Alexander and Berger, Benedikt and Gimpel, Henner and Hess, Thomas and Hinz, Oliver and Morana, Stefan and S{\"o}llner, Matthias}
}
@article {2019,
	title = {The ambiguous labor market impact of automating prediction},
	year = {2019},
	institution = {National Bureau of Economic Research},
	address = {Cambridge, MA},
	doi = {10.3386/w25619},
	author = {Agrawal, Ajay and Gans, Joshua and Goldfarb, Avi}
}
@article {2019,
	title = {Is an army of robots marching on Chinese jobs? },
	journal = {IZA {\textendash} Institute of Labor Economics},
	year = {2019},
	month = {04/2019},
	url = {https://www.iza.org/publications/dp/12281/is-an-army-of-robots-marching-on-chinese-jobs},
	author = {Osea Giuntella and Tianyi Wang}
}
@article {2019,
	title = {Artificial Intelligence and Deep Learning: The Future of Medicine and Medical Practice},
	journal = { Journal of The Association of Physicians of India ■ Vol. 67 },
	year = {2019},
	month = {05/2019},
	url = {https://www.semanticscholar.org/paper/Artificial-Intelligence-and-Deep-Learning\%3A-The-of-Sanal-Paul/795dc72decfb12389bbf7076d82fef70421b9933},
	author = {Madhusudana Girija Sanal and Kolin Paul and Senthil Kumar and Nirmal Kumar Gangul}
}
@article {2019,
	title = {Bots Coordinating Work in Open Source Software Projects},
	journal = {Computer},
	volume = {52},
	year = {2019},
	month = {Jan-09-2019},
	pages = {52 - 60},
	issn = {0018-9162},
	doi = {10.1109/MC.2018.2885970},
	author = {Hukal, Philipp and Berente, Nicholas and Germonprez, Matt and Schecter, Aaron}
}
@article {2019,
	title = {Collaboration and delegation between humans and AI: An experimental investigation of the future of work},
	journal = {SSRN Electronic Journal},
	year = {2019},
	month = {Jan-01-2019},
	doi = {10.2139/ssrn.3368813},
	author = {F{\"u}gener, Andreas and Grahl, J{\"o}rn and Gupta, Alok and Ketter, Wolfgang}
}
@article {2019,
	title = {Comparing artificial intelligence algorithms to 157 German dermatologists: the melanoma classification benchmark},
	journal = {European Journal of Cancer},
	volume = {111},
	year = {2019},
	month = {Jan-04-2019},
	pages = {30 - 37},
	issn = {09598049},
	doi = {10.1016/j.ejca.2018.12.016},
	author = {Brinker, Titus J. and Hekler, Achim and Hauschild, Axel and Berking, Carola and Schilling, Bastian and Alexander Enk and Haferkamp, Sebastian and Karoglan, Ante and von Kalle, Christof and Weichenthal, Michael and Sattler, Elke and Schadendorf, Dirk and Gaiser, Maria R. and Klode, Joachim and Jochen Sven Utikal}
}
@article {2019,
	title = {A convolutional neural network trained with dermoscopic images performed on par with 145 dermatologists in a clinical melanoma image classification task},
	journal = {European Journal of Cancer},
	volume = {111},
	year = {2019},
	month = {Jan-04-2019},
	pages = {148 - 154},
	issn = {09598049},
	doi = {10.1016/j.ejca.2019.02.005},
	author = {Brinker, Titus J. and Hekler, Achim and Alexander Enk and Klode, Joachim and Hauschild, Axel and Berking, Carola and Schilling, Bastian and Haferkamp, Sebastian and Schadendorf, Dirk and Fr{\"o}hling, Stefan and Jochen Sven Utikal and von Kalle, Christof and Ludwig-Peitsch, Wiebke and Sirokay, Judith and Heinzerling, Lucie and Albrecht, Magarete and Baratella, Katharina and Bischof, Lena and Chorti, Eleftheria and Dith, Anna and Drusio, Christina and Giese, Nina and Gratsias, Emmanouil and Griewank, Klaus and Hallasch, Sandra and Hanhart, Zdenka and Herz, Saskia and Hohaus, Katja and Jansen, Philipp and Jockenh{\"o}fer, Finja and Kanaki, Theodora and Knispel, Sarah and Leonhard, Katja and Martaki, Anna and Matei, Liliana and Matull, Johanna and Olischewski, Alexandra and Petri, Maximilian and Placke, Jan-Malte and Raub, Simon and Salva, Katrin and Schlott, Swantje and Sody, Elsa and Steingrube, Nadine and Stoffels, Ingo and Ugurel, Selma and Sondermann, Wiebke and Zaremba, Anne and Gebhardt, Christoffer and Booken, Nina and Christolouka, Maria and Buder-Bakhaya, Kristina and Bokor-Billmann, Therezia and Alexander Enk and Gholam, Patrick and H{\"a}n{\ss}le, Holger and Salzmann, Martin and Sch{\"a}fer, Sarah and Sch{\"a}kel, Knut and Schank, Timo and Bohne, Ann-Sophie and Deffaa, Sophia and Drerup, Katharina and Egberts, Friederike and Erkens, Anna-Sophie and Ewald, Benjamin and Falkvoll, Sandra and Gerdes, Sascha and Harde, Viola and Hauschild, Axel and Jost, Marion and Kosova, Katja and Messinger, Laetitia and Metzner, Malte and Morrison, Kirsten and Motamedi, Rogina and Pinczker, Anja and Rosenthal, Anne and Scheller, Natalie and Schwarz, Thomas and St{\"o}lzl, Dora and Thielking, Federieke and Tomaschewski, Elena and Wehkamp, Ulrike and Weichenthal, Michael and Wiedow, Oliver and B{\"a}r, Claudia Maria and Bender-S{\"a}belkampf, Sophia and Horbr{\"u}gger, Marc and Karoglan, Ante and Kraas, Luise and Faulhaber, J{\"o}rg and Geraud, Cyrill and Guo, Ze and Koch, Philipp and Linke, Miriam and Maurier, Nolwenn and M{\"u}ller, Verena and Thomas, Benjamin and Jochen Sven Utikal and Alamri, Ali Saeed M. and Baczako, Andrea and Berking, Carola and Betke, Matthias and Haas, Carolin and Hartmann, Daniela and Heppt, Markus V. and Kilian, Katharina and Krammer, Sebastian and Lapczynski, Natalie Lidia and Mastnik, Sebastian and Nasifoglu, Suzan and Ruini, Cristel and Sattler, Elke and Schlaak, Max and Wolff, Hans and Achatz, Birgit and Bergbreiter, Astrid and Drexler, Konstantin and Ettinger, Monika and Haferkamp, Sebastian and Halupczok, Anna and Hegemann, Marie and Dinauer, Verena and Maagk, Maria and Mickler, Marion and Philipp, Biance and Wilm, Anna and Wittmann, Constanze and Gesierich, Anja and Glutsch, Valerie and Kahlert, Katrin and Kerstan, Andreas and Schilling, Bastian and Schr{\"u}fer, Philipp}
}
@article {2019,
	title = {Deep learning outperformed 136 of 157 dermatologists in a head-to-head dermoscopic melanoma image classification task},
	journal = {European Journal of Cancer},
	volume = {113},
	year = {2019},
	month = {Jan-05-2019},
	pages = {47 - 54},
	issn = {09598049},
	doi = {10.1016/j.ejca.2019.04.001},
	author = {Brinker, Titus J. and Hekler, Achim and Alexander Enk and Klode, Joachim and Hauschild, Axel and Berking, Carola and Schilling, Bastian and Haferkamp, Sebastian and Schadendorf, Dirk and Holland-Letz, Tim and Jochen Sven Utikal and von Kalle, Christof and Ludwig-Peitsch, Wiebke and Sirokay, Judith and Heinzerling, Lucie and Albrecht, Magarete and Baratella, Katharina and Bischof, Lena and Chorti, Eleftheria and Dith, Anna and Drusio, Christina and Giese, Nina and Gratsias, Emmanouil and Griewank, Klaus and Hallasch, Sandra and Hanhart, Zdenka and Herz, Saskia and Hohaus, Katja and Jansen, Philipp and Jockenh{\"o}fer, Finja and Kanaki, Theodora and Knispel, Sarah and Leonhard, Katja and Martaki, Anna and Matei, Liliana and Matull, Johanna and Olischewski, Alexandra and Petri, Maximilian and Placke, Jan-Malte and Raub, Simon and Salva, Katrin and Schlott, Swantje and Sody, Elsa and Steingrube, Nadine and Stoffels, Ingo and Ugurel, Selma and Zaremba, Anne and Gebhardt, Christoffer and Booken, Nina and Christolouka, Maria and Buder-Bakhaya, Kristina and Bokor-Billmann, Therezia and Alexander Enk and Gholam, Patrick and H{\"a}n{\ss}le, Holger and Salzmann, Martin and Sch{\"a}fer, Sarah and Sch{\"a}kel, Knut and Schank, Timo and Bohne, Ann-Sophie and Deffaa, Sophia and Drerup, Katharina and Egberts, Friederike and Erkens, Anna-Sophie and Ewald, Benjamin and Falkvoll, Sandra and Gerdes, Sascha and Harde, Viola and Hauschild, Axel and Jost, Marion and Kosova, Katja and Messinger, Laetitia and Metzner, Malte and Morrison, Kirsten and Motamedi, Rogina and Pinczker, Anja and Rosenthal, Anne and Scheller, Natalie and Schwarz, Thomas and St{\"o}lzl, Dora and Thielking, Federieke and Tomaschewski, Elena and Wehkamp, Ulrike and Weichenthal, Michael and Wiedow, Oliver and B{\"a}r, Claudia Maria and Bender-S{\"a}belkampf, Sophia and Horbr{\"u}gger, Marc and Karoglan, Ante and Kraas, Luise and Faulhaber, J{\"o}rg and Geraud, Cyrill and Guo, Ze and Koch, Philipp and Linke, Miriam and Maurier, Nolwenn and M{\"u}ller, Verena and Thomas, Benjamin and Jochen Sven Utikal and Alamri, Ali Saeed M. and Baczako, Andrea and Berking, Carola and Betke, Matthias and Haas, Carolin and Hartmann, Daniela and Heppt, Markus V. and Kilian, Katharina and Krammer, Sebastian and Lapczynski, Natalie Lidia and Mastnik, Sebastian and Nasifoglu, Suzan and Ruini, Cristel and Sattler, Elke and Schlaak, Max and Wolff, Hans and Achatz, Birgit and Bergbreiter, Astrid and Drexler, Konstantin and Ettinger, Monika and Haferkamp, Sebastian and Halupczok, Anna and Hegemann, Marie and Dinauer, Verena and Maagk, Maria and Mickler, Marion and Philipp, Biance and Wilm, Anna and Wittmann, Constanze and Gesierich, Anja and Glutsch, Valerie and Kahlert, Katrin and Kerstan, Andreas and Schilling, Bastian and Schr{\"u}fer, Philipp}
}
@book {2019,
	title = {Designing AI futures: A symbiotic vision},
	volume = {1083},
	year = {2019},
	pages = {3 - 18},
	publisher = {Springer International Publishing},
	organization = {Springer International Publishing},
	address = {Cham},
	isbn = {978-3-030-29742-8},
	issn = {1865-0929},
	doi = {10.1007/978-3-030-29743-5_1},
	author = {Gill, Karamjit S.},
	editor = {Kravets, Alla G. and Groumpos, Peter P. and Shcherbakov, Maxim and Kultsova, Marina}
}
@article {2019,
	title = {Digital Economics},
	journal = {Journal of Economic Literature},
	volume = {57},
	year = {2019},
	month = {Jan-03-2019},
	pages = {3 - 43},
	issn = {0022-0515},
	doi = {10.1257/jel.20171452},
	author = {Goldfarb, Avi and Tucker, Catherine}
}
@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 = {Is a driverless future also jobless?},
	year = {2019},
	institution = {W.E. Upjohn Institute},
	doi = {10.17848/pb2019-17},
	author = {Groshen, Erica L.}
}
@book {2019,
	title = {Educating those most impacted by artificial intelligence},
	volume = {11626},
	year = {2019},
	pages = {344 - 349},
	publisher = {Springer International Publishing},
	organization = {Springer International Publishing},
	address = {Cham},
	isbn = {978-3-030-23206-1},
	issn = {0302-9743},
	doi = {10.1007/978-3-030-23207-8_63},
	author = {Gemmell, Laura and Wenham, Lucy and Hauert, Sabine},
	editor = {Isotani, Seiji and Mill{\'a}n, Eva and Ogan, Amy and Hastings, Peter and McLaren, Bruce and Luckin, Rose}
}
@book {2019,
	title = {How artificial intelligence and machine learning can impact market design},
	year = {2019},
	pages = {567 - 586},
	publisher = {University of Chicago Press},
	organization = {University of Chicago Press},
	isbn = {9780226613338},
	doi = {10.7208/chicago/9780226613475.003.0023},
	author = {Agrawal, Ajay and Gans, Joshua and Goldfarb, Avi}
}
@conference {2019,
	title = {IBM Talent Management Solutions The role of AI in mitigating bias to enhance diversity and inclusion},
	year = {2019},
	note = {In this paper, we examine the nature of diversity and inclusion (D\&I), explore biases as an inhibitor to more diverse and inclusive workplaces, and provide insights into the role that AI can play in mitigating biases. We then offer practical recommendations to organizations who are looking to adopt AI in their HR practices.},
	month = {03/2019},
	url = {https://www.ibm.com/downloads/cas/2DZELQ4O},
	author = {Haiyan Zhang and Sheri Feinzi and Louise Raisbec and Iain McCombe and Nigel Guenol and Jenny Montalt and Kimberley Messe}
}
@conference {2019,
	title = {Inferring work task automatability from AI expert evidence},
	booktitle = {the 2019 AAAI/ACM ConferenceProceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society  - AIES {\textquoteright}19},
	year = {2019},
	pages = {485 - 491},
	publisher = {ACM Press},
	organization = {ACM Press},
	address = {Honolulu, HI, USANew York, New York, USA},
	isbn = {9781450363242},
	doi = {10.1145/330661810.1145/3306618.3314247},
	author = {Duckworth, Paul and Graham, Logan and Osborne, Michael}
}
@conference {2019,
	title = {Machine learning in Artificial Intelligence: Towards a common understanding},
	booktitle = {Hawaii International Conference on System SciencesProceedings of the 52nd Hawaii International Conference on System Sciences},
	year = {2019},
	publisher = {Hawaii International Conference on System Sciences},
	organization = {Hawaii International Conference on System Sciences},
	doi = {10.24251/HICSS.2019.630},
	author = {K{\"u}hl, Niklas and Goutier, Marc and Hirt, Robin and Satzger, Gerhard}
}
@article {2019,
	title = {A Machine Learning Platform to Optimize the Translation of Personalized Network Models to the Clinic},
	journal = {JCO Clinical Cancer Informatics},
	year = {2019},
	month = {Jan-04-2019},
	pages = {1 - 17},
	issn = {2473-4276},
	doi = {10.1200/CCI.18.00056},
	author = {Salvucci, Manuela and Rahman, Arman and Resler, Alexa J. and Udupi, Girish M. and McNamara, Deborah A. and Kay, Elaine W. and Laurent-Puig, Pierre and Longley, Daniel B. and Johnston, Patrick G. and Lawler, Mark and Wilson, Richard and Salto-Tellez, Manuel and Van Schaeybroeck, Sandra and Rafferty, Mairin and Gallagher, William M. and Rehm, Markus and Prehn, Jochen H.M.}
}
@article {2019,
	title = {The present and future of deep learning in radiology},
	journal = {European Journal of Radiology},
	volume = {114},
	year = {2019},
	month = {Jan-05-2019},
	pages = {14 - 24},
	issn = {0720048X},
	doi = {10.1016/j.ejrad.2019.02.038},
	url = {https://doi.org/10.1016/j.ejrad.2019.02.038},
	author = {Saba, Luca and Biswas, Mainak and Kuppili, Venkatanareshbabu and Cuadrado Godia, Elisa and Suri, Harman S. and Edla, Damodar Reddy and Omerzu, Toma{\v z} and Laird, John R. and Khanna, Narendra N. and Mavrogeni, Sophie and Protogerou, Athanasios and Sfikakis, Petros P. and Viswanathan, Vijay and Kitas, George D. and Nicolaides, Andrew and Gupta, Ajay and Suri, Jasjit S.}
}
@article {2019,
	title = {Rise of the Machines: Advances in Deep Learning for Cancer Diagnosis},
	journal = {Trends in Cancer},
	volume = {5},
	year = {2019},
	month = {Jan-03-2019},
	pages = {157 - 169},
	issn = {24058033},
	doi = {10.1016/j.trecan.2019.02.002},
	author = {Levine, Adrian B. and Schlosser, Colin and Grewal, Jasleen and Coope, Robin and Jones, Steve J.M. and Yip, Stephen}
}
@article {2019,
	title = {Scaling up analogical innovation with crowds and AI},
	journal = {Proceedings of the National Academy of Sciences},
	volume = {116},
	year = {2019},
	pages = {1870-1877},
	issn = {0027-8424},
	doi = {10.1073/pnas.1807185116},
	author = {Kittur, Aniket and Yu, Lixiu and Hope, Tom and Chan, Joel and Lifshitz-Assaf, Hila and Gilon, Karni and Ng, Felicia and Kraut, Robert E. and Shahaf, Dafna}
}
@article {Frank2019,
	title = {Toward understanding the impact of artificial intelligence on labor},
	journal = {Proceedings of the National Academy of Sciences},
	volume = {116},
	year = {2019},
	month = {apr},
	pages = {6531{\textendash}6539},
	abstract = {<p>Rapid advances in artificial intelligence (AI) and automation technologies have the potential to significantly disrupt labor markets. While AI and automation can augment the productivity of some workers, they can replace the work done by others and will likely transform almost all occupations at least to some degree. Rising automation is happening in a period of growing economic inequality, raising fears of mass technological unemployment and a renewed call for policy efforts to address the consequences of technological change. In this paper we discuss the barriers that inhibit scientists from measuring the effects of AI and automation on the future of work. These barriers include the lack of high-quality data about the nature of work (e.g., the dynamic requirements of occupations), lack of empirically informed models of key microlevel processes (e.g., skill substitution and human{\textendash}machine complementarity), and insufficient understanding of how cognitive technologies interact with broader economic dynamics and institutional mechanisms (e.g., urban migration and international trade policy). Overcoming these barriers requires improvements in the longitudinal and spatial resolution of data, as well as refinements to data on workplace skills. These improvements will enable multidisciplinary research to quantitatively monitor and predict the complex evolution of work in tandem with technological progress. Finally, given the fundamental uncertainty in predicting technological change, we recommend developing a decision framework that focuses on resilience to unexpected scenarios in addition to general equilibrium behavior.</p>},
	issn = {0027-8424},
	doi = {10.1073/pnas.1900949116},
	url = {http://www.pnas.org/lookup/doi/10.1073/pnas.1900949116},
	author = {Frank, Morgan R and Autor, David and Bessen, James E and Brynjolfsson, Erik and Cebrian, Manuel and Deming, David J and Feldman, Maryann and Groh, Matthew and Lobo, Jos{\'e} and Moro, Esteban and Wang, Dashun and Youn, Hyejin and Rahwan, Iyad}
}
@conference {2019,
	title = {Why small data holds the key to the future of artificial intelligence},
	booktitle = {8th International Conference on Data Science, Technology and ApplicationsProceedings of the 8th International Conference on Data Science, Technology and Applications},
	year = {2019},
	pages = {340 - 347},
	publisher = {SCITEPRESS - Science and Technology Publications},
	organization = {SCITEPRESS - Science and Technology Publications},
	address = {Prague, Czech Republic},
	doi = {10.5220/0007956203400347},
	author = {Greco, Ciro and Polonioli, Andrea and Tagliabue, Jacopo}
}
@article {2018,
	title = {AI Could Provide Moment-by-Moment Nursing for a Hospital{\textquoteright}s Sickest Patients},
	year = {2018},
	url = {https://globaltechnologies.ca/ai-could-provide-moment-by-moment-nursing-for-a-hospitals-sickest-patients/},
	author = {Behnood Gholami and Wassim M. Haddad and James M. Bailey}
}
@conference {2018,
	title = {AI risk mitigation through democratic governance},
	booktitle = {the 2018 AAAI/ACM ConferenceProceedings of the 2018 AAAI/ACM Conference on AI, Ethics, and Society - AIES {\textquoteright}18},
	year = {2018},
	pages = {366 - 367},
	publisher = {ACM Press},
	organization = {ACM Press},
	address = {New Orleans, LA, USANew York, New York, USA},
	isbn = {9781450360128},
	doi = {10.1145/3278721.3278801},
	author = {Garvey, Colin}
}
@conference {2018,
	title = {Artificial General Intelligence},
	year = {2018},
	url = {https://ivizlab.org/wp-content/uploads/sites/2/2018/09/TurnerDiPaola_2018_ArtificialGeneralIntelligence.pdf},
	author = {Matthew Ikl{\'e} and Arthur Franz and Rafal Rzepka and Ben Goertzel}
}
@article {2018,
	title = {Artificial intelligence and sports journalism: Is it a sweeping change?},
	journal = {Technology in Society},
	year = {2018},
	issn = {0160791X},
	doi = {10.1016/j.techsoc.2018.03.001},
	author = {Yair Galily}
}
@book {2018,
	title = {Artificial Intelligence Does Not Exist: Lessons from Shared Cognition and the Opposition to the Nature/Nurture Divide},
	volume = {537},
	year = {2018},
	pages = {359 - 373},
	publisher = {Springer International Publishing},
	organization = {Springer International Publishing},
	address = {Cham},
	isbn = {978-3-319-99604-2},
	issn = {1868-4238},
	doi = {10.1007/978-3-319-99605-9_27},
	author = {Vassilis Galanos},
	editor = {Kreps, David and Ess, Charles and Leenen, Louise and Kimppa, Kai}
}
@book {2018,
	title = {Artificial Intelligence Does Not Exist: Lessons from Shared Cognition and the Opposition to the Nature/Nurture Divide},
	volume = {537},
	year = {2018},
	pages = {359 - 373},
	publisher = {Springer International Publishing},
	organization = {Springer International Publishing},
	address = {Cham},
	isbn = {978-3-319-99604-2},
	issn = {1868-4238},
	doi = {10.1007/978-3-319-99605-9_27},
	author = {Vassilis Galanos},
	editor = {Kreps, David and Ess, Charles and Leenen, Louise and Kimppa, Kai}
}
@conference {2018,
	title = {Artificial Intelligence Does Not Exist: Lessons from Shared Cognition and the Opposition to the Nature/Nurture Divide},
	booktitle = {IFIP International Conference on Human Choice and Computers},
	year = {2018},
	url = {https://doi.org/10.1007/978-3-319-99605-9_27},
	author = {Vassilis Galanos}
}
@article {2018,
	title = {Artificial Intelligence in Cardiology},
	journal = {Journal of the American College of Cardiology},
	volume = {71},
	year = {2018},
	month = {Jan-06-2018},
	pages = {2668 - 2679},
	issn = {07351097},
	doi = {10.1016/j.jacc.2018.03.521},
	author = {Johnson, Kipp W. and Torres Soto, Jessica and Glicksberg, Benjamin S. and Shameer, Khader and Miotto, Riccardo and Ali, Mohsin and Ashley, Euan and Joel T. Dudley}
}
@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 = {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 = {Artificial intelligence, machine learning and the evolution of healthcare},
	journal = {Bone \& Joint Research},
	volume = {7},
	year = {2018},
	month = {Jan-03-2018},
	pages = {223 - 225},
	doi = {10.1302/2046-3758.73.BJR-2017-0147.R1},
	author = {Jones, L. D. and D. Golan and S. A. Hanna and M. Ramachandran}
}
@article {2018,
	title = {As s essing the impact of machine intelligence on human behaviour: an interdisciplinary endeavour},
	year = {2018},
	url = {https://arxiv.org/ftp/arxiv/papers/1806/1806.03192.pdf},
	author = {Emilia G{\'o}mez and Carlos Castillo and Vicky Charisi and Ver{\'o}nica Dahl and Gustavo Deco and Blagoj Delipetrev and Nicole Dewandre and Miguel {\'A}ngel Gonz{\'a}lez-Ballester and Fabien Gouyon and Jos{\'e} Hern{\'a}ndez-Orallo and Perfecto Herrera and Anders Jonsson and Ansgar Koene and Martha Larson and Ram{\'o}n L{\'o}pez de M{\'a}ntaras and Bertin Martens and Marius Miron and Rub{\'e}n Moreno-Bote and Nuria Oliver and Antonio Puertas Gallardo and Heike Schweitzer and Nuria Sebastian and Xavier Serra and Joan Serr{\`a} and Song{\"u}l Tolan and Karina Vold}
}
@article {2018,
	title = {Automated Classification of chest X-ray images as normal or abnormal using Convolutional Neural Network},
	journal = {Asian Journal of Convergence in Technology},
	volume = {4},
	year = {2018},
	month = {04/2018},
	abstract = {Chest X-Rays are generally used for diagnosing abnormalities in the thoracic area. Radiologists need to spend significant amount of time for interpreting scans. Automatic classification of these images could greatly help radiology interpretation process by enhancing real world diagnosis of problems. Hence, radiologists can focus on detecting abnormalities from the abnormal images rather than checking for it in all the images. In this paper, we present a machine learning approach to solve this problem. Here, the algorithm uses COnvolutional Neural Networks (CNN) to learn and classify chest X-ray images as normal or abnormal based on image features.},
	keywords = {classification, machine learning, radiology},
	author = {Aayushi Gupta and Anupama C and P Indumathi and Anuj Kumar}
}
@article {2018,
	title = {Boundary spanning at the science{\textendash}policy interface: the practitioners{\textquoteright} perspectives},
	journal = {Sustainability Science},
	volume = {13},
	year = {2018},
	month = {Jan-07-2018},
	pages = {1175 - 1183},
	issn = {1862-4065},
	doi = {10.1007/s11625-018-0550-9},
	author = {Bednarek, A. T. and Wyborn, C. and Cvitanovic, C. and Meyer, R. and Colvin, R. M. and Addison, P. F. E. and Close, S. L. and Curran, K. and Farooque, M. and Goldman, E. and Hart, D. and Mannix, H. and McGreavy, B. and Parris, A. and Posner, S. and Robinson, C. and Ryan, M. and Leith, P.}
}
@book {2018,
	title = {A critical review of the politics of artificial intelligent machines, alienation and the existential risk threat to America{\textquoteright}s labour force},
	volume = {10963},
	year = {2018},
	pages = {217 - 232},
	publisher = {Springer International Publishing},
	organization = {Springer International Publishing},
	address = {Cham},
	isbn = {978-3-319-95170-6},
	issn = {0302-9743},
	doi = {10.1007/978-3-319-95171-3_18},
	author = {Wogu, Ikedinachi Ayodele and Misra, Sanjay and Assibong, Patrick and Adewumi, Adewole and Damasevicius, Robertas and Maskeliunas, Rytis},
	editor = {Gervasi, Osvaldo and Murgante, Beniamino and Misra, Sanjay and Stankova, Elena and Torre, Carmelo M. and Rocha, Ana Maria A.C. and Taniar, David and Apduhan, Bernady O. and Tarantino, Eufemia and Ryu, Yeonseung}
}
@article {2018,
	title = {Economic policy for artificial intelligence},
	number = {24690},
	year = {2018},
	month = {06/2018},
	abstract = {Recent progress in artificial intelligence (AI) {\textendash} a general purpose technology affecting many industries - has been focused on advances in machine learning, which we recast as a quality-adjusted drop in the price of prediction. How will this sharp drop in price impact society? Policy will influence the impact on two key dimensions: diffusion and consequences. First, in addition to subsidies and IP policy that will influence the diffusion of AI in ways similar to their effect on other technologies, three policy categories - privacy, trade, and liability - may be uniquely salient in their influence on the diffusion patterns of AI. Second, labor and antitrust policies will influence the consequences of AI in terms of employment, inequality, and competition.},
	keywords = {economics of automation},
	url = {https://econpapers.repec.org/paper/nbrnberwo/24690.htm},
	author = {Ajay Agrawal and Joshua Gans and Avi Goldfarb}
}
@article {2018,
	title = {Economic policy for Artificial Intelligence},
	year = {2018},
	institution = {National Bureau of Economic Research},
	address = {Cambridge, MA},
	doi = {10.3386/w24690},
	author = {Agrawal, Ajay and Gans, Joshua and Goldfarb, Avi}
}
@article {2018,
	title = {Embracing the sobering reality of technological influences on jobs, employment and human resource development},
	journal = {European Journal of Training and Development},
	volume = {42},
	year = {2018},
	month = {Mar-09-2018},
	pages = {400 - 416},
	issn = {2046-9012},
	doi = {10.1108/EJTD-03-2018-0030},
	author = {Chuang, Szufang and Graham, Carroll Marion}
}
@article {2018,
	title = {Explanation to Avert Surprise},
	journal = {IUI Workshops},
	year = {2018},
	url = {https://www.semanticscholar.org/paper/Explanation-to-Avert-Surprise-Gervasio-Myers/8e3b3d9e9075095a87c96fa9690d2ccbf127234e},
	author = {Melinda Gervasio and Karen Myers and Eric Yeh and Boone Adkins}
}
@conference {2018,
	title = {A framework for understanding chatbots and their future},
	booktitle = {the 11th International WorkshopProceedings of the 11th International Workshop on Cooperative and Human Aspects of Software Engineering  - CHASE {\textquoteright}18},
	year = {2018},
	pages = {13 - 16},
	publisher = {ACM Press},
	organization = {ACM Press},
	address = {Gothenburg, SwedenNew York, New York, USA},
	isbn = {9781450357258},
	doi = {10.1145/3195836.3195859},
	author = {Paikari, Elahe and van der Hoek, Andr{\'e}}
}
@article {2018,
	title = {How leaders face the future of work ?},
	volume = {59},
	year = {2018},
	url = {https://sloanreview.mit.edu/article/how-leaders-face-the-future-of-work/},
	author = {Lynda Gratton}
}
@article {2018,
	title = { IBM Watson Talent The Business Case for AI in HR With Insights and Tips on Getting Started },
	year = {2018},
	url = {https://www.ibm.com/downloads/cas/AGKXJX6M},
	author = {Nigel Guenole and Sheri Feinzig}
}
@article {2018,
	title = {The impact of technological progress on labour markets: policy challenges},
	journal = {Oxford Review of Economic Policy},
	volume = {34},
	year = {2018},
	month = {Feb-07-2018},
	pages = {362 - 375},
	issn = {0266-903X},
	doi = {10.1093/oxrep/gry002},
	author = {Goos, Maarten}
}
@book {2018,
	title = {Lecture Notes in Computer ScienceArtificial General IntelligenceTowards a Sociological Conception of Artificial Intelligence},
	volume = {10999},
	year = {2018},
	pages = {130 - 139},
	publisher = {Springer International Publishing},
	organization = {Springer International Publishing},
	address = {Cham},
	isbn = {978-3-319-97675-4},
	issn = {0302-9743},
	doi = {10.1007/978-3-319-97676-1},
	author = {Jakub Mlynar and Hamed S. Alavi and Himanshu Verma and Lorenzo Cantoni},
	editor = {Matthew Ikl{\'e} and Arthur Franz and Rafal Rzepka and Ben Goertzel}
}
@article {2018,
	title = { Looking though the Pygmalion Lens},
	journal = {AI \& SOCIETY},
	volume = {33},
	year = {2018},
	month = {Jan-11-2018},
	pages = {459 - 465},
	issn = {0951-5666},
	doi = {10.1007/s00146-018-0866-0},
	author = {Gill, Karamjit S.}
}
@article {2018,
	title = {Making progress with the automation of systematic reviews: principles of the International Collaboration for the Automation of Systematic Reviews (ICASR)},
	journal = {Systematic Reviews},
	year = {2018},
	month = {2018},
	publisher = {Springer},
	type = {Review},
	abstract = {Systematic reviews (SR) are vital to health care, but have become complicated and time-consuming, due to the rapid expansion of evidence to be synthesised. Fortunately, many tasks of systematic reviews have the potential to be automated or may be assisted by automation. Recent advances in natural language processing, text mining and machine learning have produced new algorithms that can accurately mimic human endeavour in systematic review activity, faster and more cheaply. Automation tools need to be able to work together, to exchange data and results. Therefore, we initiated the International Collaboration for the Automation of Systematic Reviews (ICASR), to successfully put all the parts of automation of systematic review production together. The first meeting was held in Vienna in October 2015. We established a set of principles to enable tools to be developed and integrated into toolkits.
This paper sets out the principles devised at that meeting, which cover the need for improvement in efficiency of SR tasks, automation across the spectrum of SR tasks, continuous improvement, adherence to high quality standards, flexibility of use and combining components, the need for a collaboration and varied skills, the desire for open source, shared code and evaluation, and a requirement for replicability through rigorous and open evaluation.
Automation has a great potential to improve the speed of systematic reviews. Considerable work is already being done on many of the steps involved in a review. The {\textquoteright}Vienna Principles{\textquoteright} set out in this paper aim to guide a more coordinated effort which will allow the integration of work by separate teams and build on the experience, code and evaluations done by the many teams working across the globe.},
	keywords = {automation, Collaboration, Systematic review},
	doi = {10.1186/s13643-018-0740-7},
	author = {Elaine Beller and Justin Clark and Guy Tsafnat and Clive Adams and Heinz Diehl and Hans Lund and Mourad Ouzzani and Kristina Thayer and James Thomas and Tari Turner and Jun Xia and Karen Robinson and Paul Glasziou}
}
@article {2018,
	title = {Making progress with the automation of systematic reviews: principles of the International Collaboration for the Automation of Systematic Reviews (ICASR)},
	journal = {Systematic Reviews},
	volume = {7},
	year = {2018},
	month = {Jan-12-2018},
	keywords = {science},
	doi = {10.1186/s13643-018-0740-7},
	author = {Elaine Beller and Justin Clark and Guy Tsafnat and Clive Adams and Heinz Diehl and Hans Lund and Mourad Ouzzani and Kristina Thayer and James Thomas and Tari Turner and Jun Xia and Karen Robinson and Paul Glasziou}
}
@article {2018,
	title = {The OD imperative to add inclusion to the algorithms of artificial intelligence},
	year = {2018},
	month = {01/2018},
	abstract = {This article details concerns about the potential of machine learning processes to incorporate human biases inherent in social data into artificial intelligence systems that influence consequential decisions in the courts, business and financial transactions, and employment situations. It details incidents of biased decisions and recommendations made by artificial intelligence systems that have been given the patina of objectivity because they were made by machines supposedly free of human bias. The article offers suggestions for addressing the systemic biases that are impacting the viability, credibility, and fairness of machine learning processes and artificial intelligence system.},
	url = {https://www.researchgate.net/publication/323830092_AI_x_I_AI2_The_OD_imperative_to_add_inclusion_to_the_algorithms_of_artificial_intelligence},
	author = {Frederick A. Miller and Judith H. Katz and Roger Gans}
}
@article {2018,
	title = {Platforms at work: Automated hiring platforms and other new intermediaries in the organization of work},
	year = {2018},
	url = {http://dmgreene.net/wp-content/uploads/2018/09/Ajunwa-Greene-Platforms-at-Work-Accepted-Version.pdf},
	author = {Ifeoma Ajunwa and Daniel Greene}
}
@conference {2018,
	title = {Rethinking AI strategy and policy as entangled super wicked problems},
	booktitle = {the 2018 AAAI/ACM ConferenceProceedings of the 2018 AAAI/ACM Conference on AI, Ethics, and Society - AIES {\textquoteright}18},
	year = {2018},
	pages = {122 - 122},
	publisher = {ACM Press},
	organization = {ACM Press},
	address = {New Orleans, LA, USANew York, New York, USA},
	isbn = {9781450360128},
	doi = {10.1145/3278721.3278746},
	author = {Gruetzemacher, Ross}
}
@article {2018,
	title = {Robot Assisted Surgical Ward Rounds: Virtually Always There},
	journal = {Journal of Innovation in Health Informatics},
	volume = {25},
	year = {2018},
	month = {Sep-03-2018},
	pages = {041},
	issn = {2058-4555},
	doi = {10.14236/jhi.v25i1.982},
	author = {Stefanie M. Croghan and Paul Carroll and Sarah Reade and Amy E Gillis and Paul F. Ridgway}
}
@book {2018,
	title = {The social consequences of the digital revolution},
	volume = {6},
	year = {2018},
	publisher = {Edizioni Ca{\textquoteright} Foscari},
	organization = {Edizioni Ca{\textquoteright} Foscari},
	address = {Venice},
	isbn = {978-88-6969-274-1},
	issn = {2610-9085},
	doi = {10.30687/2610-968910.30687/978-88-6969-273-410.30687/978-88-6969-273-4/008},
	url = {http://edizionicafoscari.unive.it/collane/societa-e-trasformazioni-sociali/http://edizionicafoscari.unive.it/libri/978-88-6969-274-1/http://edizionicafoscari.unive.it/libri/978-88-6969-274-1/the-social-consequences-of-the-digital-revolution/},
	author = {Basso, Pietro and Chiaretti, Giuliana and Krzywdzinski, Martin and Gerber, Christine and Evers, Maren}
}
@article {2018,
	title = {Techno-unemployment: A framework for assessing the effects of information and communication technologies on work},
	journal = {Telematics and Informatics},
	volume = {35},
	year = {2018},
	month = {Jan-10-2018},
	pages = {1863 - 1876},
	issn = {07365853},
	doi = {10.1016/j.tele.2018.05.013},
	author = {Garcia-Murillo, Martha and MacInnes, Ian and Bauer, Johannes M.}
}
@book {2018,
	title = {Understanding tasks, automation, and the national health service},
	volume = {10766},
	year = {2018},
	pages = {544 - 549},
	publisher = {Springer International Publishing},
	organization = {Springer International Publishing},
	address = {Cham},
	isbn = {978-3-319-78104-4},
	issn = {0302-9743},
	doi = {10.1007/978-3-319-78105-1_60},
	author = {Willis, Matt and Meyer, Eric T.},
	editor = {Chowdhury, Gobinda and McLeod, Julie and Gillet, Val and Willett, Peter}
}
@article {2018,
	title = {When Will AI Exceed Human Performance? Evidence from AI Experts},
	year = {2018},
	url = {https://jair.org/index.php/jair/article/download/11222/26431/},
	author = {Katja Grace and John Salvatier and Allan Dafoe and Baobao Zhang and Owain Evans}
}
@article {2018,
	title = {Will artificial intelligence solve the human resource crisis in healthcare?},
	journal = {BMC Health Services Research},
	volume = {18},
	year = {2018},
	month = {Jan-12-2018},
	doi = {10.1186/s12913-018-3359-4},
	author = {Mesk{\'o}, Bertalan and Het{\'e}nyi, Gergely and Gy{\H o}rffy, Zsuzsanna}
}
@article {2018,
	title = {Work and organizational psychology looks at the fourth industrial revolution: How to support workers and organizations? },
	journal = {Frontiers in Psychology},
	volume = {9},
	year = {2018},
	month = {Apr-11-2020},
	doi = {10.3389/fpsyg.2018.02365},
	author = {Ghislieri, Chiara and Molino, Monica and Cortese, Claudio G.}
}
@article {2017,
	title = {Algorithmically recognizable: Santorum{\textquoteright}s google problem, and google{\textquoteright}s santorum problem},
	journal = {Information, Communication \& Society},
	volume = {20},
	year = {2017},
	month = {Feb-01-2017},
	pages = {63 - 80},
	issn = {1369-118X},
	doi = {10.1080/1369118X.2016.1199721},
	author = {Gillespie, Tarleton}
}
@article {2017,
	title = {Artificial Intelligence For Social Good},
	year = {2017},
	note = {Sponsored by the Computing Community Consortium (CCC)},
	url = {https://cra.org/ccc/wp-content/uploads/sites/2/2016/04/AI-for-Social-Good-Workshop-Report.pdf},
	author = {Gregory D. Hager and Ann Drobnis and Fei Fang and Rayid Ghani and Amy Greenwald and Terah Lyons and David C. Parkes and Jason Schultz and Suchi Saria and Stephen F. Smith and Milind Tambe}
}
@article {2017,
	title = {Artificial intelligence in research},
	journal = {Science},
	volume = {357},
	year = {2017},
	month = {Jul-07-2017},
	pages = {28 - 30},
	issn = {0036-8075},
	doi = {10.1126/science.357.6346.28},
	author = {Musib, Mrinal and Wang, Feng and Tarselli, Michael A. and Yoho, Rachel and Yu, Kun-Hsing and Andr{\'e}s, Rigoberto Medina and Greenwald, Noah F. and Pan, Xubin and Lee, Chien-Hsiu and Zhang, Jian and Dutton-Regester, Ken and Johnston, Jake Wyatt and Sharafeldin, Icell Mahmoud}
}
@article {2017,
	title = {Debating big data: A literature review on realizing value from big data},
	journal = {The Journal of Strategic Information Systems},
	volume = {26},
	year = {2017},
	month = {Jan-09-2017},
	pages = {191 - 209},
	issn = {09638687},
	doi = {10.1016/j.jsis.2017.07.003},
	author = {G{\"u}nther, Wendy Arianne and Rezazade Mehrizi, Mohammad H. and Huysman, Marleen and Feldberg, Frans}
}
@article {2017,
	title = {A deep learning approach for quantifying tumor extent},
	journal = {Scientific Reports},
	volume = {7},
	year = {2017},
	month = {Jan-06-2017},
	doi = {10.1038/srep46450},
	author = {Cruz-Roa, Angel and Gilmore, Hannah and Basavanhally, Ajay and Feldman, Michael and Ganesan, Shridar and Shih, Natalie N.C. and Tomaszewski, John and Gonz{\'a}lez, Fabio A. and Madabhushi, Anant}
}
@mastersthesis {2017,
	title = {An empirical analysis of the impacts of robotization on employment in the Norwegian manufacturing industry},
	year = {2017},
	type = {master thesis},
	abstract = {Rapid advances in robotics, artificial intelligence, and digital technologies have introduced renewed concern that labor will become redundant. The aim of this thesis is to assess whether there exists a relationship between robotization and employment in the time periods 1996-2005 and 2008-2015 in Norwegian manufacturing industries. We exploit data on operational robots from the International Federation of Robotics and individual level data from the Norwegian Labour Force Survey, to assess a potential relationship between increased robotization and the probability of being employed within the manufacturing industries. Utilizing linear probability models, we find no negative relationship between increased robotization and the probability of being employed in Norwegian manufacturing industries. Further, we find indications of a relationship between increased robotization and skill-biases. However, the relationships are of no economic significance. Our findings are consistent with previous research on the impacts of robotization on employment outcomes. Further, we find that robotization is distinct and weakly correlated to import density and capital density.},
	url = {https://www.semanticscholar.org/paper/Will-robots-replace-us-\%3A-an-Empirical-analysis-of-Gr\%C3\%B8ndahl-Eriksen/e4e22bf2498e42d6308d81cc7483b5a0b8ba48e7},
	author = {Fredrik Gr{\o}ndahl and Gina Hegland Eriksen}
}
@article {2017,
	title = {Evaluating Assessments in the Age of Big Data and AI},
	year = {2017},
	url = {https://www.ibm.com/downloads/cas/D5GQD70R},
	author = {Nigel Guenole and Sheri Feinzig}
}
@article {2017,
	title = {An experimental comparison of Chatbot and Human task partners},
	journal = {Computers in Human Behavior},
	volume = {75},
	year = {2017},
	month = {Jan-10-2017},
	pages = {461 - 468},
	issn = {07475632},
	doi = {10.1016/j.chb.2017.05.045},
	author = {Fryer, Luke K. and Ainley, Mary and Thompson, Andrew and Gibson, Aaron and Sherlock, Zelinda}
}
@article {2017,
	title = {A future that works: Automation, employment and productivity},
	year = {2017},
	url = {https://www.mckinsey.com/mgi/overview},
	author = {James Manyika and Michael Chui and Mehdi Miremadi and Jaccques Bughin and Katy George and Paul Willmott and Martin Dewhurst}
}
@article {2017,
	title = {How computers will replace your doctor?},
	year = {2017},
	url = {https://theweek.com/articles/441528/how-computers-replace-doctor},
	author = {Pascal-Emmanuel Gobry}
}
@article {2017,
	title = {How is new technology changing job design?},
	journal = {IZA World of Labor},
	year = {2017},
	month = {Jan-01-2017},
	doi = {10.15185/izawol.344},
	author = {Gibbs, Michael}
}
@article {2017,
	title = {A review and synthesis of the individual work performance literature},
	journal = {Academy of Management Annals},
	volume = {11},
	year = {2017},
	month = {Jan-06-2017},
	pages = {825 - 885},
	issn = {1941-6520},
	doi = {10.5465/annals.2015.0151},
	author = {Carpini, Joseph A. and Parker, Sharon K. and Griffin, Mark A.}
}
@article {2017,
	title = {Revisiting the risk of automation},
	journal = {Economics Letters},
	volume = {159},
	year = {2017},
	month = {Jan-10-2017},
	pages = {157 - 160},
	issn = {01651765},
	doi = {10.1016/j.econlet.2017.07.001},
	author = {Arntz, Melanie and Gregory, Terry and Zierahn, Ulrich}
}
@article {2017,
	title = {Situational awareness, workload, and workflow preferences},
	journal = {The International Journal of Robotics Research},
	volume = {36},
	year = {2017},
	month = {Sep-06-2017},
	pages = {597 - 617},
	issn = {0278-3649},
	doi = {10.1177/0278364916688255},
	author = {Gombolay, Matthew and Bair, Anna and Huang, Cindy and Shah, Julie}
}
@conference {2017,
	title = {SPIE ProceedingsBuilding a framework to manage trust in automation},
	booktitle = {SPIE Defense + SecurityMicro- and Nanotechnology Sensors, Systems, and Applications IX},
	volume = {10194},
	year = {2017},
	pages = {101941U},
	publisher = {SPIE},
	organization = {SPIE},
	address = {Anaheim, California, United States},
	doi = {10.1117/12.2264245},
	author = {Metcalfe, J. S. and Amar R. Marathe and Haynes, B. and Paul, V. J. and Gremillion, G. M. and Drnec, K. and Atwater, C. and Estepp, J. R. and Lukos, J. R. and Carter, E. C. and W. D. Nothwang},
	editor = {George, Thomas and Dutta, Achyut K. and Islam, M. Saif}
}
@article {2017,
	title = {The strategic opportunities and challenges of algorithmic decision-making},
	journal = {The Journal of Strategic Information Systems},
	volume = {26},
	year = {2017},
	month = {Jan-09-2017},
	pages = {185 - 190},
	issn = {09638687},
	doi = {10.1016/j.jsis.2017.08.002},
	author = {Galliers, R.D. and Newell, S. and Shanks, G. and Topi, H.}
}
@article {2017,
	title = {A systematic framework for multilevel theorizing in information systems research},
	journal = {Information Systems Research},
	volume = {28},
	year = {2017},
	month = {Jan-06-2017},
	pages = {203 - 224},
	issn = {1047-7047},
	doi = {10.1287/isre.2017.0690},
	author = {Zhang, Meng and Gable, Guy G.}
}
@article {2017,
	title = {What to expect from artificial intelligence},
	journal = { MIT SLOAN MANAGEMENT REVIEW },
	volume = {58},
	year = {2017},
	note = {To understand how advances in artificial intelligence are
likely to change the workplace {\textemdash} and the work of managers
{\textemdash} you need to know where AI delivers the most value.},
	url = {http://ilp.mit.edu/media/news_articles/smr/2017/58311.pdf},
	author = {Ajay Agrawal and Joshua S. Gans and Avi Goldfarb}
}
@article {2016,
	title = {The digital workforce and the workplace of the future},
	journal = {Academy of Management Journal},
	volume = {59},
	year = {2016},
	month = {Jan-06-2016},
	pages = {731 - 739},
	issn = {0001-4273},
	doi = {10.5465/amj.2016.4003},
	author = {Colbert, Amy and Yee, Nick and George, Gerard}
}
@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 {2016,
	title = {Machine learning and decision support in critical care},
	journal = {Proceedings of the IEEE},
	volume = {104},
	year = {2016},
	month = {Jan-02-2016},
	pages = {444 - 466},
	issn = {0018-9219},
	doi = {10.1109/JPROC.2015.2501978},
	author = {Johnson, Alistair E. W. and Ghassemi, Mohammad M. and Nemati, Shamim and Niehaus, Katherine E. and Clifton, David and Clifford, Gari D.}
}
@conference {2016,
	title = {SPIE ProceedingsAn efficient fusion approach for combining human and machine decisions},
	booktitle = {SPIE Defense + SecurityMicro- and Nanotechnology Sensors, Systems, and Applications VIII},
	volume = {9836},
	year = {2016},
	pages = {983621},
	publisher = {SPIE},
	organization = {SPIE},
	address = {Baltimore, Maryland, United States},
	doi = {10.1117/12.2220788},
	url = {http://proceedings.spiedigitallibrary.org/proceeding.aspx?doi=10.1117/12.2220788},
	author = {Lee, Hyungtae and Kwon, Heesung and Ryan M. Robinson and W. D. Nothwang and Amar R. Marathe},
	editor = {George, Thomas and Dutta, Achyut K. and Islam, M. Saif}
}
@article {2016,
	title = {Will computers put us out of work? },
	journal = {Computer},
	volume = {49},
	year = {2016},
	month = {Jan-05-2016},
	pages = {82 - 85},
	issn = {0018-9162},
	doi = {10.1109/MC.2016.126},
	author = {King, John Leslie and Grudin, Jonathan}
}
@article {2015,
	title = {Decision-making authority, team efficiency and human worker satisfaction in mixed human{\textendash}robot teams},
	journal = {Autonomous Robots},
	volume = {39},
	year = {2015},
	month = {Jan-10-2015},
	pages = {293 - 312},
	issn = {0929-5593},
	doi = {10.1007/s10514-015-9457-9},
	author = {Gombolay, Matthew C. and Gutierrez, Reymundo A. and Clarke, Shanelle G. and Sturla, Giancarlo F. and Shah, Julie A.}
}
@article {RN30644,
	title = {Human-level control through deep reinforcement learning},
	journal = {Nature},
	volume = {518},
	number = {7540},
	year = {2015},
	pages = {529-533},
	type = {Journal Article},
	issn = {0028-0836},
	author = {Mnih, Volodymyr and Kavukcuoglu, Koray and Silver, David and Rusu, Andrei A and Veness, Joel and Bellemare, Marc G and Graves, Alex and Riedmiller, Martin and Fidjeland, Andreas K and Ostrovski, Georg}
}
@conference {2015,
	title = {Intelligible Models for HealthCare},
	booktitle = {the 21th ACM SIGKDD International ConferenceProceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining - KDD {\textquoteright}15},
	year = {2015},
	pages = {1721 - 1730},
	publisher = {ACM Press},
	organization = {ACM Press},
	address = {Sydney, NSW, AustraliaNew York, New York, USA},
	isbn = {9781450336642},
	doi = {10.1145/278325810.1145/2783258.2788613},
	author = {Caruana, Rich and Lou, Yin and Gehrke, Johannes and Koch, Paul and Sturm, Marc and Elhadad, Noemie}
}
@conference {2015,
	title = {Science bot: a model for the future computation},
	booktitle = {the 24th International ConferenceProceedings of the 24th International Conference on World Wide Web - WWW {\textquoteright}15 Companion},
	year = {2015},
	pages = {1061 - 1062},
	publisher = {ACM Press},
	organization = {ACM Press},
	address = {Florence, ItalyNew York, New York, USA},
	isbn = {9781450334730},
	doi = {10.1145/2740908.2742014},
	author = {Kuhn, Tobias}
}
@article {2015,
	title = { Users{\textquoteright} reactions to actions of automated programs in Wikipedia},
	journal = {Computers in Human Behavior},
	volume = {50},
	year = {2015},
	month = {Jan-09-2015},
	pages = {66 - 75},
	issn = {07475632},
	doi = {10.1016/j.chb.2015.03.078},
	author = {Cl{\'e}ment, Maxime and Guitton, Matthieu J.}
}
@conference {2014,
	title = {Leveraging the cross-cultural capacities of artificial agents as leaders of human virtual teams},
	booktitle = {European 10th Conference on Management Leadership and Governance},
	year = {2014},
	url = {https://www.researchgate.net/publication/268982256_Leveraging_the_Cross-Cultural_Capacities_of_Artificial_Agents_as_Leaders_of_Human_Virtual_Teams},
	author = {Matthew Gladden}
}
@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}
}
@conference {kittur2013future,
	title = {The future of crowd work},
	booktitle = {Proceedings of the 2013 conference on Computer supported cooperative work},
	year = {2013},
	pages = {1301{\textendash}1318},
	publisher = {ACM},
	organization = {ACM},
	author = {Kittur, Aniket and Jeffrey V Nickerson and Michael S. Bernstein and Gerber, Elizabeth and Shaw, Aaron and Zimmerman, John and Lease, Matt and Horton, John}
}
@article {2013,
	title = {The great reversal in the demand for skill and cognitive tasks},
	year = {2013},
	institution = {National Bureau of Economic Research},
	address = {Cambridge, MA},
	doi = {10.3386/w18901},
	author = {Beaudry, Paul and Green, David and Sand, Benjamin}
}
@book {2013,
	title = {Integration and implementation sciences for researching complex real-world problems},
	year = {2013},
	note = {Includes bibliographical references},
	isbn = {9781922144270},
	url = {https://www.jstor.org/stable/j.ctt2jbkj5},
	author = {Bammer and Gabriele}
}
@article {2010,
	title = {Not what it was and not what it will be: The future of job design research},
	journal = {Journal of Organizational Behavior},
	volume = {31},
	year = {2010},
	month = {Jan-02-2010},
	pages = {463 - 479},
	issn = {08943796},
	doi = {10.1002/job.v31:2/310.1002/job.678},
	author = {Oldham, Greg R. and Hackman, J. Richard},
	editor = {Grant, Adam and Fried, Yitzhak and Parker, Sharon and Frese, Michael}
}
@article {2010,
	title = {Understanding the role of occupational and organizational context},
	journal = {Journal of Organizational Behavior},
	volume = {31},
	year = {2010},
	month = {Jan-02-2010},
	pages = {351 - 360},
	issn = {08943796},
	doi = {10.1002/job.642},
	author = {Morgeson, Frederick P. and Dierdorff, Erich C. and Hmurovic, Jillian L.},
	editor = {Grant, Adam and Fried, Yitzhak and Parker, Sharon and Frese, Michael}
}
@conference {2009,
	title = {The changing face of digital science},
	booktitle = {the 27th international conference extended abstractsProceedings of the 27th international conference extended abstracts on Human factors in computing systems - CHI EA {\textquoteright}09},
	year = {2009},
	pages = {4819},
	publisher = {ACM Press},
	organization = {ACM Press},
	address = {Boston, MA, USANew York, New York, USA},
	isbn = {9781605582474},
	doi = {10.1145/1520340.1520749},
	author = {Aragon, Cecilia R. and Poon, Sarah and Silva, Claudio T.}
}
@article {2009,
	title = {Redesigning work design theories: The rise of relational and proactive perspectives},
	journal = {The Academy of Management Annals},
	volume = {3},
	year = {2009},
	month = {Jan-01-2009},
	pages = {317 - 375},
	issn = {1941-6520},
	doi = {10.1080/19416520903047327},
	author = {Grant, Adam M. and Parker, Sharon K.}
}
@book {2008,
	title = {Handbook of transdisciplinary research},
	year = {2008},
	pages = {427 - 432},
	publisher = {Springer Netherlands},
	organization = {Springer Netherlands},
	address = {Dordrecht},
	isbn = {978-1-4020-6698-6},
	doi = {10.1007/978-1-4020-6699-3_28},
	editor = {Hadorn, Gertrude Hirsch and Hoffmann-Riem, Holger and Biber-Klemm, Susette and Grossenbacher-Mansuy, Walter and Joye, Dominique and Pohl, Christian}
}
@proceedings {1995,
	title = {Complementary allocation of functions in automated work systems},
	volume = {20},
	year = {1995},
	pages = {989-994},
	publisher = {Elsevier},
	author = {G. Grote and S. Weik and T. Wafler and M. Zolch}
}
