@proceedings {wang2024reelframer,
	title = {ReelFramer: Human-AI Co-Creation for News-to-Video Translation},
	year = {2024},
	address = {Honolulu, Hawai{\textquoteright}i},
	abstract = {<p>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.</p>},
	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}
}
@proceedings {petridis2023anglekindling,
	title = {AngleKindling: Supporting Journalistic Angle Ideation with Large Language Models},
	year = {2023},
	doi = {10.1145/3544548.3580907},
	url = {https://savvaspetridis.github.io/papers/anglekindling.pdf},
	author = {Petridis, Savvas and Diakopoulos, Nicholas and Crowston, Kevin and Hansen, Mark and Henderson, Keren and Jastrzebski, Stan and Nickerson, Jefrey V and Chilton, Lydia B}
}
@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 {Kassens-Noor2020,
	title = {Cities of the Future? The Potential Impact of Artificial Intelligence},
	journal = {AI},
	volume = {1},
	number = {2},
	year = {2020},
	pages = {192{\textendash}197},
	abstract = {Artificial intelligence (AI), like many revolutionary technologies in human history, will have a profound impact on societies. From this viewpoint, we analyze the combined effects of AI to raise important questions about the future form and function of cities. Combining knowledge from computer science, urban planning, and economics while reflecting on academic and business perspectives, we propose that the future of cities is far from being a determined one and cities may evolve into ghost towns if the deployment of AI is not carefully controlled. This viewpoint presents a fundamentally different argument, because it expresses a real concern over the future of cities in contrast to the many publications who exclusively assume city populations will increase predicated on the neoliberal urban growth paradigm that has for centuries attracted humans to cities in search of work.},
	keywords = {artificial intelligence, autonomous vehicle, future, smart cities, work},
	issn = {2673-2688},
	doi = {10.3390/ai1020012},
	author = {Kassens-Noor, Eva and Hintze, Arend}
}
@conference {Martnez-Plumed2020,
	title = {Does AI qualify for the job? A bidirectional model mapping labour and AI intensities},
	booktitle = {AIES 2020 - Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society},
	year = {2020},
	pages = {94{\textendash}100},
	abstract = {In this paper we present a setting for examining the relation between the distribution of research intensity in AI research and the relevance for a range of work tasks (and occupations) in current and simulated scenarios. We perform a mapping between labour and AI using a set of cognitive abilities as an intermediate layer. This setting favours a two-way interpretation to analyse (1) what impact current or simulated AI research activity has or would have on labour-related tasks and occupations, and (2) what areas of AI research activity would be responsible for a desired or undesired effect on specific labour tasks and occupations. Concretely, in our analysis we map 59 generic labour-related tasks from several worker surveys and databases to 14 cognitive abilities from the cognitive science literature, and these to a comprehensive list of 328 AI benchmarks used to evaluate progress in AI techniques. We provide this model and its implementation as a tool for simulations. We also show the effectiveness of our setting with some illustrative examples.},
	keywords = {AI benchmarks, AI impact, AI intensity, Labour market, Simulation, tasks},
	isbn = {9781450371100},
	doi = {10.1145/3375627.3375831},
	author = {Mart{\textquoteright}nez-Plumed, Fernando and Tolan, Song{\textquoteright}l and Pesole, Annarosa and Hern{\textquoteright}ndez-Orallo, Jos{\'e} and Fern{\textquoteright}ndez-Mac{\textquoteright}as, Enrique and G{\textquoteright}mez, Emilia}
}
@article {Huang2020,
	title = {Engaged to a Robot? The Role of AI in Service},
	journal = {Journal of Service Research},
	year = {2020},
	abstract = {This article develops a strategic framework for using artificial intelligence (AI) to engage customers for different service benefits. This framework lays out guidelines of how to use different AIs to engage customers based on considerations of nature of service task, service offering, service strategy, and service process. AI develops from mechanical, to thinking, and to feeling. As AI advances to a higher intelligence level, more human service employees and human intelligence (HI) at the intelligence levels lower than that level should be used less. Thus, at the current level of AI development, mechanical service should be performed mostly by mechanical AI, thinking service by both thinking AI and HI, and feeling service mostly by HI. Mechanical AI should be used for standardization when service is routine and transactional, for cost leadership, and mostly at the service delivery stage. Thinking AI should be used for personalization when service is data-rich and utilitarian, for quality leadership, and mostly at the service creation stage. Feeling AI should be used for relationalization when service is relational and high touch, for relationship leadership, and mostly at the service interaction stage. We illustrate various AI applications for the three major AI benefits, providing managerial guidelines for service providers to leverage the advantages of AI as well as future research implications for service researchers to investigate AI in service from modeling, consumer, and policy perspectives.},
	keywords = {artificial intelligence, augmentation, automation, engagement, feeling AI, human intelligence, mechanical AI, personalization, relationalization, replacement, robots, service process, service strategy, standardization, thinking AI},
	issn = {15527379},
	doi = {10.1177/1094670520902266},
	author = {Huang, Ming Hui and Rust, Roland T}
}
@article {Hacker2020,
	title = {Explainable AI under contract and tort law: legal incentives and technical challenges},
	journal = {Artificial Intelligence and Law},
	number = {0123456789},
	year = {2020},
	publisher = {Springer Netherlands},
	abstract = {This paper shows that the law, in subtle ways, may set hitherto unrecognized incentives for the adoption of explainable machine learning applications. In doing so, we make two novel contributions. First, on the legal side, we show that to avoid liability, professional actors, such as doctors and managers, may soon be legally compelled to use explainable ML models. We argue that the importance of explainability reaches far beyond data protection law, and crucially influences questions of contractual and tort liability for the use of ML models. To this effect, we conduct two legal case studies, in medical and corporate merger applications of ML. As a second contribution, we discuss the (legally required) trade-off between accuracy and explainability and demonstrate the effect in a technical case study in the context of spam classification.},
	keywords = {Contract law, Corporate takeovers, Explainability, Explainability-accuracy trade-off, Explainable AI, Interpretable machine learning, Medical malpractice, Tort law},
	isbn = {0123456789},
	issn = {15728382},
	doi = {10.1007/s10506-020-09260-6},
	url = {https://doi.org/10.1007/s10506-020-09260-6},
	author = {Hacker, Philipp and Krestel, Ralf and Grundmann, Stefan and Naumann, Felix}
}
@proceedings {2018,
	title = {The Genie in the Bottle: Different Stakeholders, Different Interpretations of Machine Learning},
	year = {2020},
	type = {Working paper},
	address = {Wailea, HI},
	abstract = {<p>Machine learning (ML) constitute an algorithmic phenomenon with some distinctive characteristics (e.g., being trained, probabilistic). Our understanding of such systems is limited when it comes to how these unique characteristics play out in organizational settings and what challenges different groups of users will face in working with them. We explore how people developing or using an ML system come to understand its capabilities and challenges. We draw on the social construction of technology tradition to frame our analysis of interviews and discussion board posts involving designers and users of a ML-supported citizen-science crowdsourcing project named Gravity Spy. Our findings reveal some of the challenges facing different relevant social groups. We find that groups with less interaction with the technology have their understanding. We find that the type of understandings achieved by groups having less interaction with the technology is shaped by outside influences rather than the specifics of the system and its role in the project. Notable, some users mistake human input for ML input. This initial understanding of how different participants understand and engage with ML point to challenges that need to be overcome to help participants deal with the opaque position ML often hold in a work system.</p>},
	doi = {10.24251/HICSS.2020.719 },
	attachments = {https://waim.network/sites/crowston.syr.edu/files/Social_Construction_of_ML_in_GS_HICCS2020.pdf},
	author = {Mahboobeh Harandi and Kevin Crowston and Corey Jackson and Carsten {\O}sterlund}
}
@article {2020,
	title = {How the FDA regulates AI},
	journal = {Academic Radiology},
	volume = {27},
	year = {2020},
	month = {Jan-01-2020},
	pages = {58 - 61},
	issn = {10766332},
	doi = {10.1016/j.acra.2019.09.017},
	author = {Harvey, H. Benjamin and Gowda, Vrushab}
}
@article {B{\ae}r{\o}e2020,
	title = {How to achieve trustworthy artificial intelligence for health},
	journal = {Bulletin of the World Health Organization},
	volume = {98},
	number = {4},
	year = {2020},
	pages = {257{\textendash}262},
	abstract = {Artificial intelligence holds great promise in terms of beneficial, accurate and effective preventive and curative interventions. At the same time, there is also awareness of potential risks and harm that may be caused by unregulated developments of artificial intelligence. Guiding principles are being developed around the world to foster trustworthy development and application of artificial intelligence systems. These guidelines can support developers and governing authorities when making decisions about the use of artificial intelligence. The HighLevel Expert Group on Artificial Intelligence set up by the European Commission launched the report Ethical guidelines for trustworthy artificial intelligence in 2019. The report aims to contribute to reflections and the discussion on the ethics of artificial intelligence technologies also beyond the countries of the European Union (EU). In this paper, we use the global health sector as a case and argue that the EU{\textquoteright}s guidance leaves too much room for local, contextualized discretion for it to foster trustworthy artificial intelligence globally. We point to the urgency of shared globalized efforts to safeguard against the potential harms of artificial intelligence technologies in health care.},
	issn = {15640604},
	doi = {10.2471/BLT.19.237289},
	author = {B{\ae}r{\o}e, Kristine and Miyata-Sturm, Ainar and Henden, Edmund}
}
@article {Petersen2020,
	title = {The Role of Discretion in the Age of Automation},
	journal = {Computer Supported Cooperative Work: CSCW: An International Journal},
	volume = {29},
	number = {3},
	year = {2020},
	pages = {303{\textendash}333},
	abstract = {This paper examines the nature of discretion in social work in order to debunk myths dominating prevalent debates on digitisation and automation in the public sector. Social workers have traditionally used their discretion widely and with great autonomy, but discretion has increasingly come under pressure for its apparent subjectivity and randomness. In Denmark, our case in point, the government recently planned to standardise laws to limit or remove discretion where possible in order for automation of case management to gain a foothold. Recent studies have focused on discretion in the public sector, but few have examined it explicitly and as part of real cases. As a consequence, they often leave the myths about discretion unchallenged. Inspired by the literature on discretion and CSCW research on rules in action, this study reports on an empirical investigation of discretion in child protection services in Denmark. The results of our analysis provide a new understanding of discretion as a cooperative endeavour, based on consultation and skill, rather than an arbitrary or idiosyncratic choice. In this manner, our study contradicts the myth of discretion inherent in the automation agenda. Correspondingly, we ask for attention to be given to systems that integrate discretion with technology rather than seek to undermine it directly or get around it surreptitiously. In this age of automation, this is not only an important but also an urgent task for CSCW researchers to fulfil.},
	keywords = {Administrative work, automation, Casework, Decision-Making, Digital-ready legislation, Digitisation, Discretion, Rules in action, Social work},
	issn = {15737551},
	doi = {10.1007/s10606-020-09371-3},
	author = {Petersen, Anette C.M. and Christensen, Lars Rune and Hildebrandt, Thomas T.}
}
@article {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-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 = {As Walmart turns to robots, it{\textquoteright}s the human workers who feel like machines},
	year = {2019},
	month = {06/2019},
	type = {Technology},
	url = {https://www.washingtonpost.com/technology/2019/06/06/walmart-turns-robots-its-human-workers-who-feel-like-machines/},
	author = {Drew Harwell}
}
@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 = {Bots Coordinating Work in Open Source Software Projects},
	journal = {Computer},
	volume = {52},
	year = {2019},
	month = {Jan-09-2019},
	pages = {52 - 60},
	issn = {0018-9162},
	doi = {10.1109/MC.2018.2885970},
	author = {Hukal, Philipp and Berente, Nicholas and Germonprez, Matt and Schecter, Aaron}
}
@article {2019,
	title = {A Brief History of Artificial Intelligence: On the Past, Present, and Future of Artificial Intelligence},
	journal = {California Management Review},
	volume = {61},
	year = {2019},
	month = {Sep-08-2019},
	pages = {5 - 14},
	issn = {0008-1256},
	doi = {10.1177/0008125619864925},
	author = {Haenlein, Michael and Kaplan, Andreas}
}
@article {2019,
	title = {Comparing artificial intelligence algorithms to 157 German dermatologists: the melanoma classification benchmark},
	journal = {European Journal of Cancer},
	volume = {111},
	year = {2019},
	month = {Jan-04-2019},
	pages = {30 - 37},
	issn = {09598049},
	doi = {10.1016/j.ejca.2018.12.016},
	author = {Brinker, Titus J. and Hekler, Achim and Hauschild, Axel and Berking, Carola and Schilling, Bastian and Alexander Enk and Haferkamp, Sebastian and Karoglan, Ante and von Kalle, Christof and Weichenthal, Michael and Sattler, Elke and Schadendorf, Dirk and Gaiser, Maria R. and Klode, Joachim and Jochen Sven Utikal}
}
@conference {2019,
	title = {Consider the human work experience when integrating robotics in the workplace},
	booktitle = {2019 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI)2019 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI)},
	year = {2019},
	pages = {75 - 84},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Daegu, Korea (South)},
	doi = {10.1109/HRI.2019.8673139},
	url = {https://ieeexplore.ieee.org/document/8673139/http://xplorestaging.ieee.org/ielx7/8666012/8673065/08673139.pdf?arnumber=8673139},
	author = {Welfare, Katherine S. and Hallowell, Matthew R. and Shah, Julie A. and Riek, Laurel D.}
}
@article {2019,
	title = {A convolutional neural network trained with dermoscopic images performed on par with 145 dermatologists in a clinical melanoma image classification task},
	journal = {European Journal of Cancer},
	volume = {111},
	year = {2019},
	month = {Jan-04-2019},
	pages = {148 - 154},
	issn = {09598049},
	doi = {10.1016/j.ejca.2019.02.005},
	author = {Brinker, Titus J. and Hekler, Achim and Alexander Enk and Klode, Joachim and Hauschild, Axel and Berking, Carola and Schilling, Bastian and Haferkamp, Sebastian and Schadendorf, Dirk and Fr{\"o}hling, Stefan and Jochen Sven Utikal and von Kalle, Christof and Ludwig-Peitsch, Wiebke and Sirokay, Judith and Heinzerling, Lucie and Albrecht, Magarete and Baratella, Katharina and Bischof, Lena and Chorti, Eleftheria and Dith, Anna and Drusio, Christina and Giese, Nina and Gratsias, Emmanouil and Griewank, Klaus and Hallasch, Sandra and Hanhart, Zdenka and Herz, Saskia and Hohaus, Katja and Jansen, Philipp and Jockenh{\"o}fer, Finja and Kanaki, Theodora and Knispel, Sarah and Leonhard, Katja and Martaki, Anna and Matei, Liliana and Matull, Johanna and Olischewski, Alexandra and Petri, Maximilian and Placke, Jan-Malte and Raub, Simon and Salva, Katrin and Schlott, Swantje and Sody, Elsa and Steingrube, Nadine and Stoffels, Ingo and Ugurel, Selma and Sondermann, Wiebke and Zaremba, Anne and Gebhardt, Christoffer and Booken, Nina and Christolouka, Maria and Buder-Bakhaya, Kristina and Bokor-Billmann, Therezia and Alexander Enk and Gholam, Patrick and H{\"a}n{\ss}le, Holger and Salzmann, Martin and Sch{\"a}fer, Sarah and Sch{\"a}kel, Knut and Schank, Timo and Bohne, Ann-Sophie and Deffaa, Sophia and Drerup, Katharina and Egberts, Friederike and Erkens, Anna-Sophie and Ewald, Benjamin and Falkvoll, Sandra and Gerdes, Sascha and Harde, Viola and Hauschild, Axel and Jost, Marion and Kosova, Katja and Messinger, Laetitia and Metzner, Malte and Morrison, Kirsten and Motamedi, Rogina and Pinczker, Anja and Rosenthal, Anne and Scheller, Natalie and Schwarz, Thomas and St{\"o}lzl, Dora and Thielking, Federieke and Tomaschewski, Elena and Wehkamp, Ulrike and Weichenthal, Michael and Wiedow, Oliver and B{\"a}r, Claudia Maria and Bender-S{\"a}belkampf, Sophia and Horbr{\"u}gger, Marc and Karoglan, Ante and Kraas, Luise and Faulhaber, J{\"o}rg and Geraud, Cyrill and Guo, Ze and Koch, Philipp and Linke, Miriam and Maurier, Nolwenn and M{\"u}ller, Verena and Thomas, Benjamin and Jochen Sven Utikal and Alamri, Ali Saeed M. and Baczako, Andrea and Berking, Carola and Betke, Matthias and Haas, Carolin and Hartmann, Daniela and Heppt, Markus V. and Kilian, Katharina and Krammer, Sebastian and Lapczynski, Natalie Lidia and Mastnik, Sebastian and Nasifoglu, Suzan and Ruini, Cristel and Sattler, Elke and Schlaak, Max and Wolff, Hans and Achatz, Birgit and Bergbreiter, Astrid and Drexler, Konstantin and Ettinger, Monika and Haferkamp, Sebastian and Halupczok, Anna and Hegemann, Marie and Dinauer, Verena and Maagk, Maria and Mickler, Marion and Philipp, Biance and Wilm, Anna and Wittmann, Constanze and Gesierich, Anja and Glutsch, Valerie and Kahlert, Katrin and Kerstan, Andreas and Schilling, Bastian and Schr{\"u}fer, Philipp}
}
@article {2019,
	title = {Deep learning outperformed 136 of 157 dermatologists in a head-to-head dermoscopic melanoma image classification task},
	journal = {European Journal of Cancer},
	volume = {113},
	year = {2019},
	month = {Jan-05-2019},
	pages = {47 - 54},
	issn = {09598049},
	doi = {10.1016/j.ejca.2019.04.001},
	author = {Brinker, Titus J. and Hekler, Achim and Alexander Enk and Klode, Joachim and Hauschild, Axel and Berking, Carola and Schilling, Bastian and Haferkamp, Sebastian and Schadendorf, Dirk and Holland-Letz, Tim and Jochen Sven Utikal and von Kalle, Christof and Ludwig-Peitsch, Wiebke and Sirokay, Judith and Heinzerling, Lucie and Albrecht, Magarete and Baratella, Katharina and Bischof, Lena and Chorti, Eleftheria and Dith, Anna and Drusio, Christina and Giese, Nina and Gratsias, Emmanouil and Griewank, Klaus and Hallasch, Sandra and Hanhart, Zdenka and Herz, Saskia and Hohaus, Katja and Jansen, Philipp and Jockenh{\"o}fer, Finja and Kanaki, Theodora and Knispel, Sarah and Leonhard, Katja and Martaki, Anna and Matei, Liliana and Matull, Johanna and Olischewski, Alexandra and Petri, Maximilian and Placke, Jan-Malte and Raub, Simon and Salva, Katrin and Schlott, Swantje and Sody, Elsa and Steingrube, Nadine and Stoffels, Ingo and Ugurel, Selma and Zaremba, Anne and Gebhardt, Christoffer and Booken, Nina and Christolouka, Maria and Buder-Bakhaya, Kristina and Bokor-Billmann, Therezia and Alexander Enk and Gholam, Patrick and H{\"a}n{\ss}le, Holger and Salzmann, Martin and Sch{\"a}fer, Sarah and Sch{\"a}kel, Knut and Schank, Timo and Bohne, Ann-Sophie and Deffaa, Sophia and Drerup, Katharina and Egberts, Friederike and Erkens, Anna-Sophie and Ewald, Benjamin and Falkvoll, Sandra and Gerdes, Sascha and Harde, Viola and Hauschild, Axel and Jost, Marion and Kosova, Katja and Messinger, Laetitia and Metzner, Malte and Morrison, Kirsten and Motamedi, Rogina and Pinczker, Anja and Rosenthal, Anne and Scheller, Natalie and Schwarz, Thomas and St{\"o}lzl, Dora and Thielking, Federieke and Tomaschewski, Elena and Wehkamp, Ulrike and Weichenthal, Michael and Wiedow, Oliver and B{\"a}r, Claudia Maria and Bender-S{\"a}belkampf, Sophia and Horbr{\"u}gger, Marc and Karoglan, Ante and Kraas, Luise and Faulhaber, J{\"o}rg and Geraud, Cyrill and Guo, Ze and Koch, Philipp and Linke, Miriam and Maurier, Nolwenn and M{\"u}ller, Verena and Thomas, Benjamin and Jochen Sven Utikal and Alamri, Ali Saeed M. and Baczako, Andrea and Berking, Carola and Betke, Matthias and Haas, Carolin and Hartmann, Daniela and Heppt, Markus V. and Kilian, Katharina and Krammer, Sebastian and Lapczynski, Natalie Lidia and Mastnik, Sebastian and Nasifoglu, Suzan and Ruini, Cristel and Sattler, Elke and Schlaak, Max and Wolff, Hans and Achatz, Birgit and Bergbreiter, Astrid and Drexler, Konstantin and Ettinger, Monika and Haferkamp, Sebastian and Halupczok, Anna and Hegemann, Marie and Dinauer, Verena and Maagk, Maria and Mickler, Marion and Philipp, Biance and Wilm, Anna and Wittmann, Constanze and Gesierich, Anja and Glutsch, Valerie and Kahlert, Katrin and Kerstan, Andreas and Schilling, Bastian and Schr{\"u}fer, Philipp}
}
@book {2019,
	title = {Educating those most impacted by artificial intelligence},
	volume = {11626},
	year = {2019},
	pages = {344 - 349},
	publisher = {Springer International Publishing},
	organization = {Springer International Publishing},
	address = {Cham},
	isbn = {978-3-030-23206-1},
	issn = {0302-9743},
	doi = {10.1007/978-3-030-23207-8_63},
	author = {Gemmell, Laura and Wenham, Lucy and Hauert, Sabine},
	editor = {Isotani, Seiji and Mill{\'a}n, Eva and Ogan, Amy and Hastings, Peter and McLaren, Bruce and Luckin, Rose}
}
@book {2019,
	title = {The emergence of complexity},
	year = {2019},
	publisher = {Springer International Publishing},
	organization = {Springer International Publishing},
	address = {Cham},
	isbn = {978-3-030-31837-6},
	issn = {2366-1658},
	doi = {10.1007/978-3-030-31839-0},
	author = {Hager, Paul and Beckett, David}
}
@article {2019,
	title = {An Extensive Review on Recent Emerging Applications of Artificial Intelligence},
	journal = {Asia-pacific Journal of Convergent Research Interchange},
	volume = {5},
	year = {2019},
	month = {Jun-06-2021},
	pages = {79 - 88},
	issn = {25089080},
	doi = {10.21742/apjcri10.21742/apjcri.2019.0610.21742/apjcri.2019.06.09},
	url = {http://www.apjcri.org/papers/v5n2/9.pdf},
	author = {Harini, B}
}
@article {2019,
	title = {The future digital work force:  Robotic process automation (RPA)},
	journal = {Journal of Information Systems and Technology Management},
	volume = {16},
	year = {2019},
	month = {Apr-01-2019},
	doi = {10.4301/S1807-1775201916001},
	author = {Madakam, Somayya and M. Holmukhe, Rajesh and Kumar Jaiswal, Durgesh}
}
@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 = {The future of women at work},
	volume = {McKinsey Global Institute},
	year = {2019},
	month = {06/2019},
	keywords = {consulting reports},
	url = {https://www.mckinsey.com/~/media/mckinsey/featured\%20insights/gender\%20equality/the\%20future\%20of\%20women\%20at\%20work\%20transitions\%20in\%20the\%20age\%20of\%20automation/mgi-the-future-of-women-at-work-full-report-june\%202019.ashx},
	author = {Anu Madgavkar and James Manyika and Mekala Krishnan and Kweilin Ellingrud and Lareina Yee and Jonathan Woetzel and Michael Chui and Vivian Hunt and Sruti Balakrishnan}
}
@article {2019,
	title = {Future of work initiatives promise lots of noise and lots of activity, but to what end?},
	year = {2019},
	url = {https://sloanreview.mit.edu/article/reframing-the-future-of-work/},
	author = {Jeff Schwartz and John Hagel III and Maggie Wooll and Kelly Monahan}
}
@article {2019,
	title = {Getting ready for a post-work future},
	journal = {Foresight and STI Governance},
	volume = {13},
	year = {2019},
	month = {Jun-03-2021},
	pages = {19 - 30},
	doi = {10.17323/2500-2597.2019.1.19.30},
	author = {Hines, Andy}
}
@conference {2019,
	title = {How May I Help You? {\textendash} State of the Art and Open Research Questions for Chatbots at the Digital Workplace},
	booktitle = {Hawaii International Conference on System SciencesProceedings of the 52nd Hawaii International Conference on System Sciences},
	year = {2019},
	publisher = {Hawaii International Conference on System Sciences},
	organization = {Hawaii International Conference on System Sciences},
	isbn = {978-0-9981331-2-6},
	doi = {10.24251/HICSS.2019.013},
	author = {Meyer von Wolff, Raphael and Hobert, Sebastian and Schumann, Matthias}
}
@conference {2019,
	title = {Inferring work task automatability from AI expert evidence},
	booktitle = {the 2019 AAAI/ACM ConferenceProceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society  - AIES {\textquoteright}19},
	year = {2019},
	pages = {485 - 491},
	publisher = {ACM Press},
	organization = {ACM Press},
	address = {Honolulu, HI, USANew York, New York, USA},
	isbn = {9781450363242},
	doi = {10.1145/330661810.1145/3306618.3314247},
	author = {Duckworth, Paul and Graham, Logan and Osborne, Michael}
}
@inbook {2019,
	title = {Machine learning for clinical psychology and clinical neuroscience},
	booktitle = {researchgate.net},
	year = {2019},
	abstract = {A rapid growth in computational power and an increasing availability of large, publicly-accessible, multimodal datasets present new opportunities for psychology and neuroscience researchers to ask novel questions, and to approach old questions in novel ways. Studies of the personal characteristics, situation-specific factors, and sociocultural contexts that result in the onset, development, maintenance, and remission of psychopathology, are particularly well-suited to benefit from machine learning methods. However, introductory textbooks for machine learning rarely tailor their guidance to the needs of psychology and neuroscience researchers. Similarly, the traditional statistical training of clinical scientists often does not incorporate these approaches. This chapter acts as an introduction to machine learning for researchers in the fields of clinical psychology and clinical neuroscience. We discuss these methods, illustrated through real and hypothetical applications in the fields of clinical psychology and clinical neuroscience. We touch on study design, selecting appropriate techniques, how (and how not) to interpret results, and more, to aid researchers who are interested in applying machine learning methods to clinical science data.},
	url = {https://www.researchgate.net/publication/331000572_Machine_Learning_for_Clinical_Psychology_and_Clinical_Neuroscience},
	author = {Marc N. Countanche and Lauren S. Hallion}
}
@conference {2019,
	title = {Machine learning in Artificial Intelligence: Towards a common understanding},
	booktitle = {Hawaii International Conference on System SciencesProceedings of the 52nd Hawaii International Conference on System Sciences},
	year = {2019},
	publisher = {Hawaii International Conference on System Sciences},
	organization = {Hawaii International Conference on System Sciences},
	doi = {10.24251/HICSS.2019.630},
	author = {K{\"u}hl, Niklas and Goutier, Marc and Hirt, Robin and Satzger, Gerhard}
}
@article {2019,
	title = {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 = {A Review of the Social Impacts and Ethical Implications of Artificial Intelligence},
	year = {2019},
	publisher = {Global AI Ethics},
	keywords = {ethics},
	url = {https://arxiv.org/ftp/arxiv/papers/1907/1907.07892.pdf},
	author = {Alexa Hagerty and Igor Rubinov}
}
@article {2019,
	title = {Scaling up analogical innovation with crowds and AI},
	journal = {Proceedings of the National Academy of Sciences},
	volume = {116},
	year = {2019},
	pages = {1870-1877},
	issn = {0027-8424},
	doi = {10.1073/pnas.1807185116},
	author = {Kittur, Aniket and Yu, Lixiu and Hope, Tom and Chan, Joel and Lifshitz-Assaf, Hila and Gilon, Karni and Ng, Felicia and Kraut, Robert E. and Shahaf, Dafna}
}
@article {2019,
	title = {Towards an AI economy that works for all},
	year = {2019},
	month = {02/2019},
	keywords = {ethics},
	url = {https://www.keystoneresearch.org/sites/default/files/FOW_TowardAIEconomyForAllFinalEdit.pdf},
	author = {Stephen Herzenberg and John Alic}
}
@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 = {Accounting for the neglected dimensions of AI progress},
	journal = {data-efficient ML},
	year = {2018},
	url = {https://arxiv.org/abs/1806.00610},
	author = {Fernando Martine-Plumed and Shahar Avin and Miles Brundage and Allan Dafoe and Sean O hEigeartaigh and Jos{\'e} Hern{\'a}ndez-Orallo}
}
@article {2018,
	title = {Advances in the development of a cognitive user interface},
	journal = {MATEC Web of Conferences},
	volume = {161},
	year = {2018},
	month = {Jan-01-2018},
	pages = {01003},
	doi = {10.1051/matecconf/201816101003},
	url = {https://www.matec-conferences.org/10.1051/matecconf/201816101003https://www.matec-conferences.org/10.1051/matecconf/201816101003/pdf},
	author = {Jokisch, Oliver and Huber, Markus},
	editor = {Ronzhin, A. and Shishlakov, V.}
}
@article {2018,
	title = {AI Could Provide Moment-by-Moment Nursing for a Hospital{\textquoteright}s Sickest Patients},
	year = {2018},
	url = {https://globaltechnologies.ca/ai-could-provide-moment-by-moment-nursing-for-a-hospitals-sickest-patients/},
	author = {Behnood Gholami and Wassim M. Haddad and James M. Bailey}
}
@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}
}
@article {2018,
	title = {Artificial intelligence: Implications for social inflation and insurance},
	journal = {Risk Management and Insurance Review},
	volume = {21},
	year = {2018},
	month = {Jan-12-2018},
	pages = {373 - 387},
	doi = {10.1111/rmir.12111},
	author = {Kelley, Kevin H. and Fontanetta, Lisa M. and Heintzman, Mark and Pereira, Nikki}
}
@article {2018,
	title = {Artificial Intelligence in Service},
	journal = {Journal of Service Research},
	volume = {21},
	year = {2018},
	month = {May-05-2018},
	pages = {155 - 172},
	issn = {1094-6705},
	doi = {10.1177/1094670517752459},
	author = {Huang, Ming-Hui and Rust, Roland T.}
}
@article {2018,
	title = {Artificial intelligence, machine learning and the evolution of healthcare A bright future or cause for concern?},
	journal = {British Journal of Radiology},
	volume = {7},
	year = {2018},
	pages = {223-225},
	type = {Editorial},
	keywords = {artificial intelligence, deep learning, machine learning},
	author = {L.D. Jones and D. Golan and S. A. Hanna and M. Ramachandran}
}
@article {2018,
	title = {Artificial intelligence, machine learning and the evolution of healthcare},
	journal = {Bone \& Joint Research},
	volume = {7},
	year = {2018},
	month = {Jan-03-2018},
	pages = {223 - 225},
	doi = {10.1302/2046-3758.73.BJR-2017-0147.R1},
	author = {Jones, L. D. and D. Golan and S. A. Hanna and M. Ramachandran}
}
@article {2018,
	title = {As s essing the impact of machine intelligence on human behaviour: an interdisciplinary endeavour},
	year = {2018},
	url = {https://arxiv.org/ftp/arxiv/papers/1806/1806.03192.pdf},
	author = {Emilia G{\'o}mez and Carlos Castillo and Vicky Charisi and Ver{\'o}nica Dahl and Gustavo Deco and Blagoj Delipetrev and Nicole Dewandre and Miguel {\'A}ngel Gonz{\'a}lez-Ballester and Fabien Gouyon and Jos{\'e} Hern{\'a}ndez-Orallo and Perfecto Herrera and Anders Jonsson and Ansgar Koene and Martha Larson and Ram{\'o}n L{\'o}pez de M{\'a}ntaras and Bertin Martens and Marius Miron and Rub{\'e}n Moreno-Bote and Nuria Oliver and Antonio Puertas Gallardo and Heike Schweitzer and Nuria Sebastian and Xavier Serra and Joan Serr{\`a} and Song{\"u}l Tolan and Karina Vold}
}
@article {2018,
	title = {Autonomous vehicles employment impact study},
	year = {2018},
	month = {09/2018},
	url = {https://advi.org.au/wp-content/uploads/2018/09/Autonomous-Vehicles-Employment-Impact-Survey-COR050918-5.pdf},
	author = {Brian Haratsis and Tony Carmichael and Mark Coutney and Jacob Fong}
}
@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 = {Can artificial intelligence make work more human?},
	journal = {Strategic HR Review},
	volume = {17},
	year = {2018},
	month = {Aug-10-2018},
	pages = {263 - 264},
	issn = {1475-4398},
	doi = {10.1108/SHR-10-2018-146},
	author = {He, Emily}
}
@article {2018,
	title = {Comment on {\textquotedblleft}Should we fear the robot revolution? (The correct answer is yes){\textquotedblright} by Andrew Berg, Ed Buffie, and Felipe Zanna},
	journal = {Journal of Monetary Economics},
	volume = {97},
	year = {2018},
	month = {Jan-08-2018},
	pages = {149 - 152},
	issn = {03043932},
	doi = {10.1016/j.jmoneco.2018.05.012},
	author = {Hanley, Douglas}
}
@article {2018,
	title = {Computational power and the social impact of artificial intelligence},
	journal = {SSRN Electronic Journal},
	year = {2018},
	abstract = {Machine learning is computational process. To that end, it is inextricably tied to computational power - the tangible material of chips and semiconductors that the algorithms of machine intelligence operate on. Most obviously, computational power and computing architectures shape the speed of training and inference in machine learning, and therefore influence the rate of progress in the technology. But, these relationships are more nuanced than that: hardware shapes the methods used by researchers and engineers in the design and development of machine learning models. Characteristics such as the power consumption of chips also define where and how machine learning can be used in the real world.
In a broader perspective, computational power is also important because of its specific geographies. Semiconductors are designed, fabricated, and deployed through a complex international supply chain. Market structure and competition among companies in this space influence the progress of machine learning. Moreover, since these supply chains are also considered significant from a national security perspective, hardware becomes an arena in which government industrial and trade policy has a direct impact on the fundamental machinery necessary for artificial intelligence (AI).
This paper aims to dig more deeply into the relationship between computational power and the development of machine learning. Specifically, it examines how changes in computing architectures, machine learning methodologies, and supply chains might influence the future of AI. In doing so, it seeks to trace a set of specific relationship between this underlying hardware layer and the broader social impacts and risks around AI. On the hand, this examination shines a spotlight on how hardware works to exacerbate a range of concerns around ubiquitous surveillance, technological unemployment, and geopolitical conflict. On the other, it also highlights the potentially significant role that shaping the development of computing power might play in addressing these concerns.},
	doi = {10.2139/ssrn.3147971},
	author = {Tim Hwang}
}
@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 = {Discussion for JME special issue: APST paper},
	journal = {Journal of Monetary Economics},
	volume = {97},
	year = {2018},
	month = {Jan-08-2018},
	pages = {68 - 70},
	issn = {03043932},
	doi = {10.1016/j.jmoneco.2018.05.003},
	author = {Hershbein, Brad}
}
@book {2018,
	title = {eHealth - Making Health Care SmarterUse of Artificial Intelligence in Healthcare Delivery},
	year = {2018},
	publisher = {InTech},
	organization = {InTech},
	isbn = {978-1-78923-522-7},
	doi = {http://dx.doi.org/10.5772/intechopen.74714},
	author = {Reddy, Sandeep},
	editor = {Heston, Thomas F.}
}
@article {2018,
	title = {Ethics of using Artificial Intelligence to augment drafting legal documents},
	journal = { Texas A\&M Journal of Property Law},
	volume = {4},
	year = {2018},
	edition = {3},
	url = {https://scholarship.law.tamu.edu/cgi/viewcontent.cgi?article=1080\&context=journal-of-property-law},
	author = {David Hricik Hri and Asya-Lorrene S. Morgan and Kyle H. Williams}
}
@article {2018,
	title = {Exploiting ability for human adaptation to facilitate improved human-robot interaction and acceptance},
	journal = {The Information Society},
	volume = {34},
	year = {2018},
	month = {Mar-05-2020},
	pages = {153 - 165},
	issn = {0197-2243},
	doi = {10.1080/01972243.2018.1444255},
	author = {Caleb-Solly, Praminda and Dogramadzi, Sanja and Huijnen, Claire A.G.J. and Heuvel, Herjan van den}
}
@article {2018,
	title = {How do machine learning, robotic process automation, and blockchains affect the human factor in business process management? },
	journal = {Communications of the Association for Information Systems},
	year = {2018},
	month = {Jan-01-2018},
	pages = {297 - 320},
	doi = {10.17705/1CAIS.04319},
	author = {Mendling, Jan and Decker, Gero and Hull, Richard and Reijers, Hajo A. and Weber, Ingo}
}
@article {2018,
	title = {The impact of technology and globalization on employment and equity},
	journal = {International Journal of Global Sustainability},
	volume = {3},
	year = {2018},
	month = {Oct-11-2019},
	pages = {49},
	doi = {10.5296/ijgs.v3i1.14127},
	author = {Arogyaswamy, Bernard and Hunter, John}
}
@article {2018,
	title = {Improving palliative care with deep learning},
	journal = {BMC Medical Informatics and Decision Making},
	volume = {18},
	year = {2018},
	month = {Jan-12-2018},
	doi = {10.1186/s12911-018-0677-8},
	author = {Avati, Anand and Jung, Kenneth and Harman, Stephanie and Downing, Lance and Ng, Andrew and Shah, Nigam H.}
}
@article {2018,
	title = {iNaturalist as a tool to expand the research value of museum specimens},
	journal = {Applications in Plant Sciences},
	volume = {6},
	year = {2018},
	month = {Jan-11-2018},
	pages = {e01193},
	keywords = {AI use cases},
	doi = {10.1002/aps3.1193},
	author = {Heberling, J. Mason and Isaac, Bonnie L.}
}
@book {2018,
	title = {Investigating ergonomics in the context of human-robot collaboration as a sociotechnical system},
	volume = {784},
	year = {2018},
	pages = {127 - 135},
	publisher = {Springer International Publishing},
	organization = {Springer International Publishing},
	address = {Cham},
	isbn = {978-3-319-94345-9},
	issn = {2194-5357},
	doi = {10.1007/978-3-319-94346-6_12},
	author = {R{\"u}cker, Daniel and Hornfeck, R{\"u}diger and Paetzold, Kristin},
	editor = {Chen, Jessie}
}
@book {2018,
	title = {Machine intelligence: Blessing or curse? It depends on us!},
	year = {2018},
	pages = {25 - 39},
	publisher = {Springer International Publishing},
	organization = {Springer International Publishing},
	address = {Cham},
	isbn = {978-3-319-90868-7},
	doi = {10.1007/978-3-319-90869-4_4},
	author = {Helbing, Dirk},
	editor = {Helbing, Dirk}
}
@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}
}
@book {2018,
	title = {Machine Learning for Ecology and Sustainable Natural Resource ManagementMachine Learning and {\textquoteleft}The Cloud{\textquoteright} for Natural Resource Applications: Autonomous Online Robots Driving Sustainable Conservation Management Worldwide?},
	year = {2018},
	pages = {353 - 377},
	publisher = {Springer International Publishing},
	organization = {Springer International Publishing},
	address = {Cham},
	isbn = {978-3-319-96976-3},
	doi = {10.1007/978-3-319-96978-7_18},
	author = {Grant Humphries and Huettmann, Falk},
	editor = {Grant Humphries and Magness, Dawn R. and Huettmann, Falk}
}
@inbook {2018,
	title = {Machine Learning in Wildlife Biology: Algorithms, Data Issues and Availability, Workflows, Citizen Science, Code Sharing, Metadata and a Brief Historical Perspective},
	booktitle = {Machine Learning for Ecology and Sustainable Natural Resource Management},
	year = {2018},
	pages = {3 - 26},
	publisher = {Springer International Publishing},
	organization = {Springer International Publishing},
	address = {Cham},
	isbn = {978-3-319-96976-3},
	doi = {10.1007/978-3-319-96978-7_1},
	author = {Grant Humphries and Huettmann, Falk},
	editor = {Grant Humphries and Magness, Dawn R. and Huettmann, Falk}
}
@article {2018,
	title = {Managing talented worker in the era of new psychological contract},
	journal = {Jurnal Aplikasi Manajemen},
	volume = {16},
	year = {2018},
	month = {Jan-03-2018},
	pages = {20 - 26},
	issn = {16935241},
	doi = {10.21776/ub.jam.2018.016.01.03},
	author = {Haryadi, Haryadi and Anggraeni, Ade Irma and Ibrahim, Daing Nasir}
}
@article {2018,
	title = {A principled machine learning framework improves accuracy of stage II colorectal cancer prognosis},
	journal = {npj Digital Medicine},
	volume = {1},
	year = {2018},
	month = {Jan-12-2018},
	doi = {10.1038/s41746-018-0057-x},
	author = {Dimitriou, Neofytos and Arandjelovi{\'c}, Ognjen and Harrison, David J. and Caie, Peter D.}
}
@article {2018,
	title = {Robotic process automation},
	journal = {Business \& Information Systems Engineering},
	volume = {60},
	year = {2018},
	month = {Jan-08-2018},
	pages = {269 - 272},
	issn = {2363-7005},
	doi = {10.1007/s12599-018-0542-4},
	author = {van der Aalst, Wil M. P. and Bichler, Martin and Heinzl, Armin}
}
@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 = {Social robots as cultural objects: The sixth dimension of dynamicity?},
	journal = {The Information Society},
	volume = {34},
	year = {2018},
	month = {Mar-05-2020},
	pages = {141 - 152},
	issn = {0197-2243},
	doi = {10.1080/01972243.2018.1444253},
	author = {Fortunati, Leopoldina and Sarrica, Mauro and Ferrin, Giovanni and Brondi, Sonia and Honsell, Furio}
}
@article {2018,
	title = {System architecture of a driverless electric car in the grand cooperative driving challenge},
	journal = {IEEE Intelligent Transportation Systems Magazine},
	volume = {10},
	year = {2018},
	month = {Jan-21-2018},
	pages = {47 - 59},
	issn = {1939-1390},
	doi = {10.1109/MITS.2017.2776135},
	author = {Xu, Philippe and Dherbomez, Gerald and Hery, Elwan and Abidli, Abderrahmen and Bonnifait, Philippe}
}
@conference {2018,
	title = {Understanding Chatbot-mediated Task Management},
	booktitle = {the 2018 CHI ConferenceProceedings of the 2018 CHI Conference on Human Factors in Computing Systems  - CHI {\textquoteright}18},
	year = {2018},
	pages = {1 - 6},
	publisher = {ACM Press},
	organization = {ACM Press},
	address = {Montreal QC, CanadaNew York, New York, USA},
	isbn = {9781450356206},
	doi = {10.1145/317357410.1145/3173574.3173632},
	author = {Toxtli, Carlos and Monroy-Hern{\'a}ndez, Andr{\'e}s and Cranshaw, Justin}
}
@article {2018,
	title = {Will artificial intelligence solve the human resource crisis in healthcare?},
	journal = {BMC Health Services Research},
	volume = {18},
	year = {2018},
	month = {Jan-12-2018},
	doi = {10.1186/s12913-018-3359-4},
	author = {Mesk{\'o}, Bertalan and Het{\'e}nyi, Gergely and Gy{\H o}rffy, Zsuzsanna}
}
@article {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: The next digital frontier},
	year = {2017},
	url = {https://www.mckinsey.com/~/media/McKinsey/Industries/Advanced\%20Electronics/Our\%20Insights/How\%20artificial\%20intelligence\%20can\%20deliver\%20real\%20value\%20to\%20companies/MGI-Artificial-Intelligence-Discussion-paper.ashx},
	author = {Jaccques Bughin and Eric Hazan and Sree Ramaswamy and Michael Chui and Tera Allas and Peter Dahlstrom and Nicolaus Henke and Monica Trench}
}
@article {2017,
	title = {Automation, computerization and future employment in Singapore},
	journal = {Southeast Asian Economies},
	volume = {34},
	year = {2017},
	month = {Jul-08-2019},
	pages = {388 - 399},
	issn = {2339-5095},
	doi = {10.1355/ae34-2h},
	author = {Fuei, Lee King}
}
@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 = {Debating big data: A literature review on realizing value from big data},
	journal = {The Journal of Strategic Information Systems},
	volume = {26},
	year = {2017},
	month = {Jan-09-2017},
	pages = {191 - 209},
	issn = {09638687},
	doi = {10.1016/j.jsis.2017.07.003},
	author = {G{\"u}nther, Wendy Arianne and Rezazade Mehrizi, Mohammad H. and Huysman, Marleen and Feldberg, Frans}
}
@article {2017,
	title = {Elon Musk Lays Out Worst-Case Scenario for AI Threat},
	year = {2017},
	url = {https://www.wsj.com/articles/elon-musk-warns-nations-governors-of-looming-ai-threat-calls-for-regulations-1500154345},
	author = {Tim Higgins}
}
@mastersthesis {2017,
	title = {Evaluating the effects of industrial robots on the European labour market},
	volume = {Bergen, Fall, 2017},
	year = {2017},
	keywords = {economics of automation},
	url = {https://pdfs.semanticscholar.org/4e19/3a0a02315803d799520b094cce36a1888a94.pdf},
	author = {Elena Natalie and Cagnol Hveem}
}
@article {2017,
	title = {Google DeepMind and healthcare in an age of algorithms},
	journal = {Health and Technology},
	volume = {7},
	year = {2017},
	month = {Jan-12-2017},
	pages = {351 - 367},
	issn = {2190-7188},
	doi = {10.1007/s12553-017-0179-1},
	author = {Powles, Julia and Hodson, Hal}
}
@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}
}
@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 = {Rapid Evidence Review: Impact of  artificial  intelligence, robotics and  automation technologies on work},
	year = {2017},
	institution = {Chartered Institute of Personnel and Development},
	address = {London, United Kingdom},
	abstract = {The CIPD and Loughborough University{\textquoteright}s report gathers the evidence and insights on emerging technology at work and explores the ethical implications of how we{\textquoteright}re currently adopting new technology. This report creates a foundation for delving deeper into how we can ensure that people remain at the heart of work.

The report, Impact of artificial intelligence, robotics and automation technologies on work, focuses on the academic literature published since 2011 and evaluates the state of contemporary knowledge. It focuses on four key questions:

    What should the technological and occupations focus of the review be?

    What are the work-related outcomes and mediators from the utilisation of artificial intelligence (AI), robotics and automation technologies (considering both the impact for workers and organisations)?

    What are the impacts of AI, robotics and automation technologies on professions and society more generally?

    What are the ethical issues related to the contemporary utilisation of AI, robotics and automation technologies?},
	url = {https://www.cipd.co.uk/knowledge/work/technology/artificial-intelligence-workplace-impact},
	author = {Donald Hislop and Crispin Coombs and Stanimira  Taneva and Sarah Barnard}
}
@article {2017,
	title = {Situational awareness, workload, and workflow preferences},
	journal = {The International Journal of Robotics Research},
	volume = {36},
	year = {2017},
	month = {Sep-06-2017},
	pages = {597 - 617},
	issn = {0278-3649},
	doi = {10.1177/0278364916688255},
	author = {Gombolay, Matthew and Bair, Anna and Huang, Cindy and Shah, Julie}
}
@conference {2017,
	title = {SPIE ProceedingsBuilding a framework to manage trust in automation},
	booktitle = {SPIE Defense + SecurityMicro- and Nanotechnology Sensors, Systems, and Applications IX},
	volume = {10194},
	year = {2017},
	pages = {101941U},
	publisher = {SPIE},
	organization = {SPIE},
	address = {Anaheim, California, United States},
	doi = {10.1117/12.2264245},
	author = {Metcalfe, J. S. and Amar R. Marathe and Haynes, B. and Paul, V. J. and Gremillion, G. M. and Drnec, K. and Atwater, C. and Estepp, J. R. and Lukos, J. R. and Carter, E. C. and W. D. Nothwang},
	editor = {George, Thomas and Dutta, Achyut K. and Islam, M. Saif}
}
@article {2016,
	title = {Regional Diversity in Autonomy and Work: A Case Study from Uber and Lyft Drivers},
	year = {2016},
	chapter = {Data And Society},
	url = {https://datasociety.net/pubs/ia/Rosenblat-Hwang_Regional_Diversity-10-13.pdf},
	author = {Alex Rosenblat and Tim Hwang}
}
@article {2015,
	title = {A comparison between human{\textendash}human online conversations and human{\textendash}chatbot conversations},
	journal = {Computers in Human Behavior},
	volume = {49},
	year = {2015},
	month = {Jan-08-2015},
	pages = {245 - 250},
	issn = {07475632},
	doi = {10.1016/j.chb.2015.02.026},
	author = {Hill, Jennifer and Randolph Ford, W. and Farreras, Ingrid G.}
}
@article {2015,
	title = {Facebook launches M, its bold answer to Siri and Cortana},
	year = {2015},
	url = {https://www.wired.com/2015/08/facebook-launches-m-new-kind-virtual-assistant/},
	author = {Jessi Hempel}
}
@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}
}
@article {2010,
	title = {Not what it was and not what it will be: The future of job design research},
	journal = {Journal of Organizational Behavior},
	volume = {31},
	year = {2010},
	month = {Jan-02-2010},
	pages = {463 - 479},
	issn = {08943796},
	doi = {10.1002/job.v31:2/310.1002/job.678},
	author = {Oldham, Greg R. and Hackman, J. Richard},
	editor = {Grant, Adam and Fried, Yitzhak and Parker, Sharon and Frese, Michael}
}
@article {2010,
	title = {Understanding the role of occupational and organizational context},
	journal = {Journal of Organizational Behavior},
	volume = {31},
	year = {2010},
	month = {Jan-02-2010},
	pages = {351 - 360},
	issn = {08943796},
	doi = {10.1002/job.642},
	author = {Morgeson, Frederick P. and Dierdorff, Erich C. and Hmurovic, Jillian L.},
	editor = {Grant, Adam and Fried, Yitzhak and Parker, Sharon and Frese, Michael}
}
@conference {2009,
	title = {The changing face of digital science},
	booktitle = {the 27th international conference extended abstractsProceedings of the 27th international conference extended abstracts on Human factors in computing systems - CHI EA {\textquoteright}09},
	year = {2009},
	pages = {4819},
	publisher = {ACM Press},
	organization = {ACM Press},
	address = {Boston, MA, USANew York, New York, USA},
	isbn = {9781605582474},
	doi = {10.1145/1520340.1520749},
	author = {Aragon, Cecilia R. and Poon, Sarah and Silva, Claudio T.}
}
@book {2008,
	title = {Handbook of transdisciplinary research},
	year = {2008},
	pages = {427 - 432},
	publisher = {Springer Netherlands},
	organization = {Springer Netherlands},
	address = {Dordrecht},
	isbn = {978-1-4020-6698-6},
	doi = {10.1007/978-1-4020-6699-3_28},
	editor = {Hadorn, Gertrude Hirsch and Hoffmann-Riem, Holger and Biber-Klemm, Susette and Grossenbacher-Mansuy, Walter and Joye, Dominique and Pohl, Christian}
}
@article {2008,
	title = {Job and team design: Toward a more integrative conceptualization of work design},
	journal = {Research in Personnel and Human Resources ManagementResearch in Personnel and Human Resources Management},
	volume = {27},
	year = {2008},
	pages = {39{\textendash}91},
	author = {Frederick P. Morgeson and Stephen E. Humphrey}
}
@article {2006,
	title = {The Work Design Questionnaire (WDQ): Developing and validating a comprehensive measure for assessing job design and the nature of work.},
	journal = {Journal of Applied Psychology},
	volume = {91},
	year = {2006},
	month = {Jan-01-2006},
	pages = {1321 - 1339},
	issn = {0021-9010},
	doi = {10.1037/0021-9010.91.6.1321},
	author = {Morgeson, Frederick P. and Humphrey, Stephen E.}
}
@article {2000,
	title = {From human {\textendash} machine interaction to human {\textendash} machine cooperation},
	journal = {Ergonomics},
	volume = {43},
	year = {2000},
	month = {Oct-07-2000},
	pages = {833 - 843},
	issn = {0014-0139},
	doi = {10.1080/001401300409044},
	author = {Hoc, Jean-Michel}
}
@article {1999,
	title = {Information technology, workplace organization and the demand for skilled labor},
	year = {1999},
	institution = {National Bureau of Economic Research},
	address = {Cambridge, MA},
	doi = {10.3386/w7136},
	author = {Bresnahan, Timothy and Brynjolfsson, Erik and Hitt, Lorin}
}
@article {1996,
	title = {Distributed cognition in an airline cockpit},
	journal = {Cognition and Communication at WorkCognition and communication at work},
	year = {1996},
	pages = {15{\textendash}34},
	author = {Hutchins, Edwin and Klausen, Tove}
}
@book {1980,
	title = {Work Redesign},
	year = {1980},
	publisher = {Addison-Wesley},
	organization = {Addison-Wesley},
	address = {Reading, MA},
	author = {J. Richard Hackman and Oldham, G. R.}
}
