The implementation of artificial intelligence (AI) is assumed to lead to increased productivity of knowledge workers. However, AI could also have negative effects on the development of professional expertise.
Solution
A review of the literature on expertise development is provided, followed by examples of AI implementation in a knowledge-intensive profession, accounting. The analysis of these examples suggests that automation can result in the loss of expertise due to reduced opportunities for learning from deliberate practice and experienced colleagues, and from working on progressively more complex tasks. Implications for human resource development (HRD) include creating alternative individual development opportunities and promoting organizational cultures conducive to expertise development in human-machine interaction modes.
Stakeholders
The results of this study will be of interest to scholars of HRD, accounting education, and human-machine interaction. Practical implications will be of relevance to HRD professionals and managers responsible for the implementation of artificial intelligence solutions.
ArnoldV.ClarkN.CollierP.A.LeechS.A.SuttonS. G. (2006). The differential use and effect of knowledge-based system explanations in novice and expert judgment decisions. MIS Quarterly, 30(1), 79–97. https://doi.org/10.2307/25148718
2.
ArnoldV.CollierP. A.LeechS. A.SuttonS. G. (2004). Impact of intelligent decision aids on expert and novice decision-makers’ judgments. Accounting & Finance, 44(1), 1-26. https://doi.org/10.1111/j.1467-629x.2004.00099.x
3.
ArnoldV.CollierP. A.LeechS. A.SuttonS. G.VincentA. (2013). INCASE: Simulating experience to accelerate expertise development by knowledge workers. Intelligent Systems in Accounting, Finance & Management, 20(1), 1–21. https://doi.org/10.1002/isaf.1337
4.
ArnoldV.SuttonS. G. (1998). The theory of technology dominance: Understanding the impact of intelligent decision aids on decision makers’ judgments. Advances in Accounting Behavioral Research, 1(1), 175–194.
AutorD. H. (2015). Why are there still so many jobs? The history and future of workplace automation. Journal of Economic Perspectives, 29(3), 3–30. https://doi.org/10.1257/jep.29.3.3
7.
BeaneM. (2019). Learning to work with intelligent machines. Harvard Business Review, 140–148.
8.
BeerPMulderRH (2020). The effects of technological developments on work and their implications for continuous vocational education and training: A systematic review. Frontiers in Psychology, 11(918), 918–919. https://doi.org/10.3389/fpsyg.2020.00918
9.
BellmanR. E. (1978). An introduction to artificial intelligence: Can computers think?Boyd and frasier.
BennerP. (2004). Using the dreyfus model of skill acquisition to describe and interpret skill acquisition and clinical judgment in nursing practice and education. Bulletin of Science, Technology, and Society, 24(3), 188–199. https://doi.org/10.1177/0270467604265061.
12.
BereiterC.ScardamaliaM. (1993). Surpassing ourselves: An inquiry into the nature and implications of expertise. Open Court.
13.
BertomeuJ. (2020). Machine learning improves accounting: Discussion, implementation and research opportunities. Review of Accounting Studies, 25(3), 1135–1155. https://doi.org/10.1007/s11142-020-09554-9
14.
BravermanH. (1974). Labor and monopoly capital. Monthly Review Press.
BrockmanJ. L.DirkxJ. M. (2006). Learning to become a machine operator: The dialogical relationship between context, self, and content. Human Resource Development Quarterly, 17(2), 199–221. https://doi.org/10.1002/hrdq.1169
17.
BrynjolfssonE.McAfeeA. (2014). The second machine age: Work, progress, and prosperity in a time of brilliant technologies. W. W. Norton.
CherrstromC. A.BixbyJ. (2018). Construct of expertise within the context of HRD : Integrative literature review. Human Resource Development Review, 17(4), 440–464. https://doi.org/10.1177/1534484318796762
20.
ChiM.GlaserR.FarrM. (1988). The nature of expertise. Erlbaum.
DavenportT.RonankiR. (2018). Artificial intelligence for the real world: Don’t start without a moon shot. In Harvard Business Review, January-February, 110–116.
23.
DreyfusH. L.DreyfusS. E. (1986). Mind over machine: The power of human intuition and expertise in the era of the computer. Free Press.
24.
EricssonK. A. (2005). Recent advances in expertise research: A commentary on the contributions to the special issue. Applied Cognitive Psychology, 19(2), 233–241. https://doi.org/10.1002/acp.1111
25.
EricssonK. A. (2009). Development of professional expertise: Toward measurement of expert performance and design of optimal learning environments. Cambridge University Press.
26.
EricssonK. A.KrampeR. T.Tesch-RömerC. (1993). The role of deliberate practice in the acquisition of expert performance. Psychological Review, 100(3), 363–406. https://doi.org/10.1037/0033-295x.100.3.363
27.
EversA. T.van der HeijdenB. I. J. M. (2017). Competence and professional expertise. In MulderM. (Ed), Competence-based vocational and professional education (pp. 83–101). Springer International Publishing. https://doi.org/10.1007/978-3-319-41713-4_4
28.
FordM. (2015). Rise of the robots: Technology and the threat of a jobless future. Basic Books.
29.
FrancisA. (1986). New technology at work. Clarendon Press.
30.
FreyC. B.OsborneM. A. (2017). The future of employment: How susceptible are jobs to computerization?Technological Forecasting and Social Change, 114(1), 254–280. https://doi.org/10.1016/j.techfore.2016.08.019
31.
GermainM.-L.TejedaM. J. (2012). A preliminary exploration on the measurement of expertise : An initial development of a psychometric scale. Human Resource Development Quarterly, 23(2), 203–232. https://doi.org/10.1002/hrdq10.1002/hrdq.21134
32.
GobetF. (2015). Understanding expertise: A multidisciplinary approach. Palgrave.
GreenoJ. G.EngestromY. (2014). Learning in activity. In SawyerR. K. (Ed), The Cambridge handbook of the learning sciences (2nd ed., pp. 128–147). Cambridge University Press.
36.
GrenierR. S. (2005). How museum docents develop expertise. University of Georgia Press.
37.
GrenierR. S. (2009). The role of learning in the development of expertise in museum docents. Adult Education Quarterly, 59(2), 142–157. https://doi.org/10.1177/0741713608327369
38.
GrenierR. S.KehrhahnM. (2008). Toward an integrated model of expertise redevelopment and its implications for HRD. Human Resource Development Review, 7(2), 198–217. https://doi.org/10.1177/1534484308316653
39.
GrenierR., S.GermainM.-L. (2014). Expertise through the HRD lens. In: N FChalofsky,TRocco,M LMorris, (Eds), Handbook of Human Resource Development, pp. 183–200.
40.
HambrickDZAltmannEMOswaldFLMeinzEJGobetFCampitelliG. (2014). Deliberate practice: Is that all it takes to become an expert?Intelligence, 45(1), 751–845. https://doi.org/10.3389/fpsyg.2014.00751
41.
HambrickD. Z.MacnamaraB. N.CampitelliG.UllénF.MosingM. A. (2016). Beyond born versus made : A new look at expertise. Psychology of Learning and Motivation, 64(1), 1–55. https://doi.org/10.1016/bs.plm.2015.09.001
42.
HerlingR. W. (2000). Operational definitions of expertise and competence. Advances in Developing Human Resources, 2(1), 8–21. https://doi.org/10.1177/152342230000200103
43.
ICAEW (2018). Information technology faculty chartered accountants’ Hall report. ICAEW.
44.
JarrahiM. H. (2019). In the age of the smart artificial intelligence: AI’s dual capacities for automating and informating work. Business Information Review, 36(4), 178–187. https://doi.org/10.1177/0266382119883999
45.
KleinG. (2004). Power of intuition. Currency/Doubleday.
46.
KokinaJ.DavenportT. (2017). The emergence of Artificial Intelligence: How automation is changing auditing. Journal of Emerging Technologies in Accounting, 14(1), 115–122. DOI: 10.2308/jeta-51730
47.
KuhlmannD. (2013). How Do Tax Accountants Develop Technical-Tax Expertise? A Grounded Theory Study. Unpublished dissertation. University of Minnesota.
48.
KuhlmannD.ArdichviliA. (2014). Becoming an expert: developing expertise in an applied discipline. European Journal of Training and Development, 39(4), 262–276.
49.
LewisT. (2007). Braverman, Foucault and the labor process: framing the current high-skills debate. Journal of Education and Work, 20(5), 397–415. https://doi.org/10.1080/13639080701814315
50.
LindermanA.BakerJ.BosackerS. C. (2011). Surfacing and transferring expert knowledge: The sense-making interview. Human Resource Development International, 14(3), 353–362. https://doi.org/10.1080/13678868.2011.585071
51.
MarsickV. J.WatkinsK. (1990). Informal and incidental learning in the workplace. Routledge.
52.
McKinsey Global Institute (2017). Jobs lost, jobs gained: Workforce transitions in a time of automation. MGI Report.
53.
NgC.AlarconJ. (2021). Artificial intelligence in accounting: Practical applications. Routledge.
ReimannP.MarkauskaiteL. (2019). Expertise. In FischerF.Hmelo-SilverC. E.GoldmanS. R.ReimannP. (Eds), International handbook of the learning sciences (pp. 54–63). Routledge.
56.
SchwabK. (2017). The fourth industrial revolution. Currency.
SmithT. W.StrahanD. (2004). Toward a prototype of expertise in teaching: A descriptive case study. Journal of Teacher Education, 55(4), 357–371. https://doi.org/10.1177/0022487104267587
60.
SpencerD. A. (2018). Fear and hope in an age of mass automation: Debating the future of work. New Technology, Work and Employment, 33(1), 1–12. https://doi.org/10.1111/ntwe.12105.
61.
SunT. (2019). Applying deep learning to audit procedures: An illustrative framework. Accounting Horizons, 33(3), 89–109. https://doi.org/10.2308/acch-52455
62.
SuttonS. G.ArnoldV.HoltM. (2018). How much automation is too much? Keeping the human-relevant in knowledge work. Journal of Emerging Technologies in Accounting, 15(2), 15–25. https://doi.org/10.2308/jeta-52311
63.
TkachenkoO.ArdichviliA. (2017). Cultural-historical activity theory’s relevance to HRD: A review and application. Human Resource Development Review, 16(2), 135–157. https://doi.org/10.1177/1534484317696717
64.
Van de WielM. W. J.Van den BosscheP. (2013). Deliberate practice in medicine: The motivation to engage in work-related learning and its contribution to expertise. Vocations and Learning, 6(1), 135–158. https://doi.org/10.1007/s12186-012-9085-x.
VygotskyL. S. (1978). Mind in society: The development of higher psychological processes. Harvard University Press.
67.
WengerE. (1999). Communities of practice: Learning, meaning, and identity. Cambridge University Press.
68.
WilsonJ.DaughertyP. (2018). Collaborative intelligence: Humans and AI are joining forces. In Harvard Business Review (pp. 115–123). July-August.
69.
YawsonR. M. (2013). Systems theory and thinking as a foundational theory in human resource development: A myth or reality?Human Resource Development Review, 12(1), 53–85. https://doi.org/10.1177/1534484312461634
70.
YuanY. C.CarboniI.EhrlichK. (2010). The impact of affective relationships and awareness on expertise retrieval: A multilevel network perspective a transactive memory theory. Academy of Management Annual Meeting Proceedings, 2010(1), 1–6. https://doi.org/10.5465/AMBPP.2010.54485295
71.
ZuboffS. (1988). The age of the smart machine: The future of work and power. Basic Books.
