IDEAS home Printed from https://ideas.repec.org/a/eee/tefoso/v168y2021ics0040162521001712.html
   My bibliography  Save this article

Neurodiversity of the workforce and digital transformation: The case of inclusion of autistic workers at the workplace

Author

Listed:
  • Walkowiak, Emmanuelle

Abstract

This paper analyses the productive complementarities between the digital transformation, the skills of autistic workers and neurodiversity management. Based on a qualitative approach and interviews with leaders or experts of neurodiversity initiatives, we provide a theoretical framework to analyse the links between the neurodiversity of the workforce and digital transformation at the individual, organisational and industry levels. We identify several ways by which the digital transformation may provide a context favourable to autistic workers. This includes creating new opportunities, valuing their performative abilities, cognitive differences and creativity, removing stereotypes and biases during the recruitment and improving the management of psycho-social risks. Neurodiversity management also contributes to the digital transformation by closing the digital skills shortage, shaping algorithms of artificial intelligence and providing a competitive advantage for innovation. Most importantly, neurodiversity management provides an effective model of inclusion that can mitigate the development of inequalities associated with the digital transformation.

Suggested Citation

  • Walkowiak, Emmanuelle, 2021. "Neurodiversity of the workforce and digital transformation: The case of inclusion of autistic workers at the workplace," Technological Forecasting and Social Change, Elsevier, vol. 168(C).
  • Handle: RePEc:eee:tefoso:v:168:y:2021:i:c:s0040162521001712
    DOI: 10.1016/j.techfore.2021.120739
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0040162521001712
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.techfore.2021.120739?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. Anja Lambrecht & Catherine Tucker, 2019. "Algorithmic Bias? An Empirical Study of Apparent Gender-Based Discrimination in the Display of STEM Career Ads," Management Science, INFORMS, vol. 65(7), pages 2966-2981, July.
    2. Montes, Gabriel Axel & Goertzel, Ben, 2019. "Distributed, decentralized, and democratized artificial intelligence," Technological Forecasting and Social Change, Elsevier, vol. 141(C), pages 354-358.
    3. Maarten Goos & Alan Manning & Anna Salomons, 2014. "Explaining Job Polarization: Routine-Biased Technological Change and Offshoring," American Economic Review, American Economic Association, vol. 104(8), pages 2509-2526, August.
    4. Daron Acemoglu & Pascual Restrepo, 2020. "Robots and Jobs: Evidence from US Labor Markets," Journal of Political Economy, University of Chicago Press, vol. 128(6), pages 2188-2244.
    5. Dengler, Katharina & Matthes, Britta, 2018. "The impacts of digital transformation on the labour market: Substitution potentials of occupations in Germany," Technological Forecasting and Social Change, Elsevier, vol. 137(C), pages 304-316.
    6. Mason Ameri & Lisa Schur & Meera Adya & F. Scott Bentley & Patrick McKay & Douglas Kruse, 2018. "The Disability Employment Puzzle: A Field Experiment on Employer Hiring Behavior," ILR Review, Cornell University, ILR School, vol. 71(2), pages 329-364, March.
    7. Acemoglu, Daron & Autor, David, 2011. "Skills, Tasks and Technologies: Implications for Employment and Earnings," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 4, chapter 12, pages 1043-1171, Elsevier.
    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. repec:cup:jomorg:v:25:y:2019:i:04:p:453-463_00 is not listed on IDEAS
    10. Camiña, Ester & Díaz-Chao, Ángel & Torrent-Sellens, Joan, 2020. "Automation technologies: Long-term effects for Spanish industrial firms," Technological Forecasting and Social Change, Elsevier, vol. 151(C).
    11. Last, Cadell, 2017. "Global Commons in the Global Brain," Technological Forecasting and Social Change, Elsevier, vol. 114(C), pages 48-64.
    12. Tom Mitchell & Erik Brynjolfsson, 2017. "Track how technology is transforming work," Nature, Nature, vol. 544(7650), pages 290-292, April.
    13. Milgrom, Paul & Roberts, John, 1990. "The Economics of Modern Manufacturing: Technology, Strategy, and Organization," American Economic Review, American Economic Association, vol. 80(3), pages 511-528, June.
    Full references (including those not matched with items on IDEAS)

    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. Hensvik, Lena & Skans, Oskar Nordström, 2023. "The skill-specific impact of past and projected occupational decline," Labour Economics, Elsevier, vol. 81(C).
    2. Mr. Andrew Berg & Lahcen Bounader & Nikolay Gueorguiev & Hiroaki Miyamoto & Mr. Kenji Moriyama & Ryota Nakatani & Luis-Felipe Zanna, 2021. "For the Benefit of All: Fiscal Policies and Equity-Efficiency Trade-offs in the Age of Automation," IMF Working Papers 2021/187, International Monetary Fund.
    3. Cao, Yuqiang & Hu, Yong & Liu, Qian & Lu, Meiting & Shan, Yaowen, 2023. "Job creation or disruption? Unraveling the effects of smart city construction on corporate employment in China," Technological Forecasting and Social Change, Elsevier, vol. 195(C).
    4. Caselli, Mauro & Fracasso, Andrea & Scicchitano, Sergio & Traverso, Silvio & Tundis, Enrico, 2021. "Stop worrying and love the robot: An activity-based approach to assess the impact of robotization on employment dynamics," GLO Discussion Paper Series 802, Global Labor Organization (GLO).
    5. Gries, Thomas & Naudé, Wim, 2020. "Artificial Intelligence, Income Distribution and Economic Growth," IZA Discussion Papers 13606, Institute of Labor Economics (IZA).
    6. Fernández-Macías, Enrique & Klenert, David & Antón, José-Ignacio, 2021. "Not so disruptive yet? Characteristics, distribution and determinants of robots in Europe," Structural Change and Economic Dynamics, Elsevier, vol. 58(C), pages 76-89.
    7. de Vries, Gaaitzen J. & Gentile, Elisabetta & Miroudot, Sébastien & Wacker, Konstantin M., 2020. "The rise of robots and the fall of routine jobs," Labour Economics, Elsevier, vol. 66(C).
    8. Consoli, Davide & Marin, Giovanni & Rentocchini, Francesco & Vona, Francesco, 2023. "Routinization, within-occupation task changes and long-run employment dynamics," Research Policy, Elsevier, vol. 52(1).
    9. Gregory, Terry & Salomons, Anna & Zierahn, Ulrich, 2016. "Racing With or Against the Machine? Evidence from Europe," VfS Annual Conference 2016 (Augsburg): Demographic Change 145843, Verein für Socialpolitik / German Economic Association.
    10. Dauth, Wolfgang & Findeisen, Sebastian & Südekum, Jens & Wößner, Nicole, 2017. "German robots - the impact of industrial robots on workers," IAB-Discussion Paper 201730, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    11. Arntz, Melanie & Gregory, Terry & Zierahn, Ulrich, 2019. "Digitalization and the Future of Work: Macroeconomic Consequences," IZA Discussion Papers 12428, Institute of Labor Economics (IZA).
    12. Georg Graetz, 2019. "Labor Demand in the Past, Present, and Future," European Economy - Discussion Papers 114, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    13. Georg Graetz & Guy Michaels, 2018. "Robots at Work," The Review of Economics and Statistics, MIT Press, vol. 100(5), pages 753-768, December.
    14. Fossen, Frank M. & Sorgner, Alina, 2019. "New Digital Technologies and Heterogeneous Employment and Wage Dynamics in the United States: Evidence from Individual-Level Data," IZA Discussion Papers 12242, Institute of Labor Economics (IZA).
    15. 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.
    16. Davide Dottori, 2021. "Robots and employment: evidence from Italy," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 38(2), pages 739-795, July.
    17. Genz Sabrina & Janser Markus & Lehmer Florian, 2019. "The Impact of Investments in New Digital Technologies on Wages – Worker-Level Evidence from Germany," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 239(3), pages 483-521, June.
    18. Barbieri, Laura & Mussida, Chiara & Piva, Mariacristina & Vivarelli, Marco, 2019. "Testing the employment and skill impact of new technologies: A survey and some methodological issues," MERIT Working Papers 2019-032, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    19. repec:hal:spmain:info:hdl:2441/13fti1jo4t8vjpe6ko3qrrv2nv is not listed on IDEAS
    20. Domini, Giacomo & Grazzi, Marco & Moschella, Daniele & Treibich, Tania, 2022. "For whom the bell tolls: The firm-level effects of automation on wage and gender inequality," Research Policy, Elsevier, vol. 51(7).
    21. Florent Bordot & Andre Lorentz, 2021. "Automation and labor market polarization in an evolutionary model with heterogeneous workers," LEM Papers Series 2021/32, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.

    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:tefoso:v:168:y:2021:i:c:s0040162521001712. 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: http://www.sciencedirect.com/science/journal/00401625 .

    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.