@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} } @article {9998, title = {Artificial intelligence in information systems: State of the art and research roadmap}, journal = {Communications of the Association for Information Systems (CAIS)}, volume = {50}, year = {2022}, abstract = {

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

}, doi = {10.17705/1CAIS.05017}, attachments = {https://waim.network/sites/crowston.syr.edu/files/Artificial\%20Intelligence\%20in\%20Information\%20Systems\%20State\%20of\%20the\%20Art.pdf}, author = {P{\"a}r J. {\r A}gerfalk and Kieran Conboy and Kevin Crowston and Sirkka L. Jarvenpaa and Jenny Eriksson Lundstr{\"o}m and Patrick Mikalef and Sudha Ram} } @article {Noonpakdee2020, title = {The Adoption of Artificial Intelligence for Financial Investment Service}, journal = {2020 22nd International Conference on Advanced Communication Technology (ICACT)}, year = {2020}, pages = {396{\textendash}400}, publisher = {Global IT Research Institute - GIRI}, keywords = {AI, artificial intelligence, data, financial, fintech, investment service, Technology Adoption, to investment companies, to offer customers accessibility}, isbn = {9791188428045}, author = {Noonpakdee, Wasinee} } @article {Sidaoui2020, title = {AI feel you: customer experience assessment via chatbot interviews}, journal = {Journal of Service Management}, year = {2020}, abstract = {Purpose: While customer experience (CE) is recognized as a critical determinant of business success, both academics and managers are yet to find a means to gain a comprehensive understanding of CE cost-effectively. The authors argue that the application of relevant AI technology could help address this challenge. Employing interactively prompted narrative storytelling, and the authors investigate the effectiveness of sentiment analysis (SA) on extracting valuable CE insights from primary qualitative data generated via chatbot interviews. Design/methodology/approach: Drawing on a granular and semantically clear framework for studying CE feelings, an artificial intelligence (AI) augmented chatbot was designed. The chatbot interviewed a crowdsourced sample of consumers about their recalled service experience feelings. By combining free-text and closed-ended questions, the authors were able to compare extracted sentiment polarities against established measurement scales and empirically validate our novel approach. Findings: The authors demonstrate that SA can effectively extract CE feelings from primary chatbot data. This findings also suggest that further enhancement in accuracy can be achieved via improvements in the interplay between the chatbot interviewer and SA extraction algorithms. Research limitations/implications: The proposed customer-centric approach can help service companies to study and better understand CE feelings in a cost-effective and scalable manner. The AI-augmented chatbots can also help companies to foster immersive and engaging relationships with customers. This study focuses on feelings, warranting further research on AI{\textquoteright}s value in studying other CE elements. Originality/value: The unique inquisitive role of AI-infused chatbots in conducting interviews and analyzing data in realtime, offers considerable potential for studying CE and other subjective constructs.}, keywords = {artificial intelligence, chatbot, Customer experience, Customer feelings, Sentiment analysis, Storytelling}, issn = {17575818}, doi = {10.1108/JOSM-11-2019-0341}, author = {Sidaoui, Karim and Jaakkola, Matti and Burton, Jamie} } @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 {Black2020, title = {AI-enabled recruiting: What is it and how should a manager use it?}, journal = {Business Horizons}, volume = {63}, number = {2}, year = {2020}, pages = {215{\textendash}226}, publisher = {Elsevier Ltd}, abstract = {AI-enabled recruiting systems have evolved from nice to talk about to necessary to utilize. In this article, we outline the reasons underlying this development. First, as competitive advantages have shifted from tangible to intangible assets, human capital has transitioned from supporting cast to a starring role. Second, as digitalization has redesigned both the business and social landscapes, digital recruiting of human capital has moved from the periphery to center stage. Third, recent and near-future advances in AI-enabled recruiting have improved recruiting efficiency to the point that managers ignore them or procrastinate their utilization at their own peril. In addition to explaining the forces that have pushed AI-enabled recruiting systems from nice to necessary, we outline the key strategic steps managers need to take in order to capture its main benefits.}, keywords = {AI-enabled recruiting, artificial intelligence, Digital recruiting technology, Human resources}, issn = {00076813}, doi = {10.1016/j.bushor.2019.12.001}, url = {https://doi.org/10.1016/j.bushor.2019.12.001}, author = {Black, J Stewart and van Esch, Patrick} } @conference {2020, title = {Algorithmic Journalism and Its Impacts on Work}, booktitle = {Computation + Journalism Symposium }, year = {2020}, edition = {(cancelled due to COVID; presented in 2021)}, abstract = {

In the artificial intelligence era, algorithmic journalists can produce news reports in natural language from structured data thanks to natural language generation (NLG) algorithms. This paper presents several algorithmic content generation models and discusses the impacts of algorithmic journalism on work within a framework consisting of three levels: replacing tasks of journalists, increasing efficiency, and developing new capabilities within journalism. The findings indicate that algorithmic journalism technology may lead some changes in journalism by enabling individual users to produce their own stories. This paper may contribute to an understanding of how algorithmic news is created and how algorithmic journalism technology impacts work.

}, url = {https://cpb-us-w2.wpmucdn.com/express.northeastern.edu/dist/d/53/files/2020/02/CJ_2020_paper_26.pdf}, attachments = {https://waim.network/sites/crowston.syr.edu/files/CJ_2020_paper_26.pdf}, author = {Ayse Dalgali and Kevin Crowston} } @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 {Gentili2020, title = {Are machines stealing our jobs?}, journal = {Cambridge Journal of Regions, Economy and Society}, volume = {13}, number = {1}, year = {2020}, pages = {153{\textendash}173}, abstract = {This study aims to contribute empirical evidence to the debate about the future of work in an increasingly robotised world. We implement a data-driven approach to study the technological transition in six leading Organisation for Economic Co-operation and Development (OECD) countries. First, we perform a cross-country and cross-sector cluster analysis based on the OECD-STAN database. Second, using the International Federation of Robotics database, we bridge these results with those regarding the sectoral density of robots. We show that the process of robotisation is industry- and country-sensitive. In the future, participants in the political and academic debate may be split into optimists and pessimists regarding the future of human labour; however, the two stances may not be contradictory.}, keywords = {cluster analysis, e24, e66, j24, jel classifications, labour dislocation, robotisation}, issn = {1752-1378}, doi = {10.1093/cjres/rsz025}, author = {Gentili, Andrea and Compagnucci, Fabiano and Gallegati, Mauro and Valentini, Enzo} } @book {2020, title = {Artificial Intelligence and Judicial Modernization}, year = {2020}, publisher = {Springer Singapore}, organization = {Springer Singapore}, address = {Singapore}, isbn = {978-981-32-9879-8}, doi = {10.1007/978-981-32-9880-4}, author = {Cui, Yadong} } @article {2020, title = {Artificial intelligence and the world of work, a co-constitutive relationship}, journal = {Journal of the Association for Information Science and Technology}, year = {2020}, abstract = {

The use of intelligent machines{\textemdash}digital technologies that feature data- driven forms of customization, learning, and autonomous action{\textemdash}is rapidly growing and will continue to impact many industries and domains. This is consequential for communities of researchers, educators, and practitioners concerned with studying, supporting, and educating information profes- sionals. In the face of new developments in artificial intelligence (AI), the research community faces 3 questions: (a) How is AI becoming part of the world of work? (b) How is the world of work becoming part of AI? and (c) How can the information community help address this topic of Work in the Age of Intelligent Machines (WAIM)? This opinion piece considers these 3 questions by drawing on discussion from an engaging 2019 iConference workshop organized by the NSF supported WAIM research coordination net- work (note: https://waim.network).

}, issn = {2330-1635}, doi = {10.1002/asi.24388}, author = {{\O}sterlund, Carsten and Jarrahi, Mohammad Hossein and Willis, Matthew and Boyd, Karen and Wolf, Christine} } @conference {Sushina2020, title = {Artificial Intelligence in the Criminal Justice System: Leading Trends and Possibilities}, booktitle = {Proceedings of the 6th International Conference on Social, economic, and academic leadership (ICSEAL-6-2019)}, volume = {441}, year = {2020}, pages = {432{\textendash}437}, publisher = {Atlantis Press}, organization = {Atlantis Press}, address = {Paris, France}, keywords = {artificial intelligence, criminal justice system, digital technologies, Leadership}, isbn = {978-94-6252-974-8}, doi = {10.2991/assehr.k.200526.062}, url = {https://www.atlantis-press.com/article/125940991}, author = {Sushina, Tatyana and Sobenin, Andrew} } @conference {Dietzmann2020, title = {Assessing the Business Impact of Artificial Intelligence}, booktitle = {Proceedings of the 53rd Hawaii International Conference on System Sciences}, volume = {3}, year = {2020}, pages = {5170{\textendash}5179}, abstract = {El autor propone la creaci{\'o}n de una agencia que certificque los procesos de IA. El no certificado RCO. Tambien habla de las caracter{\'\i}sticas de la IA y la dificutlad para regularlas. Sustenta cual debe ser el ente encargado de regular la IA. Tiene en cuenta la historia de la IA y su evaluci{\'o}n en el mercado.}, isbn = {9780998133133}, doi = {10.24251/hicss.2020.635}, author = {Dietzmann, Christian and Alt, Rainer} } @article {Bessen2020, title = {Automation: A Guide for Policymakers}, year = {2020}, institution = {Brookings Institute}, abstract = {

\ldots evidence that automation is causing mass unemployment, perhaps things are about to change. Some people, such as Martin Ford (2015), argue that {\textquotedblleft}this time is different.{\textquotedblright} Perhaps the rate of technological change is much more rapid with new artificial intelligence technologies \ldots

}, url = {https://www.brookings.edu/research/automation-a-guide-for-policymakers/}, author = {Bessen, James and Goos, Maarten and Salomons, Anna and van den Berge, Wiljan} } @booklet {Jha2020, title = {Automation and Radiology{\textemdash}Part 1}, howpublished = {Academic Radiology}, volume = {27}, number = {1}, year = {2020}, pages = {147{\textendash}149}, publisher = {Elsevier Inc.}, issn = {18784046}, doi = {10.1016/j.acra.2019.10.026}, url = {https://doi.org/10.1016/j.acra.2019.10.026}, author = {Jha, Saurabh} } @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 {2019, title = {AI, robots and jobs: Estimation and implications}, year = {2019}, note = {{\textbullet} What AI can and cannot do {\textbullet} Dire prediction {\textbullet} Estimation methods and results {\textbullet} Policy implications {\textbullet} Case of Singapore}, url = {https://ehelf.nu.edu.kz/wp-content/uploads/2019/06/1-Eduardo-Araral-GSPP.pdf}, author = {Eduardo Araral} } @article {2019, title = {AI{\textquoteright}s path to the present and the painful transitions along the way}, journal = {Digital Policy, Regulation and Governance}, volume = {21}, year = {2019}, month = {Jan-05-2020}, pages = {305 - 321}, issn = {2398-50382398-5038}, doi = {10.1108/DPRG-09-2018-0051}, author = {Garcia-Murillo, Martha and MacInnes, Ian} } @article {2019, title = {AI trained on decades of food research can concoct better recipes}, journal = {FlavorBot}, year = {2019}, url = {https://futurism.com/ai-food-research-better-recipes} } @article {2019, title = {AI-Assisted Decision-making in Healthcare}, journal = {Asian Bioethics Review}, volume = {11}, year = {2019}, month = {Jan-09-2019}, pages = {299 - 314}, issn = {1793-8759}, doi = {10.1007/s41649-019-00096-0}, author = {Lysaght, Tamra and Lim, Hannah Yeefen and Xafis, Vicki and Ngiam, Kee Yuan} } @article {2019, title = {AI-Based Digital Assistants}, journal = {Business \& Information Systems Engineering}, volume = {61}, year = {2019}, month = {Jan-08-2019}, pages = {535 - 544}, issn = {2363-7005}, doi = {10.1007/s12599-019-00600-8}, author = {Maedche, Alexander and Legner, Christine and Benlian, Alexander and Berger, Benedikt and Gimpel, Henner and Hess, Thomas and Hinz, Oliver and Morana, Stefan and S{\"o}llner, Matthias} } @article {2019, title = {Algorithms, artificial intelligence and automated decisions concerning workers and the risks of discrimination: the necessary collective governance of data protection}, journal = {Transfer: European Review of Labour and Research}, volume = {25}, year = {2019}, month = {Jan-11-2019}, pages = {465 - 481}, issn = {1024-2589}, doi = {10.1177/1024258919876416}, author = {Todol{\'\i}-Signes, Adri{\'a}n} } @article {2019, title = {Algorithms at War: The Promise, Peril, and Limits of Artificial Intelligence}, journal = {International Studies Review}, year = {2019}, month = {Dec-06-2020}, issn = {1521-9488}, doi = {10.1093/isr/viz025}, author = {Jensen, Benjamin M and Whyte, Christopher and Cuomo, Scott} } @article {2019, title = {Amazon{\textquoteright}s AI expansion}, journal = {AI Daily}, year = {2019}, month = {06/2019}, type = {AI}, url = {https://www.aidaily.co.uk/articles/amazons-ai-expansion}, author = {Parth Mahendra} } @article {2019, title = {The ambiguous labor market impact of automating prediction}, year = {2019}, institution = {National Bureau of Economic Research}, address = {Cambridge, MA}, doi = {10.3386/w25619}, author = {Agrawal, Ajay and Gans, Joshua and Goldfarb, Avi} } @article {2019, title = {Apple reminds us that behind the AI revolution lies an army of humans seeing our data}, journal = {Forbes}, year = {2019}, url = {https://www.forbes.com/sites/kalevleetaru/2019/07/30/apple-reminds-us-that-behind-the-ai-revolution-lies-an-army-of-humans-seeing-our-data/$\#$3dd2e8ba339d}, author = {Kalev Leetaru} } @article {2019, title = {Applications of artificial intelligence to imaging and diagnosis}, journal = {Biophysical Reviews}, volume = {11}, year = {2019}, month = {Jan-02-2019}, pages = {111 - 118}, issn = {1867-2450}, doi = {10.1007/s12551-018-0449-9}, author = {Nichols, James A. and Herbert Chan, Hsien W. and Baker, Matthew A. B.} } @article {2019, title = {Applying for your next job may be an automated nightmare}, journal = {Gizmodo}, year = {2019}, month = {04/2019}, type = {Automation}, keywords = {automation, job}, url = {https://gizmodo.com/applying-for-your-next-job-may-be-an-automated-nightmar-1834275825}, author = {Brian Merchant} } @article {2019, title = {Are robots competing for your job? }, journal = {The New Yorker}, year = {2019}, month = {03/2019}, type = {Annals of Technology}, url = {https://www.newyorker.com/magazine/2019/03/04/are-robots-competing-for-your-job}, author = {Jill Lepore} } @article {2019, title = {Are robots stealing our jobs? }, journal = {Socius: Sociological Research for a Dynamic World}, volume = {5}, year = {2019}, month = {Oct-01-2019}, pages = {237802311984624}, issn = {2378-0231}, doi = {10.1177/2378023119846249}, author = {Dahlin, Eric} } @article {2019, title = {Is an army of robots marching on Chinese jobs? }, journal = {IZA {\textendash} Institute of Labor Economics}, year = {2019}, month = {04/2019}, url = {https://www.iza.org/publications/dp/12281/is-an-army-of-robots-marching-on-chinese-jobs}, author = {Osea Giuntella and Tianyi Wang} } @article {2019, title = {Artificial intelligence and big data in entrepreneurship: a new era has begun}, journal = {Small Business Economics}, year = {2019}, month = {Jun-06-2019}, issn = {0921-898X}, doi = {10.1007/s11187-019-00202-4}, author = {Obschonka, Martin and Audretsch, David B.} } @article {2019, title = {Artificial Intelligence and Deep Learning: The Future of Medicine and Medical Practice}, journal = { Journal of The Association of Physicians of India ■ Vol. 67 }, year = {2019}, month = {05/2019}, url = {https://www.semanticscholar.org/paper/Artificial-Intelligence-and-Deep-Learning\%3A-The-of-Sanal-Paul/795dc72decfb12389bbf7076d82fef70421b9933}, author = {Madhusudana Girija Sanal and Kolin Paul and Senthil Kumar and Nirmal Kumar Gangul} } @article {2019, title = {Artificial intelligence and the future of labor demand}, year = {2019}, institution = {National Bureau of Economic Research}, address = {Cambridge, MA}, doi = {10.3386/w25682}, author = {Acemoglu, Daron and Restrepo, Pascual} } @article {2019, title = {Artificial Intelligence and the Future of the Drug Safety Professional}, journal = {Drug Safety}, volume = {42}, year = {2019}, month = {Jan-04-2019}, pages = {491 - 497}, issn = {0114-5916}, doi = {10.1007/s40264-018-0746-z}, author = {Danysz, Karolina and Cicirello, Salvatore and Mingle, Edward and Assuncao, Bruno and Tetarenko, Niki and Mockute, Ruta and Abatemarco, Danielle and Widdowson, Mark and Desai, Sameen} } @article {2019, title = {Artificial intelligence conquers starcraft II in {\textquoteright}unimaginably unusual{\textquoteright} AI breakthrough}, journal = {Independent}, year = {2019}, url = {https://www.independent.co.uk/life-style/gadgets-and-tech/gaming/artificial-intelligence-starcraft-2-ai-deepmind-a9176601.html}, author = {Anthony Cuthbertson} } @article {2019, title = {Artificial Intelligence in FinTech: understanding robo-advisors adoption among customers}, journal = {Industrial Management \& Data Systems}, volume = {119}, year = {2019}, month = {Dec-08-2019}, pages = {1411 - 1430}, issn = {0263-5577}, doi = {10.1108/IMDS-08-2018-0368}, author = {Belanche, Daniel and Casal{\'o}, Luis V. and Flavi{\'a}n, Carlos} } @article {2019, title = {Artificial intelligence in medicine: What is it doing for us today?}, journal = {Health Policy and Technology}, volume = {8}, year = {2019}, month = {Jan-06-2019}, pages = {198 - 205}, issn = {22118837}, doi = {10.1016/j.hlpt.2019.03.004}, author = {Becker, Aliza} } @article {2019, title = {Artificial intelligence in workplaces and how it will affect employment in Latvia}, journal = {Environment. Technology. Resources. Proceedings of the International Scientific and Practical Conference}, volume = {2}, year = {2019}, month = {Aug-06-2020}, pages = {154}, issn = {1691-5402}, doi = {10.17770/etr2019vol2.4151}, author = {{\v S}ukjurovs, Ilm{\={a}}rs and Zvirgzdina, Rosita and Jeromanova-Maura, Silva} } @article {2019, title = {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} } @article {2019, title = {Automation and new tasks: How technology displaces and reinstates labor}, year = {2019}, institution = {National Bureau of Economic Research}, address = {Cambridge, MA}, doi = {10.3386/w25684}, author = {Acemoglu, Daron and Restrepo, Pascual} } @article {2019, title = {Automation as Part of the Solution}, journal = {Journal of Management Inquiry}, volume = {28}, year = {2019}, month = {Jun-07-2021}, pages = {316 - 318}, issn = {1056-4926}, doi = {10.1177/1056492619827375}, author = {Levine, David I.} } @article {2019, title = {Automation, wage inequality and implications of a robot tax}, journal = {International Review of Economics \& Finance}, volume = {59}, year = {2019}, month = {Jan-01-2019}, pages = {500 - 509}, issn = {10590560}, doi = {10.1016/j.iref.2018.10.013}, author = {Zhang, Pengqing} } @article {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} } @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} } @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 = {A.I. And big data could power a new war on poverty}, year = {2018}, month = {01/2018}, url = {https://www.nytimes.com/2018/01/01/opinion/ai-and-big-data-could-power-a-new-war-on-poverty.html}, author = {Elisabeth a. Mason} } @article {2018, title = {AI and the Economy}, year = {2018}, institution = {National Bureau of Economic Research}, address = {Cambridge, MA}, doi = {10.3386/w24689}, author = {Furman, Jason and Seamans, Robert} } @conference {2018, title = {AI Assistants as Non-human Actors in Service Design}, booktitle = {21st DMI: Academic Design Management Conference}, year = {2018}, url = {https://www.researchgate.net/publication/326997609_AI_Assistants_as_Non-human_Actors_in_Service_Design?enrichId=rgreq-80a84e881501993f8b87a3d6387900aa-XXX\&enrichSource=Y292ZXJQYWdlOzMyNjk5NzYwOTtBUzo2NTkyMjU4MjI5MTY2MTBAMTUzNDE4MzA5Mjk2MQ\%3D\%3D\&el=1_x_2\&_}, author = {TiTitta Jylkastta Jylk{\"a}s and Mikko {\"A}ij{\"a}l{\"a} and Tytti Vuorikari and V{\'e}saal Rajab} } @article {2018, title = {AI: Augmentation, more so than automation}, year = {2018}, publisher = {Singapore Management University}, issn = {2315-4284}, url = {https://cmp.smu.edu.sg/ami/all}, author = {Steven Miller} } @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 = {AI is coming after highly skilled jobs, and it{\textquoteright}s meeting resistance}, journal = {venturebeat}, year = {2018}, keywords = {AI}, url = {https://venturebeat.com/2018/03/04/ai-is-coming-after-highly-skilled-jobs-and-its-meeting-resistance/}, author = {Sascha Eder} } @conference {2018, title = {AI risk mitigation through democratic governance}, booktitle = {the 2018 AAAI/ACM ConferenceProceedings of the 2018 AAAI/ACM Conference on AI, Ethics, and Society - AIES {\textquoteright}18}, year = {2018}, pages = {366 - 367}, publisher = {ACM Press}, organization = {ACM Press}, address = {New Orleans, LA, USANew York, New York, USA}, isbn = {9781450360128}, doi = {10.1145/3278721.3278801}, author = {Garvey, Colin} } @article {2018, title = {AI stumbles in the spotlight}, year = {2018}, note = {Artificial intelligence experts {\textemdash} concerned about reported blunders with high-stakes AI systems from makers like Amazon and IBM {\textemdash} are urging more oversight, testing, and perhaps a fundamental rethinking of the underlying technology.}, url = {https://www.axios.com/artificial-intelligence-mistakes-limitations-amazon-ibm-14014597-03e9-43e3-b224-a91205a232c1.html}, author = {Kaveh Waddell} } @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.} } @mastersthesis {2018, title = {Archetypes of artificial intelligence utilization}, year = {2018}, note = {How companies create and capture value from a novel business technology}, url = {https://aaltodoc.aalto.fi/handle/123456789/33983}, author = {Selim Saukkomaa} } @article {2018, title = {Are You Working with AI or Being Replaced by AI?}, journal = {Radiology}, volume = {287}, year = {2018}, month = {Jan-05-2018}, pages = {365 - 366}, issn = {0033-8419}, doi = {10.1148/radiol.2018184007}, author = {Bluemke, David A.} } @conference {2018, title = {Artificial General Intelligence}, year = {2018}, url = {https://ivizlab.org/wp-content/uploads/sites/2/2018/09/TurnerDiPaola_2018_ArtificialGeneralIntelligence.pdf}, author = {Matthew Ikl{\'e} and Arthur Franz and Rafal Rzepka and Ben Goertzel} } @article {2018, title = {Artificial Intelligence: A Case Study on Risk Mitigation}, journal = {International Journal of Computer Science and Network Security}, volume = {18}, year = {2018}, month = {04/2018}, pages = {9-12}, abstract = {Artificial intelligence technologies are expanding at an extraordinary rate with wide range of applications from machine translation to medical image analysis. Many applications are being developed and there is no doubt that in the near future this will create substantial risk for humanity. In addition, Artificial intelligence is a dual use are of technology as it can be used toward useful of harmful ends, for example autonomous drones can be used to deliver packages faster and easier and on the other hand, they can be used to deliver explosives. This literature review research investigates different types of artificial intelligence risks and proposes ways to mitigate these risks.}, keywords = {AI application, artificial intelligence, Risk mitigation}, author = {Ahmed AL-Gindy} } @article {2018, title = {Artificial intelligence and privacy in the fourth industrial revolution}, year = {2018}, institution = {Institute for Philosophy \& Public Policy}, url = {https://www.wilsoncenter.org/sites/default/files/ai_and_privacy.pdf}, author = {Sarah W. Denton and Eleonore Pauwels} } @article {2018, title = {Artificial intelligence and sports journalism: Is it a sweeping change?}, journal = {Technology in Society}, year = {2018}, issn = {0160791X}, doi = {10.1016/j.techsoc.2018.03.001}, author = {Yair Galily} } @article {2018, title = {Artificial intelligence and the future of work: Human-AI symbiosis in organizational decision making}, journal = {Business Horizons}, volume = {61}, year = {2018}, publisher = {Elsevier}, edition = {586}, chapter = {577}, abstract = {Artificial intelligence (AI) has penetrated many organizational processes, resulting in a growing fear that smart machines will soon replace many humans in decision making. To provide a more proactive and pragmatic perspective, this article highlights the complementarity of humans and AI and examines how each can bring their own strength in organizational decision-making process typically characterized by uncertainty, complexity, and equivocality. WIth a greater computational information processing capacity and an analytical approach, AI can extend humans{\textquoteright} cognition when addressing complexity, whereas human can still offer a more holistic, intuitive approach in dealing with uncertainty and equivocality in organizational decision making. This premise mirrors the idea of intelligence augmentation, which states that AI systems should be designed with the intention of augmenting, not replacing, human contribution.}, keywords = {Analytical and intuitive decision making, artificial intelligence, Human augmentation, Human-machine symbiosis, Organization decision making}, doi = {10.1016/j.bushor.2018.03.007}, author = {Mohammad Hossein Jarrahi} } @article {2018, title = {Artificial intelligence and the future of work: Human-AI symbiosis in organizational decision making}, journal = {Business Horizons}, volume = {61}, year = {2018}, month = {Jan-07-2018}, pages = {577 - 586}, issn = {00076813}, doi = {10.1016/j.bushor.2018.03.007}, author = {Jarrahi, Mohammad Hossein} } @conference {2018, title = {Artificial Intelligence Applications and Innovations}, booktitle = {14th IFIP WG 12.5 International Conference, AIAI 2018}, year = {2018}, url = {https://www.springer.com/gp/book/9783319920153}, author = {Lazaros Iliadis and Ilias Maglogiannis and Vassilis Plagianakos} } @article {2018, title = {Artificial intelligence can transform the economy}, year = {2018}, month = {09/2018}, url = {https://www.washingtonpost.com/opinions/artificial-intelligence-can-transform-the-economy/2018/09/18/50c9c9c8-bab8-11e8-bdc0-90f81cc58c5d_story.html}, author = {Erik Brynjolfsson and Xiang Hui and Meng Liu} } @book {2018, title = {Artificial Intelligence Does Not Exist: Lessons from Shared Cognition and the Opposition to the Nature/Nurture Divide}, volume = {537}, year = {2018}, pages = {359 - 373}, publisher = {Springer International Publishing}, organization = {Springer International Publishing}, address = {Cham}, isbn = {978-3-319-99604-2}, issn = {1868-4238}, doi = {10.1007/978-3-319-99605-9_27}, author = {Vassilis Galanos}, editor = {Kreps, David and Ess, Charles and Leenen, Louise and Kimppa, Kai} } @book {2018, title = {Artificial Intelligence Does Not Exist: Lessons from Shared Cognition and the Opposition to the Nature/Nurture Divide}, volume = {537}, year = {2018}, pages = {359 - 373}, publisher = {Springer International Publishing}, organization = {Springer International Publishing}, address = {Cham}, isbn = {978-3-319-99604-2}, issn = {1868-4238}, doi = {10.1007/978-3-319-99605-9_27}, author = {Vassilis Galanos}, editor = {Kreps, David and Ess, Charles and Leenen, Louise and Kimppa, Kai} } @conference {2018, title = {Artificial Intelligence Does Not Exist: Lessons from Shared Cognition and the Opposition to the Nature/Nurture Divide}, booktitle = {IFIP International Conference on Human Choice and Computers}, year = {2018}, url = {https://doi.org/10.1007/978-3-319-99605-9_27}, author = {Vassilis Galanos} } @article {2018, title = {Artificial intelligence for the public sector: opportunities and challenges of cross-sector collaboration}, journal = {Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences}, volume = {376}, year = {2018}, month = {Jan-09-2019}, pages = {20170357}, issn = {1364-503X}, doi = {10.1098/rsta.2017.0357}, author = {Mikhaylov, Slava Jankin and Esteve, Marc and Campion, Averill} } @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 Cardiology}, journal = {Journal of the American College of Cardiology}, volume = {71}, year = {2018}, month = {Jan-06-2018}, pages = {2668 - 2679}, issn = {07351097}, doi = {10.1016/j.jacc.2018.03.521}, author = {Johnson, Kipp W. and Torres Soto, Jessica and Glicksberg, Benjamin S. and Shameer, Khader and Miotto, Riccardo and Ali, Mohsin and Ashley, Euan and Joel T. Dudley} } @article {2018, title = {Artificial Intelligence in Medicine and Radiation Oncology}, journal = {Cureus}, year = {2018}, month = {Jan-04-2019}, abstract = {Artificial Intelligence (AI) was reviewed with a focus on its potential applicability to radiation oncology. The improvement of process efficiencies and the prevention of errors were found to be the most significant contributions of AI to radiation oncology. It was found that the prevention of errors is most effective when data transfer processes were automated and operational decisions were based on logical or learned evaluations by the system. It was concluded that AI could greatly improve the efficiency and accuracy of radiation oncology operations.}, keywords = {artificial intelligence, big data, error analysis, error prevention, machine learning, process efficiency, process optimization, quality improvement, radiation oncology}, doi = {10.7759/cureus.2475}, url = {https://www.cureus.com/articles/11443-artificial-intelligence-in-medicine-and-radiation-oncology}, author = {Weidlich, Vincent and Weidlich, Georg A.} } @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 in the computer-age threatens human beings and working conditions at workplaces}, journal = {Electronics Science Technology and Application}, volume = {5}, year = {2018}, month = {Feb-08-2019}, issn = {2251-2608}, doi = {10.18686/esta.v5i3.76}, author = {Saithibvongsa, Phothong and Yu, Jae Eon} } @mastersthesis {2018, title = {Artificial Intelligence In The Sport Industry}, year = {2018}, url = {https://www.politesi.polimi.it/bitstream/10589/142501/1/ARTIFICIAL\%20INTELLIGENCE\%20IN\%20THE\%20SPORT\%20INDUSTRY_JACOPO\%20MOSELE.pdf}, author = {Jacopo Mosele} } @article {2018, title = {Artificial Intelligence Is Automating Hollywood}, year = {2018}, month = {07/2018}, keywords = {AI use cases}, url = {https://futurism.com/artificial-intelligence-automating-hollywood-art}, author = {Dan Robitzki} } @article {2018, title = {Artificial intelligence, jobs, inequality and productivity: Does aggregate demand matter}, number = {ISSN 1871-9872}, year = {2018}, publisher = {Maastricht University}, keywords = {artificial intelligence, economics of automation, growth theory, innovation, labour demand, productivity, technology}, url = {http://ftp.iza.org/dp12005.pdf}, author = {Thomas Gries and Wim Naude} } @article {2018, title = {Artificial intelligence, machine learning and health systems}, journal = {Journal of Global Health}, volume = {8}, year = {2018}, month = {Sep-10-2019}, issn = {2047-2978}, doi = {10.7189/jogh.08.020303}, author = {Panch, Trishan and Szolovits, Peter and Atun, Rifat} } @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} } @conference {2018, title = {Assisting tourism in rural Southern Africa using machine learning}, year = {2018}, publisher = {IEEE}, organization = {IEEE}, abstract = {Tourism is a major contributor to employment in southern Africa and a major contributor to gross domestic products of many southern African countries. One of the major tourist attractions in many southern African countries is the wild animals. Major national parks such as Etosha in Namibia and Central Kalahari in Botswana often have rangers available to assist tourists on their game safaris by recognising animals and describing their habitats. Many of the smaller reserves, however, do not have the luxury of rangers available to tourists. At such smaller reserves, tourists are left on their own to recognise the various animals. This paper describes the use of Google{\textquoteright}s TensorFlow to create an image recogniser trained for southern African mammals. The recogniser was embedded in an Android mobile app and could then assist tourists at smaller reserves.}, url = {https://ieeexplore.ieee.org/document/8465441}, author = {Laurie Butgereit and Laura Martinus} } @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 = {Automating the black art: Creative places for artificial intelligence in audio mastering}, journal = {Geoforum}, volume = {96}, year = {2018}, pages = {77-86}, issn = {00167185}, doi = {10.1016/j.geoforum.2018.08.005}, url = {https://linkinghub.elsevier.com/retrieve/pii/S0016718518302392}, author = {Birtchnell, Thomas and Elliott, Anthony} } @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 = {Automation and the future of work}, journal = {Centre for International Governance Innovation}, year = {2018}, url = {https://www.cigionline.org/publications/automation-and-future-work-scenarios-and-policy-options}, author = {Joel Blit and Samantha St. Amand and Joanna Wajda} } @article {2018, title = {Is automation labor-displacing? Productivity growth, employment, and the labor share}, year = {2018}, institution = {National Bureau of Economic Research}, address = {Cambridge, MA}, doi = {10.3386/w24871}, author = {Autor, David and Salomons, Anna} } @article {2018, title = {Automation, taxes and transfers with international rivalry}, year = {2018}, publisher = {Australian National University}, keywords = {automation, global modelling, income distribution, taxes, transfers}, issn = {2206-0332}, url = {https://cama.crawford.anu.edu.au/sites/default/files/publication/cama_crawford_anu_edu_au/2018-09/44_2018_tyers_zhou.pdf}, author = {Rod Tyers and Yixiao Zhou} } @article {seidel2018autonomous, title = {Autonomous tools and design: a triple-loop approach to human-machine learning}, journal = {Communications of the ACM}, volume = {62}, year = {2018}, pages = {50{\textendash}57}, publisher = {ACM}, author = {Seidel, Stefan and Berente, Nicholas and Lindberg, Aron and Lyytinen, Kalle and Jeffrey V Nickerson} } @article {seidel2018autonomous, title = {Autonomous Tools in System Design: Reflective Practice in Ubisofts Ghost Recon Wildlands Project}, journal = {Computer}, volume = {51}, year = {2018}, pages = {16{\textendash}23}, publisher = {IEEE}, author = {Seidel, Stefan and Berente, Nicholas and Martinez, Beno\^{\i}t and Lindberg, Aron and Lyytinen, Kalle and Jeffrey V Nickerson} } @article {2018, title = {Autonomous trucks and the future of the american trucker}, year = {2018}, month = {09/2018}, url = {https://www.steveviscelli.com/self-driving-trucks}, author = {Steve Viscelli} } @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} } @inbook {2017, title = {Agents as collaborating team members}, year = {2017}, month = {09/2017}, publisher = {EBSCO}, organization = {EBSCO}, keywords = {bots}, url = {https://www.taylorfrancis.com/books/e/9781315593166/chapters/10.1201/9781315593166-7}, author = {Abhijit V. Deshmukh and Sara A.McComb and Christian Wernz} } @article {2017, title = {AI AND THE GHOST IN THE MACHINE}, year = {2017}, url = {http://hackaday.com/2017/02/06/ai-and-the-ghost-in-the-machine/}, author = {Cameron Coward} } @article {2017, title = {AI can take over our mundane tasks}, year = {2017}, month = {10/2017}, abstract = {

Here{\textquoteright}s how human workers can learn new, more stimulating skills

}, url = {https://www.vox.com/2017/10/18/16492156/coaching-cloud-future-work-jobs-artificial-intelligence-ai-enterprise-employee-training}, author = {Gordon Ritter} } @article {2017, title = {The AI detectives}, volume = {357}, year = {2017}, month = {Jul-07-2017}, pages = {22 - 27}, issn = {0036-8075}, doi = {10.1126/science.357.6346.22}, author = {Voosen, Paul} } @article {2017, title = {AI has become so popular in picking stocks that it{\textquoteright}s become ineffective}, year = {2017}, note = {

Everyone mining the similar data, neutralizing its alpha

}, month = {10/2017}, url = {https://www.marketwatch.com/story/ai-has-become-so-popular-in-picking-stocks-that-its-become-ineffective-2017-10-06}, author = {Ryan Vlastelica} } @article {2017, title = {AI in Action: Combing the genome for the roots of autism}, journal = {Science}, volume = {357}, year = {2017}, month = {Jul-07-2017}, pages = {25 - 25}, issn = {0036-8075}, doi = {10.1126/science.357.6346.25}, author = {Pennisi, Elizabeth} } @article {2017, title = {AI in Action: Machines that make sense of the sky}, journal = {Science}, volume = {357}, year = {2017}, month = {Jul-07-2017}, pages = {26 - 26}, issn = {0036-8075}, doi = {10.1126/science.357.6346.26}, author = {Sokol, Joshua} } @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} } @article {2017, title = {AI will create 800,000 jobs and $1.1 trillion revenue by 2021: Salesforce}, journal = {salesforce}, year = {2017}, month = {06/2017}, type = {AI}, url = {https://www.salesforce.com/company/news-press/press-releases/2017/06/170614/}, author = {Tas Bindi} } @article {2017, title = {Algorithmic IF {\textellipsis} THEN rules and the conditions and consequences of power}, journal = {Information, Communication \& Society}, volume = {20}, year = {2017}, month = {Feb-01-2017}, pages = {45 - 62}, issn = {1369-118X}, doi = {10.1080/1369118X.2016.1156141}, author = {Neyland, Daniel and M{\"o}llers, Norma} } @article {2017, title = {The algorithmic imaginary: Exploring the ordinary affects of Facebook algorithms}, journal = {Information, Communication \& Society}, volume = {20}, year = {2017}, month = {Feb-01-2017}, pages = {30 - 44}, issn = {1369-118X}, doi = {10.1080/1369118X.2016.1154086}, author = {Bucher, Taina} } @article {2017, title = {Algorithmically recognizable: Santorum{\textquoteright}s google problem, and google{\textquoteright}s santorum problem}, journal = {Information, Communication \& Society}, volume = {20}, year = {2017}, month = {Feb-01-2017}, pages = {63 - 80}, issn = {1369-118X}, doi = {10.1080/1369118X.2016.1199721}, author = {Gillespie, Tarleton} } @article {2017, title = {Algorithms (and the) everyday}, journal = {Information, Communication \& Society}, volume = {20}, year = {2017}, month = {Feb-01-2017}, pages = {137 - 150}, issn = {1369-118X}, doi = {10.1080/1369118X.2016.1200645}, author = {Willson, Michele} } @article {2017, title = {Anxiety about automation and jobs: Will we see anti-tech laws?}, journal = {AEIdeas}, year = {2017}, month = {07/2017}, type = {economics}, url = {https://www.aei.org/economics/anxiety-about-automation-and-jobs-will-we-see-anti-tech-laws/}, author = {James Pethokoukis} } @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} } @article {2017, title = {Artificial intelligence and the modern productivity paradox: a clash of expectations and statistics}, number = {24001}, year = {2017}, month = {11/2017}, keywords = {economics of automation}, url = {http://www.nber.org/papers/w24001}, author = {Erik Brynjolfsson and Daniel Rock and Chad Syverson} } @book {2017, title = {Artificial Intelligence and the two singularities}, series = {A Chapman \& Hall Book}, year = {2017}, month = {08/2018}, publisher = {EBSCO}, organization = {EBSCO}, edition = {1st}, url = {https://www.amazon.com/Artificial-Intelligence-Singularities-Chapman-Robotics/dp/0815368534}, author = {Calum Chace} } @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. 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