@article {2024,
	title = {Artificial Intelligence and the Future of Citizen Science},
	journal = {Citizen Science: Theory and Practice},
	volume = {9},
	year = {2024},
	month = {11/2024},
	pages = {32},
	doi = {10.5334/cstp.812},
	author = {Fortson, Lucy and Crowston, Kevin and Kloetzer, Laure and Ponti, Marisa}
}
@conference {osterlund2024,
	title = {Mutual learning in human-AI interaction},
	booktitle = {Trust and Reliance in Evolving Human-AI Workflows (TREW) Workshop, ACM CHI Conference},
	year = {2024},
	address = {Honolulu, HI},
	abstract = {<p>We explore the bi-directional relationship between human and machine learning in citizen science. Theoretically, the study draws on the Zone of Proximal Development concept, which allows us to describe the augmentation of human learning by AI, human augmentation of machine learning and how tasks can be designed to facilitate co-augmentation. Methodologically, the study utilizes a design-science approach to explore the design, deployment, and evaluations of the Gravity Spy citizen science project. The findings highlight the challenges and opportunities of co-augmentation, where both humans and machines contribute to each other{\textquoteright}s learning and capabilities.\&nbsp; The research contributes to the existing literature by emphasizing the role of ZPD in citizen science projects, showcasing how the concept supports ongoing learning for volunteers and keeps machine learning aligned with evolving data.</p>},
	attachments = {https://waim.network/sites/crowston.syr.edu/files/TREW_Workshop_Paper.pdf},
	author = {{\O}sterlund, Carsten and Crowston, Kevin and Jackson, Casey B. and Takou-Ayaoh, Marlene and Wu, Yunan and Katsaggelos, Aggelos K.}
}
@conference {2024,
	title = {ReelFramer: Human-AI Co-Creation for News-to-Video Translation},
	booktitle = {CHI {\textquoteright}24: CHI Conference on Human Factors in Computing SystemsProceedings of the CHI Conference on Human Factors in Computing Systems},
	year = {2024},
	pages = {1 - 20},
	publisher = {ACM},
	organization = {ACM},
	address = {Honolulu HI USANew York, NY, USA},
	isbn = {9798400703300},
	doi = {10.1145/3613904.3642868},
	author = {Wang, Sitong and Menon, Samia and Long, Tao and Henderson, Keren and Li, Dingzeyu and Crowston, Kevin and Hansen, Mark and Nickerson, Jeffrey V and Chilton, Lydia B},
	editor = {Mueller, Florian Floyd and Kyburz, Penny and Williamson, Julie R. and Sas, Corina and Wilson, Max L. and Dugas, Phoebe Toups and Shklovski, Irina}
}
@article {9998,
	title = {Supporting and augmenting human and machine learning in citizen science: Lessons from Gravity Spy},
	journal = {Citizen Science: Theory and Practice},
	volume = {9},
	year = {2024},
	month = {11/2024},
	pages = {42},
	doi = {10.5334/cstp.738},
	author = {Carsten {\O}sterlund and Kevin Crowston and Corey B. Jackson and Yunan Wu and Alexander O. Smith and Aggelos K. Katsaggelos}
}
@article {Kuziemski2020,
	title = {AI governance in the public sector: Three tales from the frontiers of automated decision-making in democratic settings},
	journal = {Telecommunications Policy},
	volume = {44},
	number = {6},
	year = {2020},
	pages = {101976},
	publisher = {Elsevier Ltd},
	abstract = {The rush to understand new socio-economic contexts created by the wide adoption of AI is justified by its far-ranging consequences, spanning almost every walk of life. Yet, the public sector{\textquoteright}s predicament is a tragic double bind: its obligations to protect citizens from potential algorithmic harms are at odds with the temptation to increase its own efficiency - or in other words - to govern algorithms, while governing by algorithms. Whether such dual role is even possible, has been a matter of debate, the challenge stemming from algorithms{\textquoteright} intrinsic properties, that make them distinct from other digital solutions, long embraced by the governments, create externalities that rule-based programming lacks. As the pressures to deploy automated decision making systems in the public sector become prevalent, this paper aims to examine how the use of AI in the public sector in relation to existing data governance regimes and national regulatory practices can be intensifying existing power asymmetries. To this end, investigating the legal and policy instruments associated with the use of AI for strenghtening the immigration process control system in Canada; {\textquotedblleft}optimising{\textquotedblright} the employment services{\textquotedblright} in Poland, and personalising the digital service experience in Finland, the paper advocates for the need of a common framework to evaluate the potential impact of the use of AI in the public sector. In this regard, it discusses the specific effects of automated decision support systems on public services and the growing expectations for governments to play a more prevalent role in the digital society and to ensure that the potential of technology is harnessed, while negative effects are controlled and possibly avoided. This is of particular importance in light of the current COVID-19 emergency crisis where AI and the underpinning regulatory framework of data ecosystems, have become crucial policy issues as more and more innovations are based on large scale data collections from digital devices, and the real-time accessibility of information and services, contact and relationships between institutions and citizens could strengthen {\textendash} or undermine - trust in governance systems and democracy.},
	keywords = {Algorithmic accountability, artificial intelligence, Automated decision making, Public sector innovation},
	issn = {03085961},
	doi = {10.1016/j.telpol.2020.101976},
	url = {https://doi.org/10.1016/j.telpol.2020.101976},
	author = {Kuziemski, Maciej and Misuraca, Gianluca}
}
@article {Dogru2020,
	title = {AI in operations management: applications, challenges and opportunities},
	journal = {Journal of Data, Information and Management},
	volume = {2},
	number = {2},
	year = {2020},
	pages = {67{\textendash}74},
	publisher = {Journal of Data, Information and Management},
	abstract = {We have witnessed unparalleled progress in artificial intelligence (AI) and machine learning (ML) applications in the last two decades. The AI technologies have accelerated advancements in robotics and automation, which have significant implications on almost every aspect of businesses, and especially supply chain operations. Supply chains have widely adopted smart technologies that enable real-time automated data collection, analysis, and prediction. In this study, we review recent applications of AI in operations management (OM) and supply chain management (SCM). Specifically, we consider the innovations in healthcare, manufacturing, and retail operations, since collectively, these three areas represent a majority of the AI innovations in business as well as growing problem areas. We discuss primary challenges and opportunities for utilizing AI in those industries. We also discuss trending research topics with significant value potential in these areas.},
	keywords = {AI, artificial intelligence, Artificial Intelligence (AI), automation, machine learning, machine learning (ML), ml, om, operations management, Operations Management (OM), Robotics, scm, supply chain management, Supply Chain Management (SCM)},
	issn = {2524-6356},
	doi = {10.1007/s42488-020-00023-1},
	author = {Dogru, Ali K and Keskin, Burcu B}
}
@article {2020,
	title = {Algorithms at work: The new contested terrain of control},
	journal = {Academy of Management Annals},
	volume = {14},
	year = {2020},
	month = {Jan-01-2020},
	pages = {366 - 410},
	issn = {1941-6520},
	doi = {10.5465/annals.2018.0174},
	author = {Kellogg, Katherine C. and Valentine, Melissa A. and Christin, Ang{\'e}le}
}
@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}
}
@article {Bansal2020,
	title = {Does the Whole Exceed its Parts? The Effect of AI Explanations on Complementary Team Performance},
	year = {2020},
	abstract = {<p>Increasingly, organizations are pairing humans with AI systems to improve decision-making and reducing costs. Proponents of human-centered AI argue that team performance can even further improve when the AI model explains its recommendations. However, a careful analysis of existing literature reveals that prior studies observed improvements due to explanations only when the AI, alone, outperformed both the human and the best human-AI team. This raises an important question: can explanations lead to complementary performance, i.e., with accuracy higher than both the human and the AI working alone? We address this question by devising comprehensive studies on human-AI teaming, where participants solve a task with help from an AI system without explanations and from one with varying types of AI explanation support. We carefully controlled to ensure comparable human and AI accuracy across experiments on three NLP datasets (two for sentiment analysis and one for question answering). While we found complementary improvements from AI augmentation, they were not increased by state-of-the-art explanations compared to simpler strategies, such as displaying the AI{\textquoteright}s confidence. We show that explanations increase the chance that humans will accept the AI{\textquoteright}s recommendation regardless of whether the AI is correct. While this clarifies the gains in team performance from explanations in prior work, it poses new challenges for human-centered AI: how can we best design systems to produce complementary performance? Can we develop explanatory approaches that help humans decide whether and when to trust AI input?</p>},
	url = {http://arxiv.org/abs/2006.14779},
	author = {Bansal, Gagan and Wu, Tongshuang and Zhou, Joyce and Fok, Raymond and Nushi, Besmira and Kamar, Ece and Ribeiro, Marco Tulio and Weld, Daniel S.}
}
@article {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}
}
@conference {Azarova2020,
	title = {Key Advantages and Risks of Implementing Artificial Intelligence in the Activities of Professional Communicators},
	booktitle = {Proceedings of the 2020 IEEE Communication Strategies in Digital Society Seminar, ComSDS 2020},
	year = {2020},
	pages = {82{\textendash}86},
	abstract = {Nowadays we observe a wide penetration of digital technologies into communication experts practice. Literature review demonstrates a great interest of both technical and humanitarian scholars to this subject. The research results, obtained by opinion survey (young adults of 19-24 years old), illustrate possible pragmatic and ethical effects of AI applications as well as their advantages and risks.},
	keywords = {AI technologies risks, artificial intelligence, digital technologies, professional communicators},
	isbn = {9781728164410},
	doi = {10.1109/ComSDS49898.2020.9101238},
	author = {Azarova, Liudmila and Kudryavtseva, Maria and Sharakhina, Larisa}
}
@article {Kernbach2020,
	title = {Machine learning-based clinical prediction modeling {\textendash} A practical guide for clinicians},
	journal = {Artificial Intelligence in Precision Health},
	number = {June},
	year = {2020},
	pages = {257{\textendash}278},
	publisher = {Elsevier Inc.},
	keywords = {Alzheimers disease detection, artificial intelligence, Convolutional neural networks, Deep neural networks, Ensemble machine learning methods},
	isbn = {9780128171332},
	doi = {10.1016/b978-0-12-817133-2.00011-2},
	url = {https://arxiv.org/abs/2006.15069v1 http://dx.doi.org/10.1016/B978-0-12-817133-2.00011-2},
	author = {Kernbach, Julius M. and Staartjes, Victor E.}
}
@article {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}
}
@conference {Schneider2020,
	title = {Similarity Learning Networks for Animal Individual Re-Identification-Beyond the Capabilities of a Human Observer},
	booktitle = {Proceedings - 2020 IEEE Winter Conference on Applications of Computer Vision Workshops, WACVW 2020},
	volume = {479},
	year = {2020},
	pages = {44{\textendash}52},
	abstract = {Deep learning has become the standard methodology to approach computer vision tasks when large amounts of labeled data are available. One area where traditional deep learning approaches fail to perform is one-shot learning tasks where a model must correctly classify a new category after seeing only one example. One such domain is animal re-identification, an application of computer vision which can be used globally as a method to automate species population estimates from camera trap images. Our work demonstrates both the application of similarity comparison networks to animal re-identification, as well as the capabilities of deep convolutional neural networks to generalize across domains. Few studies have considered animal re-identification methods across species. Here, we compare two similarity comparison methodologies: Siamese and Triplet-Loss, based on the AlexNet, VGG-19, DenseNet201, MobileNetV2, and InceptionV3 architectures considering mean average precision (mAP)@1 and mAP@5. We consider five data sets corresponding to five different species: Humans, chimpanzees, humpback whales, fruit flies, and Siberian tigers, each with their own unique set of challenges. We demonstrate that Triplet Loss outperformed its Siamese counterpart for all species. Without any species-specific modifications, our results demonstrate that similarity comparison networks can reach a performance level beyond that of humans for the task of animal re-identification. The ability for researchers to re-identify an animal individual upon re-encounter is fundamental for addressing a broad range of questions in the study of population dynamics and community/behavioural ecology. Our expectation is that similarity comparison networks are the beginning of a major trend that could stand to revolutionize animal re-identification from camera trap data.},
	isbn = {9781728171623},
	doi = {10.1109/WACVW50321.2020.9096925},
	author = {Schneider, Stefan and Taylor, Graham W. and Kremer, Stefan C.}
}
@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}
}
@conference {Ferreira2020,
	title = {Understanding the Impact of Artificial Intelligence on Services},
	booktitle = {International Conference on Exploring Services Science},
	series = {Lecture Notes in Business Information Processing},
	volume = {1},
	number = {January},
	year = {2020},
	pages = {202{\textendash}213},
	publisher = {Springer International Publishing},
	organization = {Springer International Publishing},
	address = {Cham},
	abstract = {The service sector is changing drastically due the use of robotics and other technologies, such as Artificial Intelligence (AI), Internet of things (IoT), Big Data and Biometrics. Consequently, further research opportunities in the service industry domain are also expected. In light of the above, the purpose of this paper is to explore the potentialities and limitations of service robots in the hospitality industry. To this end, this paper uses a conceptual approach based on a literature review. As a result, we found that in contexts of high customer contact, service robots should be considered to perform standardized tasks due to social/emotional and cognitive/analytical complexity. The hospitality industry is therefore considered closely related to empathic intelligence, as the integration of service robots has not yet reached the desired stage of service delivery. In a seemingly far-fetched context of our reality, organizations will have to decide whether the AI will allow the complete replacement of humans with robots capable of performing the necessary cognitive and emotional tasks. Or investing in balanced capacities by integrating robot-human systems that seems a rea- sonable option these days. Keywords:},
	keywords = {{\'a} servitization {\'a} design, science research, service design},
	isbn = {9783030387242},
	doi = {10.1007/978-3-030-38724-2},
	url = {http://link.springer.com/10.1007/978-3-030-38724-2},
	author = {Ferreira, Pedro and Teixeira, Jorge Grenha and Teixeira, Lu{\'\i}s F.},
	editor = {N{\'o}voa, Henriqueta and Dr{\u a}goicea, Monica and K{\"u}hl, Niklas}
}
@article {Krupiy2020,
	title = {A vulnerability analysis : Theorising the impact of artificial intelligence decision-making processes on individuals , society and human diversity from a social justice perspective},
	journal = {Computer Law \& Security Review: The International Journal of Technology Law and Practice},
	volume = {38},
	year = {2020},
	pages = {105429},
	publisher = {Elsevier Ltd},
	keywords = {artificial intelligence, data science, Decision-maki},
	issn = {0267-3649},
	doi = {10.1016/j.clsr.2020.105429},
	url = {https://doi.org/10.1016/j.clsr.2020.105429},
	author = {Krupiy, Tetyana Tanya}
}
@article {2019,
	title = {Artificial Intelligence and Deep Learning: The Future of Medicine and Medical Practice},
	journal = { Journal of The Association of Physicians of India ■ Vol. 67 },
	year = {2019},
	month = {05/2019},
	url = {https://www.semanticscholar.org/paper/Artificial-Intelligence-and-Deep-Learning\%3A-The-of-Sanal-Paul/795dc72decfb12389bbf7076d82fef70421b9933},
	author = {Madhusudana Girija Sanal and Kolin Paul and Senthil Kumar and Nirmal Kumar Gangul}
}
@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 = {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 = {Collaboration and delegation between humans and AI: An experimental investigation of the future of work},
	journal = {SSRN Electronic Journal},
	year = {2019},
	month = {Jan-01-2019},
	doi = {10.2139/ssrn.3368813},
	author = {F{\"u}gener, Andreas and Grahl, J{\"o}rn and Gupta, Alok and Ketter, Wolfgang}
}
@article {2019,
	title = {Comparing artificial intelligence algorithms to 157 German dermatologists: the melanoma classification benchmark},
	journal = {European Journal of Cancer},
	volume = {111},
	year = {2019},
	month = {Jan-04-2019},
	pages = {30 - 37},
	issn = {09598049},
	doi = {10.1016/j.ejca.2018.12.016},
	author = {Brinker, Titus J. and Hekler, Achim and Hauschild, Axel and Berking, Carola and Schilling, Bastian and Alexander Enk and Haferkamp, Sebastian and Karoglan, Ante and von Kalle, Christof and Weichenthal, Michael and Sattler, Elke and Schadendorf, Dirk and Gaiser, Maria R. and Klode, Joachim and Jochen Sven Utikal}
}
@article {2019,
	title = {A convolutional neural network trained with dermoscopic images performed on par with 145 dermatologists in a clinical melanoma image classification task},
	journal = {European Journal of Cancer},
	volume = {111},
	year = {2019},
	month = {Jan-04-2019},
	pages = {148 - 154},
	issn = {09598049},
	doi = {10.1016/j.ejca.2019.02.005},
	author = {Brinker, Titus J. and Hekler, Achim and Alexander Enk and Klode, Joachim and Hauschild, Axel and Berking, Carola and Schilling, Bastian and Haferkamp, Sebastian and Schadendorf, Dirk and Fr{\"o}hling, Stefan and Jochen Sven Utikal and von Kalle, Christof and Ludwig-Peitsch, Wiebke and Sirokay, Judith and Heinzerling, Lucie and Albrecht, Magarete and Baratella, Katharina and Bischof, Lena and Chorti, Eleftheria and Dith, Anna and Drusio, Christina and Giese, Nina and Gratsias, Emmanouil and Griewank, Klaus and Hallasch, Sandra and Hanhart, Zdenka and Herz, Saskia and Hohaus, Katja and Jansen, Philipp and Jockenh{\"o}fer, Finja and Kanaki, Theodora and Knispel, Sarah and Leonhard, Katja and Martaki, Anna and Matei, Liliana and Matull, Johanna and Olischewski, Alexandra and Petri, Maximilian and Placke, Jan-Malte and Raub, Simon and Salva, Katrin and Schlott, Swantje and Sody, Elsa and Steingrube, Nadine and Stoffels, Ingo and Ugurel, Selma and Sondermann, Wiebke and Zaremba, Anne and Gebhardt, Christoffer and Booken, Nina and Christolouka, Maria and Buder-Bakhaya, Kristina and Bokor-Billmann, Therezia and Alexander Enk and Gholam, Patrick and H{\"a}n{\ss}le, Holger and Salzmann, Martin and Sch{\"a}fer, Sarah and Sch{\"a}kel, Knut and Schank, Timo and Bohne, Ann-Sophie and Deffaa, Sophia and Drerup, Katharina and Egberts, Friederike and Erkens, Anna-Sophie and Ewald, Benjamin and Falkvoll, Sandra and Gerdes, Sascha and Harde, Viola and Hauschild, Axel and Jost, Marion and Kosova, Katja and Messinger, Laetitia and Metzner, Malte and Morrison, Kirsten and Motamedi, Rogina and Pinczker, Anja and Rosenthal, Anne and Scheller, Natalie and Schwarz, Thomas and St{\"o}lzl, Dora and Thielking, Federieke and Tomaschewski, Elena and Wehkamp, Ulrike and Weichenthal, Michael and Wiedow, Oliver and B{\"a}r, Claudia Maria and Bender-S{\"a}belkampf, Sophia and Horbr{\"u}gger, Marc and Karoglan, Ante and Kraas, Luise and Faulhaber, J{\"o}rg and Geraud, Cyrill and Guo, Ze and Koch, Philipp and Linke, Miriam and Maurier, Nolwenn and M{\"u}ller, Verena and Thomas, Benjamin and Jochen Sven Utikal and Alamri, Ali Saeed M. and Baczako, Andrea and Berking, Carola and Betke, Matthias and Haas, Carolin and Hartmann, Daniela and Heppt, Markus V. and Kilian, Katharina and Krammer, Sebastian and Lapczynski, Natalie Lidia and Mastnik, Sebastian and Nasifoglu, Suzan and Ruini, Cristel and Sattler, Elke and Schlaak, Max and Wolff, Hans and Achatz, Birgit and Bergbreiter, Astrid and Drexler, Konstantin and Ettinger, Monika and Haferkamp, Sebastian and Halupczok, Anna and Hegemann, Marie and Dinauer, Verena and Maagk, Maria and Mickler, Marion and Philipp, Biance and Wilm, Anna and Wittmann, Constanze and Gesierich, Anja and Glutsch, Valerie and Kahlert, Katrin and Kerstan, Andreas and Schilling, Bastian and Schr{\"u}fer, Philipp}
}
@article {2019,
	title = {Deep learning outperformed 136 of 157 dermatologists in a head-to-head dermoscopic melanoma image classification task},
	journal = {European Journal of Cancer},
	volume = {113},
	year = {2019},
	month = {Jan-05-2019},
	pages = {47 - 54},
	issn = {09598049},
	doi = {10.1016/j.ejca.2019.04.001},
	author = {Brinker, Titus J. and Hekler, Achim and Alexander Enk and Klode, Joachim and Hauschild, Axel and Berking, Carola and Schilling, Bastian and Haferkamp, Sebastian and Schadendorf, Dirk and Holland-Letz, Tim and Jochen Sven Utikal and von Kalle, Christof and Ludwig-Peitsch, Wiebke and Sirokay, Judith and Heinzerling, Lucie and Albrecht, Magarete and Baratella, Katharina and Bischof, Lena and Chorti, Eleftheria and Dith, Anna and Drusio, Christina and Giese, Nina and Gratsias, Emmanouil and Griewank, Klaus and Hallasch, Sandra and Hanhart, Zdenka and Herz, Saskia and Hohaus, Katja and Jansen, Philipp and Jockenh{\"o}fer, Finja and Kanaki, Theodora and Knispel, Sarah and Leonhard, Katja and Martaki, Anna and Matei, Liliana and Matull, Johanna and Olischewski, Alexandra and Petri, Maximilian and Placke, Jan-Malte and Raub, Simon and Salva, Katrin and Schlott, Swantje and Sody, Elsa and Steingrube, Nadine and Stoffels, Ingo and Ugurel, Selma and Zaremba, Anne and Gebhardt, Christoffer and Booken, Nina and Christolouka, Maria and Buder-Bakhaya, Kristina and Bokor-Billmann, Therezia and Alexander Enk and Gholam, Patrick and H{\"a}n{\ss}le, Holger and Salzmann, Martin and Sch{\"a}fer, Sarah and Sch{\"a}kel, Knut and Schank, Timo and Bohne, Ann-Sophie and Deffaa, Sophia and Drerup, Katharina and Egberts, Friederike and Erkens, Anna-Sophie and Ewald, Benjamin and Falkvoll, Sandra and Gerdes, Sascha and Harde, Viola and Hauschild, Axel and Jost, Marion and Kosova, Katja and Messinger, Laetitia and Metzner, Malte and Morrison, Kirsten and Motamedi, Rogina and Pinczker, Anja and Rosenthal, Anne and Scheller, Natalie and Schwarz, Thomas and St{\"o}lzl, Dora and Thielking, Federieke and Tomaschewski, Elena and Wehkamp, Ulrike and Weichenthal, Michael and Wiedow, Oliver and B{\"a}r, Claudia Maria and Bender-S{\"a}belkampf, Sophia and Horbr{\"u}gger, Marc and Karoglan, Ante and Kraas, Luise and Faulhaber, J{\"o}rg and Geraud, Cyrill and Guo, Ze and Koch, Philipp and Linke, Miriam and Maurier, Nolwenn and M{\"u}ller, Verena and Thomas, Benjamin and Jochen Sven Utikal and Alamri, Ali Saeed M. and Baczako, Andrea and Berking, Carola and Betke, Matthias and Haas, Carolin and Hartmann, Daniela and Heppt, Markus V. and Kilian, Katharina and Krammer, Sebastian and Lapczynski, Natalie Lidia and Mastnik, Sebastian and Nasifoglu, Suzan and Ruini, Cristel and Sattler, Elke and Schlaak, Max and Wolff, Hans and Achatz, Birgit and Bergbreiter, Astrid and Drexler, Konstantin and Ettinger, Monika and Haferkamp, Sebastian and Halupczok, Anna and Hegemann, Marie and Dinauer, Verena and Maagk, Maria and Mickler, Marion and Philipp, Biance and Wilm, Anna and Wittmann, Constanze and Gesierich, Anja and Glutsch, Valerie and Kahlert, Katrin and Kerstan, Andreas and Schilling, Bastian and Schr{\"u}fer, Philipp}
}
@book {2019,
	title = {Designing AI futures: A symbiotic vision},
	volume = {1083},
	year = {2019},
	pages = {3 - 18},
	publisher = {Springer International Publishing},
	organization = {Springer International Publishing},
	address = {Cham},
	isbn = {978-3-030-29742-8},
	issn = {1865-0929},
	doi = {10.1007/978-3-030-29743-5_1},
	author = {Gill, Karamjit S.},
	editor = {Kravets, Alla G. and Groumpos, Peter P. and Shcherbakov, Maxim and Kultsova, Marina}
}
@article {2019,
	title = {Economic, Social Impacts and Operation of Smart Factories in Industry 4.0 Focusing on Simulation and Artificial Intelligence of Collaborating Robots},
	journal = {Social Sciences},
	volume = {8},
	year = {2019},
	month = {Jan-05-2019},
	pages = {143},
	doi = {10.3390/socsci8050143},
	author = {Benotsmane, Rabab and Kov{\'a}cs, Gy{\"o}rgy and Dud{\'a}s, L{\'a}szl{\'o}}
}
@book {2019,
	title = {The fourth industrial revolution: Trends and impacts on the world of work},
	year = {2019},
	pages = {177 - 194},
	publisher = {Springer International Publishing},
	organization = {Springer International Publishing},
	address = {Cham},
	isbn = {978-3-319-94531-6},
	doi = {10.1007/978-3-319-94532-3_115},
	author = {Kim, Sang Yun},
	editor = {McGrath, Simon and Mulder, Martin and Papier, Joy and Suart, Rebecca}
}
@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}
}
@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 = {Integrating ethical values and economic value to steer progress in Artificial Intelligenc},
	year = {2019},
	month = {08/2019},
	keywords = {ethics},
	url = {https://www.nber.org/papers/w26130},
	author = {Anton Korinek}
}
@article {2019,
	title = {Introduction: The Future of Jobs in an Increasingly Autonomous Economy},
	journal = {Journal of Management Inquiry},
	volume = {28},
	year = {2019},
	month = {Jun-07-2021},
	pages = {298 - 299},
	issn = {1056-4926},
	doi = {10.1177/1056492619827373},
	author = {Choi, David Y. and Kang, Jae Hyeung}
}
@conference {2019,
	title = {Machine learning in Artificial Intelligence: Towards a common understanding},
	booktitle = {Hawaii International Conference on System SciencesProceedings of the 52nd Hawaii International Conference on System Sciences},
	year = {2019},
	publisher = {Hawaii International Conference on System Sciences},
	organization = {Hawaii International Conference on System Sciences},
	doi = {10.24251/HICSS.2019.630},
	author = {K{\"u}hl, Niklas and Goutier, Marc and Hirt, Robin and Satzger, Gerhard}
}
@article {2019,
	title = {A Machine Learning Platform to Optimize the Translation of Personalized Network Models to the Clinic},
	journal = {JCO Clinical Cancer Informatics},
	year = {2019},
	month = {Jan-04-2019},
	pages = {1 - 17},
	issn = {2473-4276},
	doi = {10.1200/CCI.18.00056},
	author = {Salvucci, Manuela and Rahman, Arman and Resler, Alexa J. and Udupi, Girish M. and McNamara, Deborah A. and Kay, Elaine W. and Laurent-Puig, Pierre and Longley, Daniel B. and Johnston, Patrick G. and Lawler, Mark and Wilson, Richard and Salto-Tellez, Manuel and Van Schaeybroeck, Sandra and Rafferty, Mairin and Gallagher, William M. and Rehm, Markus and Prehn, Jochen H.M.}
}
@book {2019,
	title = {Moral reasoning at work automation and ethics},
	year = {2019},
	pages = {69 - 77},
	publisher = {Springer International Publishing},
	organization = {Springer International Publishing},
	address = {Cham},
	isbn = {978-3-030-15190-4},
	url = {10.1007/978-3-030-15191-1_8},
	author = {Kvalnes, {\O}yvind and Kvalnes, {\O}yvind}
}
@article {2019,
	title = {Net job creation in an increasingly autonomous economy: The challenge of a generation},
	journal = {Journal of Management Inquiry},
	volume = {28},
	year = {2019},
	month = {Jun-07-2021},
	pages = {300 - 305},
	issn = {1056-4926},
	doi = {10.1177/1056492619827372},
	author = {Choi, David Y. and Kang, Jae Hyeung}
}
@article {2019,
	title = {The potential for artificial intelligence in healthcare},
	journal = {Future Healthcare Journal},
	volume = {6},
	year = {2019},
	month = {Jan-06-2020},
	pages = {94 - 98},
	issn = {2514-6645},
	doi = {10.7861/futurehosp.6-2-94},
	author = {Davenport, Thomas and Kalakota, Ravi}
}
@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 = {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}
}
@article {2019,
	title = {Towards a smart automated society: Cognitive technologies, knowledge production, and economic growth},
	journal = {Economics, Management, and Financial Markets},
	volume = {14},
	year = {2019},
	month = {Jan-01-2019},
	pages = {44},
	issn = {1842-3191},
	doi = {10.22381/EMFM14120195},
	author = {Mitchell Udell and Vojtech Stehel and Tomas Kliestik and Jana Kliestikova and Pavol Durana}
}
@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 = {Use of Artificial Intelligence to Improve Resilience and Preparedness Against Adverse Flood Events},
	journal = {Water},
	volume = {11},
	year = {2019},
	month = {Jan-05-2019},
	pages = {973},
	doi = {10.3390/w11050973},
	author = {Saravi, Sara and Kalawsky, Roy and Joannou, Demetrios and Rivas Casado, Monica and Fu, Guangtao and Meng, Fanlin}
}
@article {2018,
	title = {7 things I learned from building an AI chatbot for leadership development},
	year = {2018},
	url = {https://www.forbes.com/sites/kevinkruse/2018/10/15/ai-chatbot-leadership-development-training-hr/$\#$206492515ff0},
	author = {Kevin Kruse}
}
@article {2018,
	title = {7 things I learned from building an AI chatbot for leadership development},
	year = {2018},
	url = {https://www.forbes.com/sites/kevinkruse/2018/10/15/ai-chatbot-leadership-development-training-hr/$\#$206492515ff0},
	author = {Kevin Kruse}
}
@book {2018,
	title = {Advances in intelligent systems and computing},
	series = {Proceedings of the 1st International Conference on Intelligent Human Systems Integration },
	year = {2018},
	url = {https://link.springer.com/book/10.1007/978-3-030-11051-2?page=2},
	author = {Advances in Intelligent Systems and Computing 722 Waldemar Karwowski}
}
@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 = {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 = {As s essing the impact of machine intelligence on human behaviour: an interdisciplinary endeavour},
	year = {2018},
	url = {https://arxiv.org/ftp/arxiv/papers/1806/1806.03192.pdf},
	author = {Emilia G{\'o}mez and Carlos Castillo and Vicky Charisi and Ver{\'o}nica Dahl and Gustavo Deco and Blagoj Delipetrev and Nicole Dewandre and Miguel {\'A}ngel Gonz{\'a}lez-Ballester and Fabien Gouyon and Jos{\'e} Hern{\'a}ndez-Orallo and Perfecto Herrera and Anders Jonsson and Ansgar Koene and Martha Larson and Ram{\'o}n L{\'o}pez de M{\'a}ntaras and Bertin Martens and Marius Miron and Rub{\'e}n Moreno-Bote and Nuria Oliver and Antonio Puertas Gallardo and Heike Schweitzer and Nuria Sebastian and Xavier Serra and Joan Serr{\`a} and Song{\"u}l Tolan and Karina Vold}
}
@article {2018,
	title = {Automated Classification of chest X-ray images as normal or abnormal using Convolutional Neural Network},
	journal = {Asian Journal of Convergence in Technology},
	volume = {4},
	year = {2018},
	month = {04/2018},
	abstract = {Chest X-Rays are generally used for diagnosing abnormalities in the thoracic area. Radiologists need to spend significant amount of time for interpreting scans. Automatic classification of these images could greatly help radiology interpretation process by enhancing real world diagnosis of problems. Hence, radiologists can focus on detecting abnormalities from the abnormal images rather than checking for it in all the images. In this paper, we present a machine learning approach to solve this problem. Here, the algorithm uses COnvolutional Neural Networks (CNN) to learn and classify chest X-ray images as normal or abnormal based on image features.},
	keywords = {classification, machine learning, radiology},
	author = {Aayushi Gupta and Anupama C and P Indumathi and Anuj Kumar}
}
@article {2018,
	title = {Automation and the future of jobs in India},
	year = {2018},
	month = {11/2018},
	publisher = {University of Pennsylvania},
	type = {Economy, Politics, Science and Technology},
	keywords = {economics of automation},
	url = {https://casi.sas.upenn.edu/iit/kuriakoseiyer},
	author = {Francis Kuriakose and Deepa Iyer}
}
@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}
}
@mastersthesis {2018,
	title = {Examination of cognitive load in the human-machine teaming context},
	year = {2018},
	month = {06/2018},
	abstract = {The Department of Defense (DoD) is increasingly hoping to employ unmanned systems and artificial intelligence to achieve a strategic advantage over adversaries. While some tasks may be suitable for machine substitution, many parts of the DoD{\textquoteright}s mission continue to require boots on the ground and humans in the loop working in interdependent human-machine teams. The commercial unmanned systems marketplace and active UxS and autonomous systems offer military research and acquisitions professionals promising technical solutions, but may integrate poorly in a human-machine team application. The authors developed a framework for analyzing task-to-technology matches and team design for military human-machine teams. The framework is grounded in the cognitive theories of situational awareness and decision making, team dynamics, and functional allocation literature. Additionally, the research recommends developing a shared DoD-wide understanding of autonomous systems terms and taxonomy, and educating operational leaders, acquisitions staff, and executives about realistic expectations and employment of autonomous systems in human-machine environments.},
	url = {https://hdl.handle.net/10945/59638},
	author = {Clarke, Alan J. and Knudson, Daniel F. III}
}
@article {2018,
	title = {Explaining the decline in the u. S. Employment-to-population ratio: A review of the evidence},
	year = {2018},
	institution = {National Bureau of Economic Research},
	address = {Cambridge, MA},
	doi = {10.3386/w24333},
	author = {Abraham, Katharine and Kearney, Melissa}
}
@article {2018,
	title = {Financing Terror Enterprises Funding Operations in Prolonged Conflicts in South Asia},
	year = {2018},
	institution = {KW Publishers Pvt Ltd},
	address = {New Delhi},
	issn = {23939729},
	url = {https://www.claws.in/images/publication_pdf/1589740822_1515901225_MP71-NikitaKohli(Final)_CLAWS.pdf},
	author = {Nikita Kohli}
}
@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.}
}
@article {2018,
	title = {Future of artificial intelligence: Japan{\textquoteright}s path to growth},
	journal = {American Journal Of Modern Physics And Application},
	volume = {5},
	year = {2018},
	month = {05/2018},
	pages = {48-52},
	url = {https://www.researchgate.net/publication/326625497_Future_of_Artificial_Intelligence_Japan{\textquoteright}s_Path_to_Growth_Email_address},
	author = {Salman Abdou and Nadeen Nustafa Kamal}
}
@article {2018,
	title = {Google and others are building AI systems that doubt themselves},
	year = {2018},
	url = {https://www.technologyreview.com/s/609762/google-and-others-are-building-ai-systems-that-doubt-themselves/},
	author = {Will Knight}
}
@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 Machine Learning},
	journal = {Computational Economics},
	year = {2018},
	month = {Sep-02-2019},
	issn = {0927-7099},
	doi = {10.1007/s10614-018-9803-z},
	author = {Kao, Ying-Fang and Venkatachalam, Ragupathy}
}
@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}
}
@article {2018,
	title = {Identifying factors reinforcing robotization: Interactive forces of employment, working hour and wage},
	journal = {Sustainability},
	volume = {10},
	year = {2018},
	month = {Jan-02-2018},
	pages = {490},
	doi = {10.3390/su10020490},
	author = {Cho, Joonmo and Kim, Jinha}
}
@article {2018,
	title = {Imagining a future of work that fosters mobility for all},
	year = {2018},
	url = {https://www.mobilitypartnership.org/imagining-future-work-fosters-mobility-all},
	author = {Lawrence Katz and Ai-Jen Poo and Elaine Waxman}
}
@article {2018,
	title = {The impact of automation on employment: Just the usual structural change? },
	journal = {Sustainability},
	volume = {10},
	year = {2018},
	month = {Jan-05-2018},
	pages = {1661},
	doi = {10.3390/su10051661},
	author = {Vermeulen, Ben and Kesselhut, Jan and Pyka, Andreas and Saviotti, Pier}
}
@article {2018,
	title = {The OD imperative to add inclusion to the algorithms of artificial intelligence},
	year = {2018},
	month = {01/2018},
	abstract = {This article details concerns about the potential of machine learning processes to incorporate human biases inherent in social data into artificial intelligence systems that influence consequential decisions in the courts, business and financial transactions, and employment situations. It details incidents of biased decisions and recommendations made by artificial intelligence systems that have been given the patina of objectivity because they were made by machines supposedly free of human bias. The article offers suggestions for addressing the systemic biases that are impacting the viability, credibility, and fairness of machine learning processes and artificial intelligence system.},
	url = {https://www.researchgate.net/publication/323830092_AI_x_I_AI2_The_OD_imperative_to_add_inclusion_to_the_algorithms_of_artificial_intelligence},
	author = {Frederick A. Miller and Judith H. Katz and Roger Gans}
}
@article {2018,
	title = {Reinventing capitalism to address automation: Sharing work to secure employment and income},
	journal = {Competition \& Change},
	volume = {22},
	year = {2018},
	month = {Jan-08-2020},
	pages = {343 - 362},
	issn = {1024-5294},
	doi = {10.1177/1024529418783579},
	author = {Rafi Khan, Shahrukh}
}
@book {2018,
	title = {The social consequences of the digital revolution},
	volume = {6},
	year = {2018},
	publisher = {Edizioni Ca{\textquoteright} Foscari},
	organization = {Edizioni Ca{\textquoteright} Foscari},
	address = {Venice},
	isbn = {978-88-6969-274-1},
	issn = {2610-9085},
	doi = {10.30687/2610-968910.30687/978-88-6969-273-410.30687/978-88-6969-273-4/008},
	url = {http://edizionicafoscari.unive.it/collane/societa-e-trasformazioni-sociali/http://edizionicafoscari.unive.it/libri/978-88-6969-274-1/http://edizionicafoscari.unive.it/libri/978-88-6969-274-1/the-social-consequences-of-the-digital-revolution/},
	author = {Basso, Pietro and Chiaretti, Giuliana and Krzywdzinski, Martin and Gerber, Christine and Evers, Maren}
}
@conference {2018,
	title = {Theorizing human and bot co - production effects on information quality},
	booktitle = {Thirty - n inth International Conference on Information Systems,},
	year = {2018},
	url = {https://icis2018postergallery.weebly.com/416-social-media-and-digital-collaboration.html},
	author = {Amber G. Young and Amber G. Young and Gerald C. Kane}
}
@article {2017,
	title = {AI in contact centers},
	journal = {Communications of the ACM},
	volume = {60},
	year = {2017},
	month = {Dec-07-2018},
	pages = {18 - 19},
	issn = {00010782},
	doi = {10.1145/312734310.1145/3105442},
	author = {Kirkpatrick, Keith}
}
@conference {2017,
	title = {Are We Safe Enough in the Future of Artificial Intelligence? A Discussion on Machine Ethics and Artificial Intelligence Safety},
	booktitle = {Scientific Methods in Academic Research and Teaching International Conference},
	year = {2017},
	pages = {184-197},
	abstract = {Nowadays, there is a serious anxiety on the existence of dangerous intelligent systems and it is not just a science-fiction idea of evil machines like the ones in well-known Terminator movie or any other movies including intelligent robots - machines threatening the existence of humankind. So, there is a great interest in some alternative research works under the topics of Machine Ethics, and Existential Risks. The objective of this study is to provide a general discussion about the expressed research topics and try to find some answers to the question of {\textquoteright}Are we safe enough in the future of Artificial Intelligence?{\textquoteright}. In detail, the discussion includes a comprehensive focus on {\textquoteright}dystopic{\textquoteright} scenarios, enables interested researchers to think about some {\textquoteright}moral dilemmas{\textquoteright} and family have some ethical outputs that are considerable for developing good intelligent systems. From a general perspective, the discussion taken here is a good opportunity to improve awareness on the mentioned, remarkable research topics associated with not only Artificial Intelligence but also many other natural and social sciences taking role in the humankind},
	keywords = {artificial intelligence, artificial intelligence safety, future of artificial intelligence, machine ethics, machine learning},
	author = {Utku  K{\"o}se}
}
@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 {RN30632,
	title = {Dermatologist-level classification of skin cancer with deep neural networks},
	journal = {Nature},
	volume = {542},
	number = {7639},
	year = {2017},
	pages = {115{\textendash}118},
	type = {Journal Article},
	issn = {0028-0836},
	author = {Esteva, Andre and Kuprel, Brett and Novoa, Roberto A and Ko, Justin and Swetter, Susan M and Blau, Helen M and Thrun, Sebastian}
}
@article {2017,
	title = {Do technological innovations affect unemployment? Some empirical evidence from European countries},
	journal = {Economies},
	volume = {5},
	year = {2017},
	month = {Jan-12-2017},
	pages = {48},
	doi = {10.3390/economies5040048},
	author = {Matuzeviciute, Kristina and Butkus, Mindaugas and Karaliute, Akvile}
}
@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}
}
@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 automation is changing auditing},
	journal = {Journal of Emerging Technologies in Accounting},
	volume = {14},
	year = {2017},
	month = {Jan-03-2017},
	pages = {115 - 122},
	issn = {1554-1908},
	doi = {10.2308/jeta-51730},
	author = {Kokina, Julia and Davenport, Thomas H.}
}
@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 = {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}
}
@article {2017,
	title = {Thinking critically about and researching algorithms},
	journal = {Information, Communication \& Society},
	volume = {20},
	year = {2017},
	month = {Feb-01-2017},
	pages = {14 - 29},
	keywords = {Algorithmic management},
	issn = {1369-118X},
	doi = {10.1080/1369118X.2016.1154087},
	author = {Kitchin, Rob}
}
@article {2016,
	title = {AI can show us the ravages of climate change},
	year = {2016},
	keywords = {AI use cases},
	url = {https://www.technologyreview.com/f/613547/ai-can-show-us-the-ravages-of-climate-change/},
	author = {Will Knight}
}
@article {2016,
	title = {AP Sports is using robot reporters to cover Minor League Baseball },
	year = {2016},
	url = {https://techcrunch.com/2016/07/03/ap-sports-is-using-robot-reporters-to-cover-minor-league-baseball/},
	author = {Lora Kolodny}
}
@article {2016,
	title = {How artificial intelligence will redefine management},
	year = {2016},
	month = {11/2016},
	url = {https://hbr.org/2016/11/how-artificial-intelligence-will-redefine-management},
	author = {Vegard Kolbjornsrud and Richard Amico and Robert J. Thomas}
}
@article {2016,
	title = {Robots working with humans or humans working with robots?},
	journal = {Societies},
	volume = {6},
	year = {2016},
	month = {Jan-09-2016},
	pages = {23},
	doi = {10.3390/soc6030023},
	author = {Moniz, Ant{\'o}nio and Krings, Bettina-Johanna}
}
@conference {2016,
	title = {SPIE ProceedingsAn efficient fusion approach for combining human and machine decisions},
	booktitle = {SPIE Defense + SecurityMicro- and Nanotechnology Sensors, Systems, and Applications VIII},
	volume = {9836},
	year = {2016},
	pages = {983621},
	publisher = {SPIE},
	organization = {SPIE},
	address = {Baltimore, Maryland, United States},
	doi = {10.1117/12.2220788},
	url = {http://proceedings.spiedigitallibrary.org/proceeding.aspx?doi=10.1117/12.2220788},
	author = {Lee, Hyungtae and Kwon, Heesung and Ryan M. Robinson and W. D. Nothwang and Amar R. Marathe},
	editor = {George, Thomas and Dutta, Achyut K. and Islam, M. Saif}
}
@article {2016,
	title = {Will computers put us out of work? },
	journal = {Computer},
	volume = {49},
	year = {2016},
	month = {Jan-05-2016},
	pages = {82 - 85},
	issn = {0018-9162},
	doi = {10.1109/MC.2016.126},
	author = {King, John Leslie and Grudin, Jonathan}
}
@article {RN30644,
	title = {Human-level control through deep reinforcement learning},
	journal = {Nature},
	volume = {518},
	number = {7540},
	year = {2015},
	pages = {529-533},
	type = {Journal Article},
	issn = {0028-0836},
	author = {Mnih, Volodymyr and Kavukcuoglu, Koray and Silver, David and Rusu, Andrei A and Veness, Joel and Bellemare, Marc G and Graves, Alex and Riedmiller, Martin and Fidjeland, Andreas K and Ostrovski, Georg}
}
@conference {2015,
	title = {Intelligible Models for HealthCare},
	booktitle = {the 21th ACM SIGKDD International ConferenceProceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining - KDD {\textquoteright}15},
	year = {2015},
	pages = {1721 - 1730},
	publisher = {ACM Press},
	organization = {ACM Press},
	address = {Sydney, NSW, AustraliaNew York, New York, USA},
	isbn = {9781450336642},
	doi = {10.1145/278325810.1145/2783258.2788613},
	author = {Caruana, Rich and Lou, Yin and Gehrke, Johannes and Koch, Paul and Sturm, Marc and Elhadad, Noemie}
}
@conference {2015,
	title = {Science bot: a model for the future computation},
	booktitle = {the 24th International ConferenceProceedings of the 24th International Conference on World Wide Web - WWW {\textquoteright}15 Companion},
	year = {2015},
	pages = {1061 - 1062},
	publisher = {ACM Press},
	organization = {ACM Press},
	address = {Florence, ItalyNew York, New York, USA},
	isbn = {9781450334730},
	doi = {10.1145/2740908.2742014},
	author = {Kuhn, Tobias}
}
@article {2014,
	title = {The global decline of the labor share},
	journal = {The Quarterly Journal of Economics},
	volume = {129},
	year = {2014},
	month = {Jan-02-2014},
	pages = {61 - 103},
	issn = {0033-5533},
	doi = {10.1093/qje/qjt032},
	author = {Karabarbounis, L. and Neiman, B.}
}
@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 {2011,
	title = {Approaches to understanding and measuring interdisciplinary scientific research (IDR): A review of the literature},
	journal = {Journal of Informetrics},
	volume = {5},
	year = {2011},
	month = {Jan-01-2011},
	pages = {14 - 26},
	issn = {17511577},
	doi = {10.1016/j.joi.2010.06.004},
	author = {Wagner, Caroline S. and Roessner, J. David and Bobb, Kamau and Klein, Julie Thompson and Boyack, Kevin W. and Keyton, Joann and Rafols, Ismael and B{\"o}rner, Katy}
}
@article {2011,
	title = {Is there an ethics of algorithms?},
	journal = {Ethics and Information Technology},
	volume = {13},
	year = {2011},
	month = {Jan-09-2011},
	pages = {251 - 260},
	issn = {1388-1957},
	doi = {10.1007/s10676-010-9233-7},
	author = {Kraemer, Felicitas and van Overveld, Kees and Peterson, Martin}
}
@article {2009,
	title = {Under diagnosis and referral bias of autism in ethnic minorities},
	journal = {Journal of Autism and Developmental Disorders},
	volume = {39},
	year = {2009},
	month = {Jan-01-2009},
	pages = {142 - 148},
	issn = {0162-3257},
	doi = {10.1007/s10803-008-0611-5},
	author = {Begeer, Sander and Bouk, Saloua El and Boussaid, Wafaa and Terwogt, Mark Meerum and Koot, Hans M.}
}
@booklet {2008,
	title = {How life imitates chess: Making the right moves-from the board to the boardroom},
	year = {2008},
	publisher = {Random House},
	address = {New York, NY},
	isbn = {0363-0277},
	author = {Kasparov, Garry}
}
@article {2007,
	title = {Towards a theory for multiparty proactive communication in agent teams},
	journal = {International Journal of Cooperative Information Systems},
	volume = {16},
	year = {2007},
	month = {Jan-06-2009},
	pages = {271 - 298},
	issn = {0218-8430},
	doi = {10.1142/S0218843007001640},
	author = {Kaivan Kamali and Xiaocong Fan and John Yen, JOHN}
}
@inbook {2003,
	title = {Work design},
	booktitle = {Handbook of Psychology: Industrial and Organizational Psychology},
	volume = {12},
	year = {2003},
	pages = {423{\textendash}452},
	publisher = {Wiley},
	organization = {Wiley},
	address = {Hoboken, NY},
	author = {Frederick P. Morgeson and Campion, Michael A.},
	editor = {W. Borman and Ilgen, D. and Klimoski, R.}
}
@article {RN2496,
	title = {Bringing work back in},
	journal = {Organization Science},
	volume = {12},
	number = {1},
	year = {2001},
	pages = {76{\textendash}95},
	type = {Journal Article},
	doi = {10.1287/orsc.12.1.76.10122},
	author = {Stephen R. Barley and Kunda, Gideon}
}
@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}
}
@proceedings {1995,
	title = {Integration of people, technology and organization: the european approach},
	volume = {20},
	year = {1995},
	pages = {957-961},
	publisher = {Elsevier},
	address = {Tokyo, Japan},
	abstract = {This paper presents the general outline of new method, HITOP-D, considering the integration and joint optimization of people, technology, and organization. This method is based on the existing american methods HITOP and ACTION. It takes in account the specific european industrial context. In an iterating process the preliminary design of a project is assessed according a list of criteria of the four aspects people, technology, organization, and task design. Incongruencies are solved through a fit analysis and redesigning the original project. The performance of HITOP-D will be empirically evaluated.},
	author = {Christina Kirsch and Peter Troxier and Eberhard Ulich}
}
@article {1994,
	title = {Design concepts of computer-aided integrated manufacturing systems: Work-psychological concepts and empirical findings},
	journal = {International Journal of Industrial Ergonomics},
	volume = {17},
	year = {1994},
	publisher = {Elsevier},
	chapter = {11-19},
	abstract = {The research project "GRIPS" is investigating the design of computer-aided integrated manufacturing systems from a work psychological perspective. The goal is to develop and empirically support adequate design concepts. The project consists of three phases. Evidence from a broad questionnaire survey indicates that most CIM implementations fail to meet expectations associated therewith. Based on the assumption that only the joint optimization of social and technical system results in humane working conditions and economic efficiency, implementations and use of CIM systems has been investigated in 60 companies in Switzerland. THe conceptual framework distinguishes technically-oriented and work-oriented design concepts on four levels; the enterprise, the organizational unit, the group and the individual. Work-oriented manufacturing systems - as opposed to technically-oriented ones - are characterized by decentralization, functional integration, work in self-regulated groups and complete and challenging tasks. The findings support the hypothesis that work-oriented design concepts are related to higher efficiency and better achievement of goals and pursued with the use of new technologies. In the third phase 12 companies have been selected for detailed case studies: The companies are comparable concerning product range and manufacturing conditions but different on the level of work-orientation.},
	keywords = {Computer-Integrated-Manufacturing CIM, Organizational design, Production design concepts, Socio-technical system approach, Work psychology, Work-orientation},
	author = {C. Kirsh and O. Strohm and E. Ulich}
}
