IDEAS home Printed from https://ideas.repec.org/a/eee/intell/v89y2021ics0160289621000696.html
   My bibliography  Save this article

To predict the future, consider the past: Revisiting Carroll (1993) as a guide to the future of intelligence research

Author

Listed:
  • Wilhelm, Oliver
  • Kyllonen, Patrick

Abstract

There is a widely held consensus in the field of intelligence research that the broad factors identified by Cattell, Horn, and Carroll are an adequate summary of individual differences in human cognitive abilities. Most researchers would agree that the redundancy among these factors is best accounted for by an overarching general factor. We think the best way to acknowledge major accomplishments is to build upon them with the goal to challenge the status quo. Here we want to do so by discussing six broad ability factors that are either considered in Carroll's epochal book or could be candidates for future inclusions to the list of established cognitive ability factors: fluid intelligence, crystallized intelligence, cognitive speed, creativity, social and emotional intelligence, and collaborative problem solving. We conclude with four pleas: reunite correlational and experimental research, enrich construct interpretations, reunite educational and psychological measurement of maximal cognitive effort, and reconsider the sampling of indicators and content validity.

Suggested Citation

  • Wilhelm, Oliver & Kyllonen, Patrick, 2021. "To predict the future, consider the past: Revisiting Carroll (1993) as a guide to the future of intelligence research," Intelligence, Elsevier, vol. 89(C).
    • Handle: RePEc:eee:intell:v:89:y:2021:i:c:s0160289621000696
    DOI: 10.1016/j.intell.2021.101585
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0160289621000696
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.intell.2021.101585?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Chuderski, Adam, 2019. "Even a single trivial binding of information is critical for fluid intelligence," Intelligence, Elsevier, vol. 77(C).
    2. Karl Holzinger & Frances Swineford, 1937. "The Bi-factor method," Psychometrika, Springer;The Psychometric Society, vol. 2(1), pages 41-54, March.
    3. Christoph Riedl & Young Ji Kim & Pranav Gupta & Thomas W. Malone & Anita Williams Woolley, 2021. "Quantifying collective intelligence in human groups," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 118(21), pages 2005737118-, May.
    4. Borghans, L. & Golsteyn, B.H.H. & Heckman, James & Humphries, John Eric, 2011. "Identification problems in personality psychology," Research Memorandum 025, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
    5. Wim van der Linden, 2007. "A Hierarchical Framework for Modeling Speed and Accuracy on Test Items," Psychometrika, Springer;The Psychometric Society, vol. 72(3), pages 287-308, September.
    6. 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.
    7. Ben Weidmann & David J. Deming, 2021. "Team Players: How Social Skills Improve Team Performance," Econometrica, Econometric Society, vol. 89(6), pages 2637-2657, November.
    8. Jeffrey Mo, 2017. "Collaborative problem solving," PISA in Focus 78, OECD Publishing.
    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. Haier, Richard J., 2021. "Are we thinking big enough about the road ahead? Overview of the special issue on the future of intelligence research," Intelligence, Elsevier, vol. 89(C).
    2. Callis, Zoe & Gerrans, Paul & Walker, Dana L. & Gignac, Gilles E., 2023. "The association between intelligence and financial literacy: A conceptual and meta-analytic review," Intelligence, Elsevier, vol. 100(C).
    3. Walker, Dana L. & Palermo, Romina & Callis, Zoe & Gignac, Gilles E., 2023. "The association between intelligence and face processing abilities: A conceptual and meta-analytic review," Intelligence, Elsevier, vol. 96(C).
    4. Feraco, Tommaso & Cona, Giorgia, 2022. "Differentiation of general and specific abilities in intelligence. A bifactor study of age and gender differentiation in 8- to 19-year-olds," Intelligence, Elsevier, vol. 94(C).
    5. Procopio, Francesca & Zhou, Quan & Wang, Ziye & Gidziela, Agnieska & Rimfeld, Kaili & Malanchini, Margherita & Plomin, Robert, 2022. "The genetics of specific cognitive abilities," Intelligence, Elsevier, vol. 95(C).

    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. Eckhardt Bode & Stephan Brunow & Ingrid Ott & Alina Sorgner, 2019. "Worker Personality: Another Skill Bias beyond Education in the Digital Age," German Economic Review, Verein für Socialpolitik, vol. 20(4), pages 254-294, November.
    2. Loebbing, Jonas, 2018. "An Elementary Theory of Endogenous Technical Change and Wage Inequality," VfS Annual Conference 2018 (Freiburg, Breisgau): Digital Economy 181603, Verein für Socialpolitik / German Economic Association.
    3. Basso, Henrique S. & Jimeno, Juan F., 2021. "From secular stagnation to robocalypse? Implications of demographic and technological changes," Journal of Monetary Economics, Elsevier, vol. 117(C), pages 833-847.
    4. Caroline Lloyd & Jonathan Payne, 2021. "Fewer jobs, better jobs? An international comparative study of robots and ‘routine’ work in the public sector," Industrial Relations Journal, Wiley Blackwell, vol. 52(2), pages 109-124, March.
    5. Gilberto Santos & Jose Carlos Sá & Maria João Félix & Luís Barreto & Filipe Carvalho & Manuel Doiro & Kristína Zgodavová & Miladin Stefanović, 2021. "New Needed Quality Management Skills for Quality Managers 4.0," Sustainability, MDPI, vol. 13(11), pages 1-22, May.
    6. Czarnitzki, Dirk & Fernández, Gastón P. & Rammer, Christian, 2023. "Artificial intelligence and firm-level productivity," Journal of Economic Behavior & Organization, Elsevier, vol. 211(C), pages 188-205.
    7. Thanos Fragkandreas, 2022. "Three Decades of Research on Innovation and Inequality: Causal Scenarios, Explanatory Factors, and Suggestions," Working Papers 60, Birkbeck Centre for Innovation Management Research, revised Feb 2022.
    8. Sebastian Brumann & Ulrike Ohl & Johannes Schulz, 2022. "Inquiry-Based Learning on Climate Change in Upper Secondary Education: A Design-Based Approach," Sustainability, MDPI, vol. 14(6), pages 1-29, March.
    9. Singh, Anuraag & Triulzi, Giorgio & Magee, Christopher L., 2021. "Technological improvement rate predictions for all technologies: Use of patent data and an extended domain description," Research Policy, Elsevier, vol. 50(9).
    10. Montse Gomendio, 2023. "The Level of Skills in Spain: How to Solve the Puzzle using International Surveys," Studies on the Spanish Economy eee2023-35, FEDEA.
    11. Steven Andrew Culpepper & James Joseph Balamuta, 2017. "A Hierarchical Model for Accuracy and Choice on Standardized Tests," Psychometrika, Springer;The Psychometric Society, vol. 82(3), pages 820-845, September.
    12. María Jesús Rosado-García & Renata Kubus & Ramón Argüelles-Bustillo & María Jesús García-García, 2021. "A New European Bauhaus for a Culture of Transversality and Sustainability," Sustainability, MDPI, vol. 13(21), pages 1-22, October.
    13. Gianluca MISURACA & Colin van Noordt, 2020. "AI Watch - Artificial Intelligence in public services: Overview of the use and impact of AI in public services in the EU," JRC Research Reports JRC120399, Joint Research Centre.
    14. Dario Cords & Klaus Prettner, 2022. "Technological unemployment revisited: automation in a search and matching framework [The future of work: meeting the global challenges of demographic change and automation]," Oxford Economic Papers, Oxford University Press, vol. 74(1), pages 115-135.
    15. John Burgess & Julia Connell, 2020. "New technology and work: Exploring the challenges," The Economic and Labour Relations Review, , vol. 31(3), pages 310-323, September.
    16. Anton Korinek & Joseph E. Stiglitz, 2018. "Artificial Intelligence and Its Implications for Income Distribution and Unemployment," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 349-390, National Bureau of Economic Research, Inc.
    17. Markus Menz & Sven Kunisch & Julian Birkinshaw & David J. Collis & Nicolai J. Foss & Robert E. Hoskisson & John E. Prescott, 2021. "Corporate Strategy and the Theory of the Firm in the Digital Age," Journal of Management Studies, Wiley Blackwell, vol. 58(7), pages 1695-1720, November.
    18. David J. Deming, 2017. "The Growing Importance of Social Skills in the Labor Market," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 132(4), pages 1593-1640.
    19. Alex Chernoff & Casey Warman, 2023. "COVID-19 and implications for automation," Applied Economics, Taylor & Francis Journals, vol. 55(17), pages 1939-1957, April.
    20. Emil Sundstrup & Annette Meng & Jeppe Z. N. Ajslev & Karen Albertsen & Flemming Pedersen & Lars L. Andersen, 2022. "New Technology and Loss of Paid Employment among Older Workers: Prospective Cohort Study," IJERPH, MDPI, vol. 19(12), pages 1-13, June.

    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:eee:intell:v:89:y:2021:i:c:s0160289621000696. 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: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/intelligence .

    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.