@article {Zavrsnik2020,
	title = {Criminal justice, artificial intelligence systems, and human rights},
	journal = {ERA Forum},
	volume = {20},
	number = {4},
	year = {2020},
	pages = {567{\textendash}583},
	publisher = {The Author(s)},
	abstract = {The automation brought about by big data analytics, machine learning and artificial intelligence systems challenges us to reconsider fundamental questions of criminal justice. The article outlines the automation which has taken place in the criminal justice domain and answers the question of what is being automated and who is being replaced thereby. It then analyses encounters between artificial intelligence systems and the law, by considering case law and by analysing some of the human rights affected. The article concludes by offering some thoughts on proposed solutions for remedying the risks posed by artificial intelligence systems in the criminal justice domain.},
	keywords = {Algorithms, artificial intelligence, automation, Criminal justice, Fair trial, Human rights},
	isbn = {1202702000602},
	issn = {18639038},
	doi = {10.1007/s12027-020-00602-0},
	url = {http://dx.doi.org/10.1007/s12027-020-00602-0},
	author = {Zavr{\v s}nik, Ale{\v s}}
}
@article {Bansal2020,
	title = {Does the Whole Exceed its Parts? The Effect of AI Explanations on Complementary Team Performance},
	year = {2020},
	abstract = {<p>Increasingly, organizations are pairing humans with AI systems to improve decision-making and reducing costs. Proponents of human-centered AI argue that team performance can even further improve when the AI model explains its recommendations. However, a careful analysis of existing literature reveals that prior studies observed improvements due to explanations only when the AI, alone, outperformed both the human and the best human-AI team. This raises an important question: can explanations lead to complementary performance, i.e., with accuracy higher than both the human and the AI working alone? We address this question by devising comprehensive studies on human-AI teaming, where participants solve a task with help from an AI system without explanations and from one with varying types of AI explanation support. We carefully controlled to ensure comparable human and AI accuracy across experiments on three NLP datasets (two for sentiment analysis and one for question answering). While we found complementary improvements from AI augmentation, they were not increased by state-of-the-art explanations compared to simpler strategies, such as displaying the AI{\textquoteright}s confidence. We show that explanations increase the chance that humans will accept the AI{\textquoteright}s recommendation regardless of whether the AI is correct. While this clarifies the gains in team performance from explanations in prior work, it poses new challenges for human-centered AI: how can we best design systems to produce complementary performance? Can we develop explanatory approaches that help humans decide whether and when to trust AI input?</p>},
	url = {http://arxiv.org/abs/2006.14779},
	author = {Bansal, Gagan and Wu, Tongshuang and Zhou, Joyce and Fok, Raymond and Nushi, Besmira and Kamar, Ece and Ribeiro, Marco Tulio and Weld, Daniel S.}
}
@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 {2019,
	title = {Artificial intelligence in workplaces and how it will affect employment in Latvia},
	journal = {Environment. Technology. Resources. Proceedings of the International Scientific and Practical Conference},
	volume = {2},
	year = {2019},
	month = {Aug-06-2020},
	pages = {154},
	issn = {1691-5402},
	doi = {10.17770/etr2019vol2.4151},
	author = {{\v S}ukjurovs, Ilm{\={a}}rs and Zvirgzdina, Rosita and Jeromanova-Maura, Silva}
}
@article {2019,
	title = {Automation, wage inequality and implications of a robot tax},
	journal = {International Review of Economics \& Finance},
	volume = {59},
	year = {2019},
	month = {Jan-01-2019},
	pages = {500 - 509},
	issn = {10590560},
	doi = {10.1016/j.iref.2018.10.013},
	author = {Zhang, Pengqing}
}
@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}
}
@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}
}
@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}
}
@article {2019,
	title = {Labor, technology and work organization: An introduction to the forum},
	journal = {Journal of Industrial and Business Economics},
	volume = {46},
	year = {2019},
	month = {Jan-09-2019},
	pages = {313 - 321},
	issn = {0391-2078},
	doi = {10.1007/s40812-019-00126-w},
	author = {Cirillo, Valeria and Molero Zayas, Jos{\'e}}
}
@article {2018,
	title = {Applications of machine learning algorithms to predict therapeutic outcomes in depression: A meta-analysis and systematic review},
	journal = {Journal of Affective Disorders},
	volume = {241},
	year = {2018},
	pages = {519-532},
	issn = {01650327},
	doi = {10.1016/j.jad.2018.08.073},
	author = {Lee, Yena and Ragguett, Renee-Marie and Mansur, Rodrigo B. and Boutilier, Justin J. and Rosenblat, Joshua D. and Trevizol, Alisson and Brietzke, Elisa and Lin, Kangguang and Pan, Zihang and Subramaniapillai, Mehala and Chan, Timothy C.Y. and Fus, Dominika and Park, Caroline and Musial, Natalie and Zuckerman, Hannah and Chen, Vincent Chin-Hung and Ho, Roger and Rong, Carola and McIntyre, Roger S.}
}
@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 = {How the anthropormorphization of virtual assistants influences user{\textquoteright}s trust},
	journal = {Academy of Management Proceedings},
	volume = {2018},
	year = {2018},
	month = {Jan-08-2018},
	pages = {16328},
	issn = {0065-0668},
	doi = {10.5465/AMBPP.2018.16328abstract},
	author = {Crone, Tim and Shafeie Zargar, Mahmood}
}
@article {2018,
	title = {How to respond to the fourth industrial revolution, or the second information technology revolution? Dynamic new combinations between technology, market, and society through open innovation},
	journal = {Journal of Open Innovation: Technology, Market, and Complexity},
	volume = {4},
	year = {2018},
	month = {Jan-09-2018},
	pages = {21},
	doi = {10.3390/joitmc4030021},
	author = {Lee, MinHwa and Yun, JinHyo and Pyka, Andreas and Won, DongKyu and Kodama, Fumio and Schiuma, Giovanni and Park, HangSik and Jeon, Jeonghwan and Park, KyungBae and Jung, KwangHo and Yan, Min-Ren and Lee, SamYoul and Zhao, Xiaofei}
}
@article {2018,
	title = {Should we fear the robot revolution?},
	journal = {Journal of Monetary Economics},
	volume = {97},
	year = {2018},
	month = {Jan-08-2018},
	pages = {117 - 148},
	issn = {03043932},
	doi = {10.1016/j.jmoneco.2018.05.014},
	author = {Berg, Andrew and Buffie, Edward F. and Zanna, Luis-Felipe}
}
@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 {2017,
	title = {Artificial intelligence in healthcare: past, present and future},
	journal = {Stroke and Vascular Neurology},
	volume = {2},
	year = {2017},
	month = {Aug-12-2018},
	pages = {230 - 243},
	issn = {2059-8688},
	doi = {10.1136/svn-2017-000101},
	author = {Jiang, Fei and Jiang, Yong and Zhi, Hui and Dong, Yi and Li, Hao and Ma, Sufeng and Wang, Yilong and Dong, Qiang and Shen, Haipeng and Wang, Yongjun}
}
@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 {657,
	title = {Gravity Spy: Integrating Advanced LIGO Detector Characterization, Machine Learning, and Citizen Science},
	journal = {Classical and Quantum Gravity},
	volume = {34},
	year = {2017},
	pages = {064003},
	type = {Journal Article},
	doi = {10.1088/1361-6382/aa5cea},
	author = {Michael Zevin and Scott Coughlin and Sara Bahaadini and Emre Besler and Neda Rohani and Sarah Allen and Miriam Cabero and Kevin Crowston and Aggelos Katsaggelos and Shane Larson and Tae Kyoung Lee and Chris Lintott and Tyson Littenberg and Andrew Lundgren and Carsten Oesterlund and Joshua Smith and Laura Trouille and Vicky Kalogera}
}
@article {2017,
	title = {House gets serious about driverless cars},
	year = {2017},
	url = {https://thehill.com/policy/transportation/344141-driverless-car-bill-speeds-through-house},
	author = {Melanie Zanona}
}
@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}
}
@conference {2017,
	title = {Robots, ai, and the question of {\textquoteright}e-persons{\textquoteright}},
	booktitle = {Journal of science communication},
	year = {2017},
	month = {07/2017},
	keywords = {bots, Public perception of science and technology, Public understanding of science and technology, Science and policy-making},
	url = {http://eprints.whiterose.ac.uk/124830/},
	author = {Michael zollosy}
}
@article {2017,
	title = {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.}
}
@conference {2016,
	title = {Disrupting developer productivity one bot at a time},
	booktitle = {the 2016 24th ACM SIGSOFT International SymposiumProceedings of the 2016 24th ACM SIGSOFT International Symposium on Foundations of Software Engineering - FSE 2016},
	year = {2016},
	pages = {928 - 931},
	publisher = {ACM Press},
	organization = {ACM Press},
	address = {Seattle, WA, USANew York, New York, USA},
	isbn = {9781450342186},
	doi = {10.1145/2950290.2983989},
	author = {Storey, Margaret-Anne and Zagalsky, Alexey}
}
@article {2015,
	title = {The history of technological anxiety and the future of economic growth: Is this time different? },
	journal = {Journal of Economic Perspectives},
	volume = {29},
	year = {2015},
	month = {Jan-08-2015},
	pages = {31 - 50},
	issn = {0895-3309},
	doi = {10.1257/jep.29.3.31},
	author = {Mokyr, Joel and Vickers, Chris and Ziebarth, Nicolas L.}
}
@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 {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}
}
@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}
}
