IDEAS home Printed from https://ideas.repec.org/a/inm/orisre/v32y2021i3p675-687.html
   My bibliography  Save this article

Editorial for the Special Section on Humans, Algorithms, and Augmented Intelligence: The Future of Work, Organizations, and Society

Author

Listed:
  • Hemant Jain

    (Gary W. Rollins College of Business, University of Tennessee – Chattanooga, Chattanooga, Tennessee 37403)

  • Balaji Padmanabhan

    (Muma College of Business, University of South Florida, Tampa, Florida 33620)

  • Paul A. Pavlou

    (C.T. Bauer College of Business, University of Houston, Houston, Texas 77204)

  • T. S. Raghu

    (W.P. Carey School of Business, Arizona State University, Tempe, Arizona 85287)

Abstract

Recent developments in artificial intelligence (AI) have increased interest in combining AI with human intelligence to develop superior systems that augment human and artificial intelligence. In this paper, augmented intelligence informally means computers and humans working together, by design, to enhance one another, such that the intelligence of the resulting system improves. Intelligence augmentation (IA) can pool the joint intelligence of humans and computers to transform individual work, organizations, and society. Notably, applications of IA are beginning to emerge in several domains, such as cybersecurity, privacy, counterterrorism, and healthcare, among others. We provide a brief summary of papers in this special section that represent early attempts to address some of the rapidly emerging research issues. We also present a framework to guide research on IA and advocate for the important implications of IA for the future of work, organizations, and society. We conclude by outlining promising research directions based on this framework for the information systems and related disciplines.

Suggested Citation

  • Hemant Jain & Balaji Padmanabhan & Paul A. Pavlou & T. S. Raghu, 2021. "Editorial for the Special Section on Humans, Algorithms, and Augmented Intelligence: The Future of Work, Organizations, and Society," Information Systems Research, INFORMS, vol. 32(3), pages 675-687, September.
    • Handle: RePEc:inm:orisre:v:32:y:2021:i:3:p:675-687
    DOI: 10.1287/isre.2021.1046
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/isre.2021.1046
    Download Restriction: no
    File URL: https://libkey.io/10.1287/isre.2021.1046?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Hilal Atasoy & Rajiv D. Banker & Paul A. Pavlou, 2016. "On the Longitudinal Effects of IT Use on Firm-Level Employment," Information Systems Research, INFORMS, vol. 27(1), pages 6-26, March.
    2. Dan Ariely & Anat Bracha & Stephan Meier, 2009. "Doing Good or Doing Well? Image Motivation and Monetary Incentives in Behaving Prosocially," American Economic Review, American Economic Association, vol. 99(1), pages 544-555, March.
    3. Junming Yin & Jerry Luo & Susan A. Brown, 2021. "Learning from Crowdsourced Multi-labeling: A Variational Bayesian Approach," Information Systems Research, INFORMS, vol. 32(3), pages 752-773, September.
    4. David H. Autor & David Dorn, 2013. "The Growth of Low-Skill Service Jobs and the Polarization of the US Labor Market," American Economic Review, American Economic Association, vol. 103(5), pages 1553-1597, August.
    5. T. S. Raghu & R. Ramesh & Ai-Mei Chang & Andrew B. Whinston, 2001. "Collaborative Decision Making: A Connectionist Paradigm for Dialectical Support," Information Systems Research, INFORMS, vol. 12(4), pages 363-383, December.
    6. Daron Acemoglu & Pascual Restrepo, 2019. "Automation and New Tasks: How Technology Displaces and Reinstates Labor," Journal of Economic Perspectives, American Economic Association, vol. 33(2), pages 3-30, Spring.
    7. Marios Kokkodis, 2021. "Dynamic, Multidimensional, and Skillset-Specific Reputation Systems for Online Work," Information Systems Research, INFORMS, vol. 32(3), pages 688-712, September.
    8. Frey, Carl Benedikt & Osborne, Michael A., 2017. "The future of employment: How susceptible are jobs to computerisation?," Technological Forecasting and Social Change, Elsevier, vol. 114(C), pages 254-280.
    9. Thomas W. Malone, 1987. "Modeling Coordination in Organizations and Markets," Management Science, INFORMS, vol. 33(10), pages 1317-1332, October.
    10. Roger Clarke & Andrew Burton-Jones & Ron Weber, 2016. "On the Ontological Quality and Logical Quality of Conceptual-Modeling Grammars: The Need for a Dual Perspective," Information Systems Research, INFORMS, vol. 27(2), pages 365-382, June.
    11. Georg Meyer & Gediminas Adomavicius & Paul E. Johnson & Mohamed Elidrisi & William A. Rush & JoAnn M. Sperl-Hillen & Patrick J. O'Connor, 2014. "A Machine Learning Approach to Improving Dynamic Decision Making," Information Systems Research, INFORMS, vol. 25(2), pages 239-263, June.
    12. Michel Benaroch, 2018. "Real Options Models for Proactive Uncertainty-Reducing Mitigations and Applications in Cybersecurity Investment Decision Making," Information Systems Research, INFORMS, vol. 29(2), pages 315-340, June.
    13. Ruyi Ge & Zhiqiang (Eric) Zheng & Xuan Tian & Li Liao, 2021. "Human–Robot Interaction: When Investors Adjust the Usage of Robo-Advisors in Peer-to-Peer Lending," Information Systems Research, INFORMS, vol. 32(3), pages 774-785, September.
    14. Jay R. Galbraith, 1974. "Organization Design: An Information Processing View," Interfaces, INFORMS, vol. 4(3), pages 28-36, May.
    15. Hilal Atasoy & Rajiv D. Banker & Paul A. Pavlou, 2021. "Information Technology Skills and Labor Market Outcomes for Workers," Information Systems Research, INFORMS, vol. 32(2), pages 437-461, June.
    16. Kate Crawford & Ryan Calo, 2016. "There is a blind spot in AI research," Nature, Nature, vol. 538(7625), pages 311-313, October.
    17. David Silver & Aja Huang & Chris J. Maddison & Arthur Guez & Laurent Sifre & George van den Driessche & Julian Schrittwieser & Ioannis Antonoglou & Veda Panneershelvam & Marc Lanctot & Sander Dieleman, 2016. "Mastering the game of Go with deep neural networks and tree search," Nature, Nature, vol. 529(7587), pages 484-489, January.
    18. Vasant Dhar & Tomer Geva & Gal Oestreicher-Singer & Arun Sundararajan, 2014. "Prediction in Economic Networks," Information Systems Research, INFORMS, vol. 25(2), pages 264-284, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ulrich Gnewuch & Stefan Morana & Oliver Hinz & Ralf Kellner & Alexander Maedche, 2024. "More Than a Bot? The Impact of Disclosing Human Involvement on Customer Interactions with Hybrid Service Agents," Information Systems Research, INFORMS, vol. 35(3), pages 936-955, September.
    2. Erdem Dogukan Yilmaz & Christian Peukert, 2024. "Who Benefits from AI? Project-Level Evidence on Labor Demand, Operations and Profitability," CESifo Working Paper Series 11321, CESifo.
    3. Premilla D’Cruz & Shuili Du & Ernesto Noronha & K. Praveen Parboteeah & Hannah Trittin-Ulbrich & Glen Whelan, 2022. "Technology, Megatrends and Work: Thoughts on the Future of Business Ethics," Journal of Business Ethics, Springer, vol. 180(3), pages 879-902, October.
    4. Martin Adam & Konstantin Roethke & Alexander Benlian, 2023. "Human vs. Automated Sales Agents: How and Why Customer Responses Shift Across Sales Stages," Information Systems Research, INFORMS, vol. 34(3), pages 1148-1168, September.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Dawei (David) Zhang & Gang Peng & Yuliang Yao & Tyson R. Browning, 2024. "Is a College Education Still Enough? The IT-Labor Relationship with Education Level, Task Routineness, and Artificial Intelligence," Information Systems Research, INFORMS, vol. 35(3), pages 992-1010, September.
    2. Montobbio, Fabio & Staccioli, Jacopo & Virgillito, Maria Enrica & Vivarelli, Marco, 2022. "Robots and the origin of their labour-saving impact," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    3. Gries, Thomas & Naudé, Wim, 2022. "Modelling artificial intelligence in economics," Journal for Labour Market Research, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], vol. 56, pages 1-12.
    4. Belloc, Filippo & Burdin, Gabriel & Cattani, Luca & Ellis, William & Landini, Fabio, 2022. "Coevolution of job automation risk and workplace governance," Research Policy, Elsevier, vol. 51(3).
    5. Usabiaga, Carlos & Núñez, Fernando & Arendt, Lukasz & Gałecka-Burdziak, Ewa & Pater, Robert, 2022. "Skill requirements and labour polarisation: An association analysis based on Polish online job offers," Economic Modelling, Elsevier, vol. 115(C).
    6. Krenz, Astrid & Prettner, Klaus & Strulik, Holger, 2021. "Robots, reshoring, and the lot of low-skilled workers," European Economic Review, Elsevier, vol. 136(C).
    7. Christenko, Aleksandr, 2022. "Automation and occupational mobility: A task and knowledge-based approach," Technology in Society, Elsevier, vol. 70(C).
    8. López Noria Gabriela, 2021. "Effects of Trade and Technology on the Mexican Labor Market," Working Papers 2021-22, Banco de México.
    9. Kostøl, Fredrik B. & Svarstad, Elin, 2023. "Trade Unions and the Process of Technological Change," Labour Economics, Elsevier, vol. 84(C).
    10. Fierro, Luca Eduardo & Caiani, Alessandro & Russo, Alberto, 2022. "Automation, Job Polarisation, and Structural Change," Journal of Economic Behavior & Organization, Elsevier, vol. 200(C), pages 499-535.
    11. Zhang, Xinchun & Sun, Murong & Liu, Jianxu & Xu, Aijia, 2024. "The nexus between industrial robot and employment in China: The effects of technology substitution and technology creation," Technological Forecasting and Social Change, Elsevier, vol. 202(C).
    12. Azio Barani, 2021. "Innovazione tecnologica e lavoro: automazione, occupazione e impatti socio-economici," QUADERNI DI ECONOMIA DEL LAVORO, FrancoAngeli Editore, vol. 0(114), pages 51-79.
    13. Du, Longzheng & Lin, Weifen, 2022. "Does the application of industrial robots overcome the Solow paradox? Evidence from China," Technology in Society, Elsevier, vol. 68(C).
    14. Nikolova, Milena & Cnossen, Femke & Nikolaev, Boris, 2024. "Robots, meaning, and self-determination," Research Policy, Elsevier, vol. 53(5).
    15. Stähler, Nikolai, 2021. "The Impact of Aging and Automation on the Macroeconomy and Inequality," Journal of Macroeconomics, Elsevier, vol. 67(C).
    16. Lekfuangfu, Warn N. & Nakavachara, Voraprapa, 2021. "Reshaping Thailand's labor market: The intertwined forces of technology advancements and shifting supply chains," Economic Modelling, Elsevier, vol. 102(C).
    17. Li, Chao & Zhang, Yuhan & Li, Xiang & Hao, Yanwei, 2024. "Artificial intelligence, household financial fragility and energy resources consumption: Impacts of digital disruption from a demand-based perspective," Resources Policy, Elsevier, vol. 88(C).
    18. Roberto Antonietti & Luca Cattani & Francesca Gambarotto & Giulio Pedrini, 2021. "Education, routine, and complexity-biased Knowledge Enabling Technologies: Evidence from Emilia-Romagna, Italy," Discussion Paper series in Regional Science & Economic Geography 2021-07, Gran Sasso Science Institute, Social Sciences, revised May 2021.
    19. Genz, Sabrina & Schnabel, Claus, 2021. "Digging into the Digital Divide: Workers' Exposure to Digitalization and Its Consequences for Individual Employment," IZA Discussion Papers 14649, Institute of Labor Economics (IZA).
    20. Łukasz Arendt & Eugeniusz Kwiatkowski, 2023. "Kontrowersje wokół wpływu nowoczesnych technologii na zatrudnienie i bezrobocie," Ekonomista, Polskie Towarzystwo Ekonomiczne, issue 2, pages 195-216.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:inm:orisre:v:32:y:2021:i:3:p:675-687. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.