the preferred automation model of business leaders, recent research has revealed that skills related to feelings will define the future jobs for humans. In fact, salaries for human employees in the future are expected to be determined more by the ability to deal with emotions and relationships rather than by their cognitive abilities. This reality paints a future where jobs that require sensitivity to needs for relationships will have to be populated by humans and the role of leadership seems to fit that bill.
The argument that I am putting forward is that the functioning of our organizations and societies are not served by a kind of sentiment that the analysis of data by algorithms will automatically develop and lead strategies in miraculous ways. Algorithms are not technological tools that have the leading abilities to deliver immediate returns without any human presence or interference needed. As we see technology develop today, we need to be aware of the fact that automated decision-making is still something of a black-box that runs in less structured ways than we think. Algorithms also miss human sophistication, and an awareness of moral norms and emotions; all skills that allow leaders to create value beyond the immediate observable financial returns. In fact, when looking at the data available, reality paints a somewhat different vision when it comes down to the optimal use of algorithms in leading and co-ordinating organizations.
Research by IBM shows that 41% of CEOs report that their organization is not at all prepared to introduce data analytic tools into their management structures.51 In addition, when it comes down to dealing with humans in automated ways, only about 22% of organizations say that they have adopted algorithms in their Human Resources practices.52 And, of those 22%, most are not clear on what the exact effect is that the algorithms reveal. Given these numbers, it seems reasonable to argue that wise leadership in the 21st century will still need more of a strategy than simply trying to make a difference by means of optimizing the technology (including the management technology) taking care of our data. Rather the real difference will be made in having leadership out there that can make use of these technologies in human-centred and sustainable ways that benefit human values, interests and well-being.
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40 MacCrory, F., Westerman, G., Alhammadi, Y., & Brynjolfsson, E. (2014). ‘Racing with and against the machine: Changes in occupational skill composition in an era of rapid technological advance.’ In Proceedings of the 35th International Conference on Information Systems (pp. 295–311). Red Hook, NY: Curran Associates Inc.
41 von Krogh, G. (2018). ‘Artificial intelligence in organizations: New opportunities for phenomenon-based theorizing.’ Academy of Management Discoveries, 4(4), 404-409.
42 Parry, K., Cohen, M., & Bhattacharya, S. (2016). ‘Rise of the machines: A critical consideration of automated leadership decision making in organizations.’ Group & Organization Management, 41(5), 571-594.
43 Lindebaum, D., Vesa, M., & den Hond, F. (in press). ‘Insights from the machine stops to better understand rational assumptions in algorithmic decision-making and its implications for organizations.’ Academy of Management Review.
44 Derrick, D.C., & Elson, J.S. (2019). ‘Exploring automated leadership and agent interaction modalities.’ Proceedings of the 52nd Hawaii International Conference on System Sciences, 207-216.
45 SAS (2018). ‘Becoming a data-driven organization.’ https://analyticsconsultores.com.mx/wp-content/uploads/2019/03/Becoming-a-data-driven-organization-Citizen-Data-Scientist-SAS-2018.pdf
46 Copeland, R., & Hope, B. (2016). ‘The world’s largest hedge fund is building an algorithmic model from its employees’ brains.’ Retrieved from https://www.wsj.com/articles/the-worlds-largest-hedge-fund-is-building-an-algorithmic-model-of-its-founders-brain-1482423694 on 31 October 2018.
47 Nelson, J. (2019). ‘AI in the boardroom – Fantasy or reality?’ March 26. Retrieved from http://www.mondaq.com/x/792746/new+technology/AI+In+The+Boardroom+Fantasy+Or+Reality
48 Libert, B., Beck, M., & Bonchek, M. (2017). ‘AI in the boardroom: The next realm of corporate governance.’ February 21. Retrieved from https://sloanreview.mit.edu/article/ai-in-the-boardroom-the-next-realm-of-corporate-governance/
49 Amazon (2019). https://www.businessinsider.sg/amazon-system- automatically-fires-warehouse-workers-time-off-task-2019-4/?r= US&IR=T
50 Acemoglu, D., & Restrepo, P. (2019). ‘Robots and jobs: Evidence from US labor markets.’ Journal of Political Economy. Accepted August 1.
51 IBM (2019). ‘Unplug from the Past: 19th Global C-Suite Study,’ IBM Institute for Business Value, 2018, https://www.ibm.com/downloads/cas/D2KEJQRO
52 LinkedIn (2019). ‘The Rise of HR Analytics,’ 2018, https://business.linkedin.com/content/dam/me/business/en-us/talent-solutions/talent-intelligence/workforce/pdfs/Final_v2_NAMER_Riseof-Analytics-Report.pdf.
Chapter 3: Leading by Algorithm: Rushing In
Recognized as the new big thing, algorithms are ready to penetrate many of our daily activities and tasks. The reality, however, is that algorithms are not just preparing to dominate our lives, they already do.
Algorithms drive machines by telling them what to do to in order to produce what humans want to see. Yes, algorithms are not only the eagerly awaited, super intelligent aspect of the AI hype, but also the driver of ubiquitous machines we use today in a routine way, such as computers. Algorithms are thus already a pivotal