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Why Artificial Intelligence Will Not Outsmart Complex Knowledge Work

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  • Lene Pettersen

Abstract

The potential role of artificial intelligence in improving organisations’ performance and productivity has been promoted regularly and vociferously since the 1960s. Artificial intelligence is today reborn out of big business, similar to the occurrences surrounding big data in the 1990s, and expectations are high regarding AI’s potential role in businesses. This article discusses different aspects of knowledge work that tend to be ignored in the debate about whether or not artificial intelligence systems are a threat to jobs. A great deal of knowledge work concerns highly complex problem solving and must be understood in contextual, social and relational terms. These aspects have no generic nor universal rules and solutions and, thus, cannot be easily replaced by artificial intelligence or programmed into computer systems, nor are they constructed based on models of the rational brain. In this respect, this article draws on philosopher Herbert Dreyfus’ thesis regarding artificial intelligence.

Suggested Citation

  • Lene Pettersen, 2019. "Why Artificial Intelligence Will Not Outsmart Complex Knowledge Work," Work, Employment & Society, British Sociological Association, vol. 33(6), pages 1058-1067, December.
    • Handle: RePEc:sae:woemps:v:33:y:2019:i:6:p:1058-1067
    DOI: 10.1177/0950017018817489
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    References listed on IDEAS

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    1. Stephen R. Barley & Gideon Kunda, 2001. "Bringing Work Back In," Organization Science, INFORMS, vol. 12(1), pages 76-95, February.
    2. Eero Vaara & Richard Whittington, 2012. "Strategy as practice : Taking Social Practices Seriously," Post-Print hal-02312709, HAL.
    3. Davide Nicolini, 2011. "Practice as the Site of Knowing: Insights from the Field of Telemedicine," Organization Science, INFORMS, vol. 22(3), pages 602-620, June.
    4. Melanie Arntz & Terry Gregory & Ulrich Zierahn, 2016. "The Risk of Automation for Jobs in OECD Countries: A Comparative Analysis," OECD Social, Employment and Migration Working Papers 189, OECD Publishing.
    5. Eero Vaara & Richard Whittington, 2012. "Strategy as practice : Taking Social Practices Seriously," Post-Print hal-02276672, HAL.
    6. David H. Autor & Frank Levy & Richard J. Murnane, 2003. "The Skill Content of Recent Technological Change: An Empirical Exploration," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 118(4), pages 1279-1333.
    7. Martha S. Feldman & Wanda J. Orlikowski, 2011. "Theorizing Practice and Practicing Theory," Organization Science, INFORMS, vol. 22(5), pages 1240-1253, October.
    8. Frantz, Roger, 2003. "Herbert Simon. Artificial intelligence as a framework for understanding intuition," Journal of Economic Psychology, Elsevier, vol. 24(2), pages 265-277, April.
    9. David H. Autor & Frank Levy & Richard J. Murnane, 2003. "The skill content of recent technological change: an empirical exploration," Proceedings, Federal Reserve Bank of San Francisco, issue nov.
    10. Damon Golsorkhi & Linda Rouleau & David Seidl & Eero Vaara, 2010. "Cambridge Handbook of Strategy as Practice," Post-Print hal-02298145, HAL.
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    5. Areeba Khan & Saboohi Nasim, 2025. "Mapping research on the subjective well-being of knowledge workers: a systematic enquiry deploying bibliometrics," Management Review Quarterly, Springer, vol. 75(1), pages 911-954, February.
    6. Rezaei, Mojtaba, 2025. "Artificial intelligence in knowledge management: Identifying and addressing the key implementation challenges," Technological Forecasting and Social Change, Elsevier, vol. 217(C).
    7. Nuno Boavida & Marta Candeias, 2021. "Recent Automation Trends in Portugal: Implications on Industrial Productivity and Employment in Automotive Sector," Societies, MDPI, vol. 11(3), pages 1-16, August.
    8. Oliver Giering & Stefan Kirchner, 2025. "Artificial intelligence and autonomy at work: empirical insights from Germany," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), vol. 59(1), pages 1-15, December.
    9. Emrah Karakilic, 2022. "Why Do Humans Remain Central to the Knowledge Work in the Age of Robots? Marx’s Fragment on Machines and Beyond," Work, Employment & Society, British Sociological Association, vol. 36(1), pages 179-189, February.
    10. Luca Antonazzo & Dean Stroud & Martin Weinel, 2024. "Smart manufacturing and tasks automation in the steel industry: Reflecting on routine work and skills in Industry 4.0," Economic and Industrial Democracy, Department of Economic History, Uppsala University, Sweden, vol. 45(3), pages 914-936, August.
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