@proceedings {wang2024reelframer, title = {ReelFramer: Human-AI Co-Creation for News-to-Video Translation}, year = {2024}, address = {Honolulu, Hawai{\textquoteright}i}, abstract = {

Short videos on social media are the dominant way young people consume content. News outlets aim to reach audiences through news reels -- short videos conveying news -- but struggle to translate traditional journalistic formats into short, entertaining videos. To translate news into social media reels, we support journalists in reframing the narrative. In literature, narrative framing is a high-level structure that shapes the overall presentation of a story. We identified three narrative framings for reels that adapt social media norms but preserve news value, each with a different balance of information and entertainment. We introduce ReelFramer, a human-AI co-creative system that helps journalists translate print articles into scripts and storyboards. ReelFramer supports exploring multiple narrative framings to find one appropriate to the story. AI suggests foundational narrative details, including characters, plot, setting, and key information. ReelFramer also supports visual framing; AI suggests character and visual detail designs before generating a full storyboard. Our studies show that narrative framing introduces the necessary diversity to translate various articles into reels, and establishing foundational details helps generate scripts that are more relevant and coherent. We also discuss the benefits of using narrative framing and foundational details in content retargeting.

}, url = {https://arxiv.org/abs/2304.09653}, author = {Sitong Wang and Samia Menon and Tao Long and Keren Henderson and Dingzeyu Li and Kevin Crowston and Mark Hansen and Jeffrey V. Nickerson and Lydia B. Chilton} } @article {9998, title = {Artificial intelligence in information systems: State of the art and research roadmap}, journal = {Communications of the Association for Information Systems (CAIS)}, volume = {50}, year = {2022}, abstract = {

Many would argue that artificial intelligence (AI) is not just a technology but represents a paradigmatic shift in the relationship between humans and machines. Much of the literature assumes that AI-powered practices are substantially different and profoundly changes organizational structures, communication, affordances, and ecosystems. However, research in AI is often fragmented and lacks clarity. While the Information Systems (IS) field can play a pivotal role in the emergence and use of AI, there is a need for a clear direction that specifies how IS can contribute and what are to be the key research themes and questions. This paper draws on a PDW at ICIS 2020 and the discussions that followed. It summarizes and synthesizes five decades of the impact of AI on organizational practices, providing views from various perspectives. It identifies weaknesses in the current AI literature as measured against conceptual clarity, theoretical glue, cumulative tradition, parsimony, and applicability. The paper concludes by identifying direct actions that the IS research community can undertake to address these issues. The final contribution is a next-step research agenda to guide AI research in the coming years.

}, doi = {10.17705/1CAIS.05017}, attachments = {https://waim.network/sites/crowston.syr.edu/files/Artificial\%20Intelligence\%20in\%20Information\%20Systems\%20State\%20of\%20the\%20Art.pdf}, author = {P{\"a}r J. {\r A}gerfalk and Kieran Conboy and Kevin Crowston and Sirkka L. Jarvenpaa and Jenny Eriksson Lundstr{\"o}m and Patrick Mikalef and Sudha Ram} } @article {2021, title = {Hybrid intelligence in business networks}, journal = {Electronic Markets}, year = {2021}, month = {Nov-06-2021}, issn = {1019-6781}, doi = {10.1007/s12525-021-00481-4}, attachments = {https://waim.network/sites/crowston.syr.edu/files/Ebel2021_Article_HybridIntelligenceInBusinessNe.pdf}, author = {Ebel, Philipp and S{\"o}llner, Matthias and Leimeister, Jan Marco and Crowston, Kevin and de Vreede, Gert-Jan} } @booklet {Cebreros2020, title = {Automation Technologies and Employment at Risk : The Case of Mexico}, year = {2020}, publisher = {Banco de M{\'e}xico}, author = {Cebreros, Alfonso and Heffner-Rodr{\'\i}guez, Aldo and Livas, Ren{\'e} and Puggioni, Daniela} } @article {Johnson2020, title = {The benefits of eHRM and AI for talent acquisition}, journal = {Journal of Tourism Futures}, year = {2020}, abstract = {Purpose : The hospitality and tourism industry faces a number of workforce challenges, especially the high turnover rates and associated replacement costs associated with continually identifying and hiring new employees. The purpose of this paper is to discuss how hospitality and tourism organizations can use electronic human resource management (eHRM) and artificial intelligence (AI) to help recruit and select qualified employees, increase individual retention rates and decrease the time needed to replace employees. Specifically, it discusses how e-recruiting and e-selection and AI tools can help hospitality and tourism organizations improve recruiting and selection outcomes. Design/methodology/approach: Research on eHRM, AI, employee recruitment and employee selection are applied to the hospitality and tourism industry and insights for how eHRM and AI can be applied to the industry are discussed. Findings: eHRM and AI have the potential to transform how the hospitality and tourism industry recruit and select employees. However, care must be taken to ensure that the insights gained and the decisions made are well received by employees and lead to better employee and organizational outcomes. Research limitations/implications: This paper represents the first research that integrates research from eHRM and AI and applies it to the hospitality and tourism industry. Originality/value: This paper represents the first research that integrates research from eHRM and AI and applies it to the hospitality and tourism industry.}, keywords = {artificial intelligence, e-HRM, e-recruiting, e-selection, eHRM, Electronic human resource management, Employee selection, Recruitment, Selection}, issn = {2055592X}, doi = {10.1108/JTF-02-2020-0013}, author = {Johnson, Richard D and Stone, Dianna L and Lukaszewski, Kimberly M} } @article {Acemoglu2020, title = {Competing with Robots: Firm-Level Evidence from France}, journal = {AEA Papers and Proceedings}, volume = {110}, year = {2020}, pages = {383{\textendash}388}, abstract = {We study the firm-level implications of robot adoption in France. Of 55,390 firms in our sample, 598 adopted robots between 2010 and 2015, but these firms accounted for 20 percent of manufacturing employment. Adopters experienced significant declines in labor shares, the share of production workers in employment, and increases in value added and productivity. They expand their overall employment as well. However, this expansion comes at the expense of competitors, leading to an overall negative association between adoption and employment. Robot adoption has a large impact on the labor share because adopters are larger and grow faster than their competitors.}, keywords = {automation, competition, j23, j24, jel codes, l11, labor share, manufacturing, productivity, reallocation, robots, tasks}, issn = {2574-0768}, doi = {10.1257/pandp.20201003}, author = {Acemoglu, Daron and Lelarge, Claire and Restrepo, Pascual} } @article {Jung2020, title = {Industrial robots, employment growth, and labor cost: A simultaneous equation analysis}, journal = {Technological Forecasting and Social Change}, volume = {159}, number = {June}, year = {2020}, pages = {120202}, publisher = {Elsevier}, abstract = {In recent years, the global rapid expansion of industrial robots has induced ever-increasing concerns for the cause and effect of such growth, particularly with regard to its relationship with labor. This paper analyzes the factors underlying the adoption of industrial robots, employment growth and structure, and labor costs, taking into account the two-way causalities between these variables. For the empirical analysis, we use the three-stage least squares (3SLS) method for the system of simultaneous equations and apply it to the panel data constructed for 42 countries. Explanatory variables for each equation include the dependent variables of other equations and exogenous variables, such as the labor market environment, physical and human capital, and country-specific social environment. The empirical results of the present study indicate that the increase in both unit labor costs and hourly compensation level induces an extensive application of industrial robots. Subsequently, the expansion of industrial robots leads to a reduction of unit labor costs; however, the hourly compensation level increases, implying that the productivity-enhancing effect exceeds the wage-increasing effect of industrial robots. The extensive use of industrial robots tends to suppress employment growth, confirming the labor-substituting effect of industrial robots; the observed trend disproportionately affects low-skilled labor.}, keywords = {Compensation level, Employment growth, Industrial robots, Labor cost, Simultaneous equation analysis}, issn = {00401625}, doi = {10.1016/j.techfore.2020.120202}, url = {https://doi.org/10.1016/j.techfore.2020.120202}, author = {Jung, Jin Hwa and Lim, Dong Geon} } @article {Capatina2020, title = {Matching the future capabilities of an artificial intelligence-based software for social media marketing with potential users{\textquoteright} expectations}, journal = {Technological Forecasting and Social Change}, volume = {151}, number = {June 2019}, year = {2020}, pages = {119794}, publisher = {Elsevier}, abstract = {The increasing use of Artificial Intelligence (AI) in Social Media Marketing (SMM) triggered the need for this research to identify and further analyze such expectations of potential users of an AI-based software for Social Media Marketing; a software that will be developed in the next two years, based on its future capabilities. In this research, we seek to discover how the potential users of this AI-based software (owners and employees from digital agencies based in France, Italy and Romania, as well as freelancers from these countries, with expertise in SMM) perceive the capabilities that we offer, as a way to differentiate our technological solution from other available in the market. We propose a causal model to find out which expected capabilities of the future AI-based software can explain potential users{\textquoteright} intention to test and use this innovative technological solution for SMM, based on integer valued regression models. With this purpose, R software is used to analyze the data provided by the respondents. We identify different causal configurations of upcoming capabilities of the AI-based software, classified in three categories (audience, image and sentiment analysis), and will trigger potential users{\textquoteright} intention to test and use the software, based on an fsQCA approach.}, keywords = {artificial intelligence, Audience analysis, Image analysis, machine learning, Sentiment analysis, Social media marketing}, issn = {00401625}, doi = {10.1016/j.techfore.2019.119794}, url = {https://doi.org/10.1016/j.techfore.2019.119794}, author = {Capatina, Alexandru and Kachour, Maher and Lichy, Jessica and Micu, Adrian and Micu, Angela Eliza and Codignola, Federica} } @article {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 = {AI-Assisted Decision-making in Healthcare}, journal = {Asian Bioethics Review}, volume = {11}, year = {2019}, month = {Jan-09-2019}, pages = {299 - 314}, issn = {1793-8759}, doi = {10.1007/s41649-019-00096-0}, author = {Lysaght, Tamra and Lim, Hannah Yeefen and Xafis, Vicki and Ngiam, Kee Yuan} } @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 = {Apple reminds us that behind the AI revolution lies an army of humans seeing our data}, journal = {Forbes}, year = {2019}, url = {https://www.forbes.com/sites/kalevleetaru/2019/07/30/apple-reminds-us-that-behind-the-ai-revolution-lies-an-army-of-humans-seeing-our-data/$\#$3dd2e8ba339d}, author = {Kalev Leetaru} } @article {2019, title = {Are robots competing for your job? }, journal = {The New Yorker}, year = {2019}, month = {03/2019}, type = {Annals of Technology}, url = {https://www.newyorker.com/magazine/2019/03/04/are-robots-competing-for-your-job}, author = {Jill Lepore} } @article {2019, title = {Automation as Part of the Solution}, journal = {Journal of Management Inquiry}, volume = {28}, year = {2019}, month = {Jun-07-2021}, pages = {316 - 318}, issn = {1056-4926}, doi = {10.1177/1056492619827375}, author = {Levine, David I.} } @conference {2019, title = {Beyond Dyadic Interactions: Considering Chatbots as Community Members}, booktitle = {Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems - CHI {\textquoteright}19}, year = {2019}, pages = {1-13}, publisher = {ACM Press}, organization = {ACM Press}, address = {Glasgow, Scotland UK}, isbn = {9781450359702}, doi = {10.1145/3290605}, author = {Seering, Joseph and Luria, Michal and Kaufman, Geoff and Hammer, Jessica} } @article {2019, title = {Can nurses remain relevant in a technologically advanced future?}, journal = {International Journal of Nursing Sciences}, volume = {6}, year = {2019}, month = {Jan-01-2019}, pages = {106 - 110}, issn = {23520132}, doi = {10.1016/j.ijnss.2018.09.013}, author = {Pepito, Joseph Andrew and Locsin, Rozzano} } @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 = {Digital inequalities in the age of artificial intelligence and big data}, journal = {Human Behavior and Emerging Technologies}, volume = {1}, year = {2019}, month = {Feb-04-2021}, pages = {141 - 148}, issn = {2578-1863}, doi = {10.1002/hbe2.140}, author = {Lutz, Christoph} } @conference {2019, title = {Does automation influence career decisions among South African students?}, booktitle = {the South African Institute of Computer Scientists and Information Technologists 2019Proceedings of the South African Institute of Computer Scientists and Information Technologists 2019 on ZZZ - SAICSIT {\textquoteright}19}, year = {2019}, pages = {1 - 10}, publisher = {ACM Press}, organization = {ACM Press}, address = {Skukuza, South AfricaNew York, New York, USA}, isbn = {9781450372657}, doi = {10.1145/335110810.1145/3351108.3351137}, author = {Mbilini, Sakhumzi N. and le Roux, Daniel B. and Parry, Douglas A.} } @article {2019, title = {Does the use of synchrony and artificial intelligence in video interviews affect interview ratings and applicant attitudes?}, journal = {Computers in Human Behavior}, volume = {98}, year = {2019}, month = {Jan-09-2019}, pages = {93 - 101}, issn = {07475632}, doi = {10.1016/j.chb.2019.04.012}, author = {Suen, Hung-Yue and Chen, Mavis Yi-Ching and Lu, Shih-Hao} } @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} } @conference {2019, title = {The future of human-AI collaboration: A taxonomy of design knowledge for hybrid intelligence systems}, booktitle = {Hawaii International Conference on System Sciences (HICSS)}, year = {2019}, month = {09/2018}, abstract = {Recent technological advances, especially in the field of machine learning, provide astonishing progress on the road towards artificial general intelligence. However, tasks in current real-world business applications cannot yet be solved by machines alone. We, therefore, identify the need for developing socio-technological ensembles of humans and machines. Such systems possess the ability to accomplish complex goals by combining human and artificial intelligence to collectively achieve superior results and continuously improve by learning from each other. Thus, the need for structured design knowledge for those systems arises. Following a taxonomy development method, this article provides three main contributions: First, we present a structured overview of interdisciplinary research on the role of humans in the machine learning pipeline. Second, we envision hybrid intelligence systems and conceptualize the relevant dimensions for system design for the first time. Finally, we offer useful guidance for system developers during the implementation of such applications.}, url = {https://www.alexandria.unisg.ch/publications/254994}, author = {Dominik Dellermann and Adrian Calma and Nikolaus Lipusch and Thorsten Weber and Sascha Weigel and Philipp Ebel} } @article {2019, title = {The future of the work in America}, year = {2019}, month = {07/2019}, keywords = {consulting reports}, url = {https://www.mckinsey.com/featured-insights/future-of-work/the-future-of-work-in-america-people-and-places-today-and-tomorrow}, author = {Susan Lund and James Manyika and Liz Hilton Segal and Andre Dua and Bryan Hancock and Scott Rutherford and Brent Macon} } @article {2019, title = {Global commission on the future of work}, year = {2019}, institution = {International Labour Organization }, keywords = {government reports}, url = {https://www.ilo.org/global/topics/future-of-work/WCMS_569528/lang--en/index.htm}, author = {Cyril Ramaphosa and Stefan Lofven} } @proceedings {2019, title = {How to Streamline AI Application in Government? A Case Study on Citizen Participation in Germany}, volume = {Lecture Notes in Computer Science 11685}, year = {2019}, pages = {233-247}, publisher = {Springer International Publishing}, address = {Cham}, abstract = {Artificial intelligence (AI) technologies are on the rise in almost every aspect of society, business and government. Especially in government, it is of interest how the application of AI can be streamlined: at least, in a controlled environment, in order to be able to evaluate potential (positive and negative) impact. Unfortunately, reuse in development of AI applications and their evaluation results lack interoperability and transferability. One potential remedy to this challenge would be to apply standardized artefacts: not only on a technical level, but also on an organization or semantic level. This paper presents findings from a qualitative explorative case study on online citizen participation in Germany that reveal insights on the current standardization level of AI applications. In order to provide an in-depth analysis, the research involves evaluation of two particular AI approaches to natural language processing. Our findings suggest that standardization artefacts for streamlining AI application exist predominantly on a technical level and are still limited.}, isbn = {978-3-030-27324-8}, issn = {0302-9743}, doi = {10.1007/978-3-030-27325-5}, author = {Balta, Dian and Kuhn, Peter and Sellami, Mahdi and Kulus, Daniel and Lieven, Claudius and Krcmar, Helmut}, editor = {Lindgren, Ida and Janssen, Marijn and Lee, Habin and Polini, Andrea and Rodr{\'\i}guez Bol{\'\i}var, Manuel Pedro and Scholl, Hans Jochen and Tambouris, Efthimios} } @article {2019, title = {Hybrid Intelligence}, journal = {Business \& Information Systems Engineering}, volume = {61}, year = {2019}, month = {Jan-10-2019}, pages = {637 - 643}, issn = {2363-7005}, doi = {10.1007/s12599-019-00595-2}, author = {Dellermann, Dominik and Ebel, Philipp and S{\"o}llner, Matthias and Leimeister, Jan Marco} } @conference {2019, title = {Impacts of Artificial Intelligence on Public Administration: A Systematic Literature Review}, booktitle = {2019 14th Iberian Conference on Information Systems and Technologies (CISTI)}, year = {2019}, isbn = {978-989-98434-9-3}, url = {https://ieeexplore.ieee.org/document/8760778}, author = {Jo{\~a}o Reis and Paula Esp{\'\i}rito Santo and Lisbon, Portugal and Nuno Mel{\~a}o} } @article {2019, title = {Machine learning concepts, concerns and opportunities for a pediatric radiologist}, journal = {Pediatric Radiology}, volume = {49}, year = {2019}, month = {Jan-04-2019}, pages = {509 - 516}, issn = {0301-0449}, doi = {10.1007/s00247-018-4277-7}, author = {Moore, Michael M. and Slonimsky, Einat and Long, Aaron D. and Sze, Raymond W. and Iyer, Ramesh S.} } @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 = {Mitigating bias in algorithmic employment screening: Evaluating claims and practices}, year = {2019}, abstract = {

There has been rapidly growing interest in the use of algorithms for employment assessment,especially as a means to address or mitigate bias in hiring. Yet, to date, little is known abouthow these methods are being used in practice. How are algorithmic assessments built, vali-dated, and examined for bias? In this work, we document and assess the claims and practicesof companies offering algorithms for employment assessment, using a methodology that can beapplied to evaluate similar applications and issues of bias in other domains. In particular, weidentify vendors of algorithmic pre-employment assessments (i.e., algorithms to screen candi-dates), document what they have disclosed about their development and validation procedures,and evaluate their techniques for detecting and mitigating bias. We find that companies{\textquoteright} for-mulation of {\textquotedblleft}bias{\textquotedblright} varies, as do their approaches to dealing with it. We also discuss the variouschoices vendors make regarding data collection and prediction targets, in light of the risks andtrade-offs that these choices pose. We consider the implications of these choices and we raise anumber of technical and legal considerations.

}, keywords = {social power of algorithms}, url = {https://www.researchgate.net/publication/333971698_Mitigating_Bias_in_Algorithmic_Employment_Screening_Evaluating_Claims_and_Practices}, author = {Manish Raghavan and Solon Barocas and Jon KleinbergKaren Levy} } @article {2019, title = {The moderating roles of perceived organizational support and competitive psychological climate}, journal = {Tourism Management}, volume = {73}, year = {2019}, month = {Jan-08-2019}, pages = {172 - 181}, issn = {02615177}, doi = {10.1016/j.tourman.2019.02.006}, author = {Li, Jun (Justin) and Bonn, Mark A. and Ye, Ben Haobin} } @article {2019, title = {Negotiated and reciprocal exchange structures in human-agent cooperation}, journal = {Computers in Human Behavior}, volume = {90}, year = {2019}, month = {Jan-01-2019}, pages = {288 - 297}, issn = {07475632}, doi = {10.1016/j.chb.2018.08.012}, author = {Chiou, Erin K. and Lee, John D. and Su, Tianshuo} } @article {2019, title = {Nurses{\textquoteright} Views on the Potential Use of Robots in the Pediatric Unit}, journal = {Journal of Pediatric Nursing}, volume = {47}, year = {2019}, month = {Jan-07-2019}, pages = {e58 - e64}, issn = {08825963}, doi = {10.1016/j.pedn.2019.04.027}, author = {Liang, Hwey-Fang and Wu, Kuang-Ming and Weng, Cheng-Hsing and Hsieh, Hui-Wen} } @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} } @book {2019, title = {Steps toward a scaffolding design framework}, year = {2019}, pages = {149 - 161}, publisher = {Springer International Publishing}, organization = {Springer International Publishing}, address = {Cham}, isbn = {978-3-030-12333-8}, issn = {1571-5035}, doi = {10.1007/978-3-030-12334-5_5}, author = {Correia, Ant{\'o}nio and Jameel, Shoaib and Paredes, Hugo and Fonseca, Benjamim and Schneider, Daniel}, editor = {Khan, Vassillis-Javed and Papangelis, Konstantinos and Lykourentzou, Ioanna and Markopoulos, Panos} } @book {2019, title = {Technology and Work Worth Doing (Not Jobs) Post-AlphaGo: A World-Building Workshop on the Future of Artificial Intelligence}, year = {2019}, publisher = {RAND Corporation}, organization = {RAND Corporation}, doi = {10.7249/CF398}, author = {Pendleton-Jullian, Ann and Lempert, Robert} } @article {2019, title = {There is no general AI: Why Turing machines cannot pass the Turing test}, year = {2019}, url = {https://arxiv.org/abs/1906.05833}, author = {Jobst Landgrebe} } @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 = {

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.

}, 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} } @article {2019, title = {Transforming the communication between citizens and government through AI-guided chatbots}, journal = {Government Information Quarterly}, volume = {36}, year = {2019}, month = {Jan-04-2019}, pages = {358 - 367}, issn = {0740624X}, doi = {10.1016/j.giq.2018.10.001}, url = {https://doi.org/10.1016/j.giq.2018.10.001}, author = {Androutsopoulou, Aggeliki and Karacapilidis, Nikos and Loukis, Euripidis and Charalabidis, Yannis} } @article {2019, title = {Will Artificial Intelligence Replace Radiologists?}, journal = {Radiology: Artificial Intelligence}, volume = {1}, year = {2019}, month = {Jan-05-2019}, pages = {e190058}, doi = {10.1148/ryai.2019190058}, author = {Langlotz, Curtis P.} } @article {2019, title = {Will artificial intelligence take over human resources recruitment and selection?}, journal = {Network Intelligence Studies}, volume = {VII}, year = {2019}, keywords = {artificial intelligence, human resources information systems, recruitment and selection}, url = {https://ideas.repec.org/a/cmj/networ/y2019i13p21-30.html}, author = {Bilal Hmoud and Varallya Laszlo} } @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 = {Artificial intelligence can transform the economy}, year = {2018}, month = {09/2018}, url = {https://www.washingtonpost.com/opinions/artificial-intelligence-can-transform-the-economy/2018/09/18/50c9c9c8-bab8-11e8-bdc0-90f81cc58c5d_story.html}, author = {Erik Brynjolfsson and Xiang Hui and Meng Liu} } @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} } @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 {seidel2018autonomous, title = {Autonomous tools and design: a triple-loop approach to human-machine learning}, journal = {Communications of the ACM}, volume = {62}, year = {2018}, pages = {50{\textendash}57}, publisher = {ACM}, author = {Seidel, Stefan and Berente, Nicholas and Lindberg, Aron and Lyytinen, Kalle and Jeffrey V Nickerson} } @article {seidel2018autonomous, title = {Autonomous Tools in System Design: Reflective Practice in Ubisofts Ghost Recon Wildlands Project}, journal = {Computer}, volume = {51}, year = {2018}, pages = {16{\textendash}23}, publisher = {IEEE}, author = {Seidel, Stefan and Berente, Nicholas and Martinez, Beno\^{\i}t and Lindberg, Aron and Lyytinen, Kalle and Jeffrey V Nickerson} } @article {2018, title = {{\textquoteleft}The beginning of a wave{\textquoteright}: A.I. Tiptoes into the workplace}, journal = {The NewYork Times}, year = {2018}, keywords = {AI, impacts}, url = {https://www.nytimes.com/2018/08/05/technology/workplace-ai.html}, author = {Steve Lohr} } @article {2018, title = {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.} } @article {2018, title = {A critical approach to human helping in information systems: Heteromation in the Brazilian correspondent banking system}, journal = {Information and Organization}, volume = {28}, year = {2018}, month = {Jan-09-2018}, pages = {111 - 128}, issn = {14717727}, doi = {10.1016/j.infoandorg.2018.08.002}, author = {Diane E. Bailey and Eduardo H. Diniz and Bonnie A. Nardi and Paul M. Leonardi and Dan Sholler} } @article {2018, title = {Cryptocurrency, Artificial Intelligence and basic income as innovative technological system}, journal = {Path of Science}, volume = {4}, year = {2018}, month = {Jul-08-2020}, pages = {2024 - 2030}, doi = {10.22178/pos10.22178/pos.37-6}, author = {Sopilnyk, Lyubomyr and Shevchuk, Andriy and Kopytko, Vasyl} } @article {2018, title = {DEFINITION, APPLICATION AND INFLUENCE OF ARTI FICIAL INTELLIGENCE ON DESIGN INDUSTRIES}, journal = {Landscape Architecture Frontiers}, volume = {6}, year = {2018}, month = {Jan-01-2018}, pages = {56}, issn = {2095-5405}, doi = {10.15302/J-LAF-20180207}, author = {Linghao Cai and Ling Fan and Wenbo Lai and LONG, Ying and Peng Wang and Xiangyang Xin} } @article {2018, title = {Developing robots: The need for an ethical framework}, journal = {European View}, volume = {17}, year = {2018}, month = {Aug-04-2019}, pages = {37 - 43}, issn = {1781-6858}, doi = {10.1177/1781685818761016}, author = {Leveringhaus, Alex} } @article {2018, title = {The discourse approach to boundary identification and corpus construction for theory review articles}, journal = {Journal of the Association for Information Systems}, year = {2018}, keywords = {article identification, boundary identification, citation search, keyword search, literature review, machine learning, research review, review article}, url = {https://www.researchgate.net/publication/325215971_Understanding_the_Elephant_The_Discourse_Approach_to_Boundary_Identification_and_Corpus_Construction_for_Theory_Review_Articles}, author = {Kai R. Larsen and Dirik S. Hovorka and Alan R. Dennis and Jevin D. West} } @article {2018, title = {Embracing the new world of work}, year = {2018}, url = {https://sfmagazine.com/post-entry/june-2018-embracing-the-new-world-of-work/}, author = {John M. Lewin} } @article {2018, title = {foo.castr: visualising the future AI workforce}, journal = {Big Data Analytics}, volume = {3}, year = {2018}, month = {Jan-12-2018}, doi = {10.1186/s41044-018-0034-z}, author = {Amador Diaz Lopez, Julio and Molina-Solana, Miguel and Kennedy, Mark T.} } @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 = {The Future of Work: The Trustless, by Ken Liu}, year = {2018}, url = {https://www.wired.com/story/future-of-work-trustless-ken-liu/}, author = {Ken Liu} } @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 = {Human and smart machine co-learning with brain computer interface}, journal = {IEEE SMC Magazine}, volume = {4}, year = {2018}, keywords = {human and machine inttelligence}, url = {https://arxiv.org/abs/1802.06521}, author = {Chang - Shing Lee and Mei - Hui Wang and Li - Wei Ko and Naoyuki Kubota and Lu - An Lin and Shinya Kitaoka and Yu - Te Wang and Shun - Feng Su} } @conference {2018, title = {Image Recognition of Disease-Carrying Insects: A System for Combating Infectious Diseases Using Image Classification Techniques and Citizen Science}, booktitle = {Hawaii International Conference on System SciencesProceedings of the 51st Hawaii International Conference on System Sciences}, year = {2018}, publisher = {Hawaii International Conference on System Sciences}, organization = {Hawaii International Conference on System Sciences}, doi = {10.24251/HICSS.2018.00010.24251/HICSS.2018.359}, url = {http://hdl.handle.net/10125/49887http://hdl.handle.net/10125/50247}, author = {Munoz, J. Pablo and Boger, Rebecca and Dexter, Scott and Low, Russanne and Li, Justin} } @book {2018, title = {Machine Learning for Ecology and Sustainable Natural Resource ManagementUse of Machine Learning (ML) for Predicting and Analyzing Ecological and {\textquoteleft}Presence Only{\textquoteright} Data: An Overview of Applications and a Good Outlook}, year = {2018}, pages = {27 - 61}, publisher = {Springer International Publishing}, organization = {Springer International Publishing}, address = {Cham}, isbn = {978-3-319-96976-3}, doi = {10.1007/978-3-319-96978-7_2}, author = {Huettmann, Falk and Craig, Erica H. and Herrick, Keiko A. and Baltensperger, Andrew P. and Grant Humphries and Lieske, David J. and Miller, Katharine and Mullet, Timothy C. and Oppel, Steffen and Resendiz, Cynthia and Rutzen, Imme and Schmid, Moritz S. and Suwal, Madan K. and Young, Brian D.}, editor = {Grant Humphries and Magness, Dawn R. and Huettmann, Falk} } @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 = {Medicine and the rise of the robots: a qualitative review of recent advances of artificial intelligence in health}, journal = {BMJ Leader}, volume = {2}, year = {2018}, month = {Apr-06-2020}, pages = {59 - 63}, doi = {10.1136/leader-2018-000071}, author = {Loh, Erwin} } @article {2018, title = {Occupational Classifications With A Machine Learning Approach}, year = {2018}, keywords = {administrative data, machine learning, occupational classifications, transaction data, UMETRICS}, url = {https://www.iza.org/publications/dp/11738/occupational-classifications-a-machine-learning-approach}, author = {Akina Ikudo and Julia Lane and Joseph Staudt and Bruce A. Weinberg} } @article {aroyo2018reports, title = {Reports of the Workshops Held at the Sixth AAAI Conference on Human Computation and Crowdsourcing}, journal = {AI Magazine}, volume = {39}, year = {2018}, pages = {57{\textendash}63}, author = {Aroyo, Lora and Dumitrache, Anca and Jeffrey V Nickerson and Lease, Matthew and Michelucci, Pietro} } @article {2018, title = {Skill shift automation and the future of the workforce}, year = {2018}, month = {05/2018}, url = {https://www.mckinsey.com/featured-insights/future-of-work/skill-shift-automation-and-the-future-of-the-workforce}, author = {Jaccques Bughin and Eric Hazan and Susan Lund and Peter Dahlstrom and Anna Wiesinger and Amresh Subramaniam} } @article {2018, title = {Sustainable skills for the world of work in the digital age}, journal = {Systems Research and Behavioral Science}, volume = {35}, year = {2018}, month = {Jan-07-2018}, pages = {399 - 405}, doi = {10.1002/sres.v35.410.1002/sres.2540}, author = {Sousa, Maria Jos{\'e} and Wilks, Daniela}, editor = {Laszlo, Alexander} } @article {2018, title = {Is There a Smarter Path to Artificial Intelligence? Some Experts Hope So}, journal = {The NewYork Times}, year = {2018}, url = {https://www.nytimes.com/2018/06/20/technology/deep-learning-artificial-intelligence.html}, author = {Steve Lohr} } @article {2018, title = {This time it might be different: Analysis of the impact of digitalization on the labour market}, journal = {European Scientific Journal ESJ}, volume = {14}, year = {2018}, month = {Jul-12-2020}, issn = {18577881}, doi = {10.19044/esj.2018.v14n36p68}, author = {Lovergine, Saverio and Pellero, Alberto} } @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 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 {2017, title = {Automation, computerisation and future employment in Singapore}, journal = {Journal of Southeast Asian Economies}, volume = {34}, year = {2017}, keywords = {economics of automation}, url = {https://mpra.ub.uni-muenchen.de/79961/}, author = {King Fuei Lee} } @proceedings {2017, title = {Automation of a Business Process Using Robotic Process Automation (RPA): A Case Study}, volume = {742}, year = {2017}, pages = {65 - 71}, publisher = {Springer International Publishing}, address = {Cham}, isbn = {978-3-319-66962-5}, issn = {1865-0929}, doi = {10.1007/978-3-319-66963-2_7}, author = {Aguirre, Santiago and Rodriguez, Alejandro}, editor = {Figueroa-Garc{\'\i}a, Juan Carlos and L{\'o}pez-Santana, Eduyn Ramiro and Villa-Ram{\'\i}rez, Jos{\'e} Luis and Ferro-Escobar, Roberto} } @book {2017, title = {Big Data in Organizations and the Role of Human Resource Management}, year = {2017}, url = {https://www.jstor.org/stable/j.ctv9hj9z6.1}, author = {Peter Lang} } @proceedings {9999, title = {Blending machine and human learning processes}, year = {2017}, abstract = {

Citizen science projects rely on contributions from volunteers to achieve their scientific goals and so face a dilemma: providing volunteers with explicit training might increase the quality of contributions, but at the cost of losing the work done by newcomers during the training period, which for many is the only work they will contribute to the project. Based on research in cognitive science on how humans learn to classify images, we have designed an approach to use machine learning to guide the presentation of tasks to newcomers that help them more quickly learn how to do the image classification task while still contributing to the work of the project. A Bayesian model for tracking this learning is presented.

}, doi = {10.24251/HICSS.2017.009}, url = {http://hdl.handle.net/10125/41159}, attachments = {https://waim.network/sites/crowston.syr.edu/files/training\%20v3\%20to\%20share_0.pdf}, author = {Kevin Crowston and Carsten {\O}sterlund and Lee, Tae Kyoung} } @proceedings {2017, title = {Chatbots as assistants, an architectural framework}, year = {2017}, url = {https://dl.acm.org/citation.cfm?id=3172805}, author = {Adam Di Prospera and Nojan norouzi and Morios Fokaefs and Marin Litoiu} } @conference {2017, title = {Data tracking in search of workflows}, booktitle = {the 2017 ACM ConferenceProceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing - CSCW {\textquoteright}17}, year = {2017}, pages = {2153 - 2165}, publisher = {ACM Press}, organization = {ACM Press}, address = {Portland, Oregon, USANew York, New York, USA}, isbn = {9781450343350}, doi = {10.1145/2998181.2998296}, author = {Holten M{\o}ller, Naja L. and Bj{\o}rn, Pernille and Villumsen, Jonas Christoffer and Hancock, Tine C. Hansen and Aritake, Toshimitsu and Tani, Shigeyuki} } @article {2017, title = {Employment, inequality and ethics in the digital age}, journal = {The IPPR Commission on Economic Justice}, year = {2017}, month = {12/2017}, url = {https://www.ippr.org/publications/managing-automation}, author = {Mathew Lawrence and Carys Roberts and Loren King} } @conference {RN30645, title = {Examining crowd work and gig work through the historical lens of piecework}, booktitle = {Proceedings of the CHI Conference on Human Factors in Computing Systems}, year = {2017}, pages = {4599-4616}, publisher = {ACM}, organization = {ACM}, type = {Conference Proceedings}, isbn = {1450346553}, author = {Alkhatib, Ali and Michael S. Bernstein and Levi, Margaret} } @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 = {How fortune 500 firms are adopting online freelancing platforms}, year = {2017}, institution = {University of Oxford}, url = {https://www.oii.ox.ac.uk/publications/platform-sourcing.pdf}, author = {Greetje F. Corporaal and Vili Lehdonvirta} } @article {2017, title = {Impact of robotics, RPA and AI on the insurance industry }, journal = {The Journal of Financial Perspectives: Insurance}, year = {2017}, url = {https://www.ey.com/Publication/vwLUAssets/ey-impact-of-robotics-rpa-and-ai-on-the-insurance-industry-challenges-and-opportunities/\%24File/ey-impact-of-robotics-rpa-and-ai-on-the-insurance-industry-challenges-and-opportunities.pdf}, author = {Chris Lamberton and Damiano Brigo and Dave Hoy} } @article {2017, title = {Jobs lost, jobs gained: Workforce transactions in a time of automation}, year = {2017}, keywords = {consulting reports}, url = {https://www.mckinsey.com/~/media/mckinsey/featured\%20insights/future\%20of\%20organizations/what\%20the\%20future\%20of\%20work\%20will\%20mean\%20for\%20jobs\%20skills\%20and\%20wages/mgi-jobs-lost-jobs-gained-report-december-6-2017.ashx}, author = {James Manyika and Susan Lund and Michael Chui and Jonathan Woetzel and Ryan Ko and Saurabh Sanghvi and Parul Batra and Jacques Bughin} } @article {2017, title = {Of robots, Artificial Intelligence, and work}, journal = {Academy of Management Perspectives}, volume = {31}, year = {2017}, month = {Jan-11-2017}, pages = {253 - 255}, issn = {1558-9080}, doi = {10.5465/amp.2017.0199}, author = {Phan, Phillip and Wright, Michael and Lee, Soo-Hoon} } @conference {Malone:2017:PPB:2998181.2998343, title = {Putting the Pieces Back Together Again: Contest Webs for Large-Scale Problem Solving}, booktitle = {Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing}, year = {2017}, pages = {1661{\textendash}1674}, publisher = {ACM}, organization = {ACM}, address = {New York, NY, USA}, keywords = {climate change, collective intelligence, contest webs, contests, Coordination, incentives, knowledge reuse}, isbn = {978-1-4503-4335-0}, doi = {10.1145/2998181.2998343}, url = {http://doi.acm.org/10.1145/2998181.2998343}, author = {Malone, Thomas W. and Jeffrey V Nickerson and Laubacher, Robert J. and Fisher, Laur Hesse and de Boer, Patrick and Han, Yue and Towne, W. Ben} } @article {2017, title = {The rise of technological unemployment and its implications on the future macroeconomic landscape}, journal = {Futures}, volume = {87}, year = {2017}, month = {Jan-03-2017}, pages = {1 - 9}, issn = {00163287}, doi = {10.1016/j.futures.2017.01.003}, author = {Kim, Young Joon and Kim, Kyungsoo and Lee, SuKyoung} } @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 = {Stewardship in the age of algorithms}, journal = {Peer-reviewed journal on the internet}, year = {2017}, url = {https://firstmonday.org/article/view/8097/6583}, author = {Clifford Lynch} } @article {2017, title = {Understanding human-machine networks}, journal = {ACM Computing Surveys}, volume = {50}, year = {2017}, month = {Jan-04-2018}, pages = {1 - 35}, issn = {03600300}, doi = {10.1145/3039868}, author = {Tsvetkova, Milena and Yasseri, Taha and Meyer, Eric T. and Pickering, J. Brian and Engen, Vegard and Walland, Paul and L{\"u}ders, Marika and F{\o}lstad, Asbj{\o}rn and Bravos, George} } @article {2016, title = {Citizen science on a smartphone: Participants{\textquoteright} motivations and learning}, journal = {Public Understanding of Science}, volume = {25}, year = {2016}, month = {Mar-01-2017}, pages = {45 - 60}, issn = {0963-6625}, doi = {10.1177/0963662515602406}, author = {Land-Zandstra, Anne M. and Devilee, Jeroen L. A. and Snik, Frans and Buurmeijer, Franka and van den Broek, Jos M.} } @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} } @book {2015, title = {Deep Learning Tutorial}, series = {Release 0.1}, year = {2015}, url = {http://deeplearning.net/tutorial/deeplearning.pdf}, author = {LISA lab, University of Montreal} } @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 {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} } @article {2013, title = {The convergence of engineering and the life sciences}, journal = {National Academy of Engineering}, volume = {43}, year = {2013}, month = {10/2013}, url = {https://www.nae.edu/88364/The-Convergence-of-Engineering-and-the-Life-Sciences}, author = {Pjilip A. Sharp and Robert Langer} } @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 rise and fall of interdisciplinary research: The case of open source innovation}, journal = {Research Policy}, volume = {42}, year = {2013}, month = {Jan-06-2013}, pages = {1138 - 1151}, issn = {00487333}, doi = {10.1016/j.respol.2013.01.010}, author = {Raasch, Christina and Lee, Viktor and Spaeth, Sebastian and Herstatt, Cornelius} } @conference {2008, title = {Context-linked virtual assistants for distributed teams}, booktitle = {the ACM 2008 conferenceProceedings of the ACM 2008 conference on Computer supported cooperative work - CSCW {\textquoteright}08}, year = {2008}, pages = {361}, publisher = {ACM Press}, organization = {ACM Press}, address = {San Diego, CA, USANew York, New York, USA}, isbn = {9781605580074}, doi = {10.1145/1460563.1460623}, author = {Poon, Sarah S. and Thomas, Rollin C. and Aragon, Cecilia R. and Lee, Brian} } @conference {RN30259, title = {Context-linked virtual assistants for distributed teams: an astrophysics case study}, booktitle = {Proceedings of the ACM Conference on Computer Supported Cooperative Work}, year = {2008}, pages = {361{\textendash}370}, type = {Conference Proceedings}, isbn = {1605580074}, author = {Poon, Sarah S and Thomas, Rollin C and Cecilia Aragon and Lee, Brian} } @article {RN30479, title = {The skill content of recent technological change: An empirical exploration}, journal = {Quarterly Journal of Economics}, volume = {118}, number = {4}, year = {2003}, pages = {1279{\textendash}1333}, type = {Journal Article}, issn = {0033-5533}, doi = {10.1162/003355303322552801}, url = {http://apps.isiknowledge.com/InboundService.do?Func=Frame\&product=WOS\&action=retrieve\&SrcApp=EndNote\&Init=Yes\&SrcAuth=ResearchSoft\&mode=FullRecord\&UT=WOS:000186624900004}, author = {Autor, D. H. and Levy, F. and Murnane, R. J.} } @article {1995, title = {Application of Machine Learning and Rule Induction}, year = {1995}, url = {https://dl.acm.org/citation.cfm?id=219768}, author = {Pat Langley} }