Harrison, T., Nichol, Lynn, Gatto, M., Wai, M.C., Cox, A. and Gold, J. (2018) What Will Be the Surprises for HRD in 2028? A Futures Scenario. International Journal of Human Resource Development Practice, Policy and Research, 3 (2). pp. 63-71. ISSN 23974575
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Abstract
The paper reports findings from a futures workshop to consider surprises — unexpected or astonishing events or facts — that may await HRD. Participants were asked to identify an HRD issue for the future and then pose questions that placed surprise up front and that could indicate a vulnerability for HRD. Two scenarios are developed for the year 2028 and events leading to this year. In the first, S1, human behaviour within organizations is defined by machines and machines prescribe why, what and where work is needed, who does it, when, and how work is done. Thus programmes of learning are pre-determined by machines. In the second, S2, aritificial intelligence proves to be incapable of adapting to the extreme events of solar activity affecting satellites and internet communications globally. HRD rebuilds trust in the collective human ability to work together collaboratively to restore a team ethic and rebuild. The scenarios are discussed and a recommendation is made for HRD research to consider the direction and value of their work and how progress in academic life might be reconstituted to allow more attention to be given to key areas of machine learning and artificial intelligence.
Item Type: | Article |
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Additional Information: | The full-text can be accessed via the Official URL. |
Uncontrolled Discrete Keywords: | HRD Futures, Machines, Artificial Intelligence, Work, Global Citizens |
Subjects: | H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management |
Divisions: | College of Business, Psychology and Sport > Worcester Business School |
Related URLs: | |
Copyright Info: | Open Access |
Depositing User: | Lynn Nichol |
Date Deposited: | 26 Oct 2018 09:51 |
Last Modified: | 17 Jun 2020 17:25 |
URI: | https://eprints.worc.ac.uk/id/eprint/7170 |
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