Maurice Thévenet, Professor of Management at ESSEC Business School, consultant and Delegate General of the French Foundation for Management Education (FNEGE), shares part 2 of his article on management and the dimensions of Artificial Intelligence and Natural Intelligence.
Management: Red flags, black swans or human nature by Maurice Thévenent. Translated from French by Tom Gamble.
Red flags, black swans – or human nature
Man dreams of controlling everything – we’ve known that since the appearance of the oldest texts – and he gives regular proof of it. The dominant management culture is that of control and the organisational systems or processes, in which organisations have invested so much money over the last few years, that also, but not only, contribute to the thirst for control. AI, with its learning capacities, controlling and exploiting piles of data inaccessible to humans answers the seduction of control.
There is one thing in particular which man dreams of controlling – and something that seems to him the most uncertain: not so much the mystery of his contemporaries but of the future. AI meets this need because it enables the capacities to analyse the past to multiply in order to extract the scenarios of the future – as if past behaviours predicted the future and as if the past frequency of behaviours strengthens the probability of what is to occur. This is indeed a reality, except when, as Taleb tells us, the ‘black swans’ – an event that comes as a surprise, has a major effect, and is often inappropriately rationalized after the fact with the benefit of hindsight – appear [3].
Fears and expectations with regard to AI convey a limiting image of the future: as if it were the past with, in addition, the new tool and its possibilities that have transformed a frozen present. When micro computing developed, everybody betted on the disappearance of paper and it is the contrary that the vendors of ink and printers have benefited from. When the French declare their yearly incomes on the internet, the fiscal administration hopes to save time, but this virtual and interactive mode of tax form transforms tax payers’ attitudes and they begin to change their declarations, asking questions to which the administration spends vast amounts of time in answering. We always have trouble imagining what an innovation will transform – not in the usage aimed for in the beginning, but in all those around it. It is for this fact that the figures portraying job losses caused by AI must be taken with much care.
The second illusion is that of virtue. Some say that the development of artificial intelligence will enable human resources managers freed of tedious tasks to devote themselves to the noble tasks of their function such as relations, listening to employee concerns and looking after co-workers. This might remind us of the time when people hoped that reducing the number of working hours would free time for relations, family and commitments to clubs and societies: in all evidence it rather seems that it is television and the ‘screen geeks’ that have benefitted the most.
The Rousseauism remains in which the fundamentally good individual is prevented from being so by the villainous society or organisation; once boredom rid of, he will obligatorily turn towards what has more human value. This remains to be seen: for managers and HR managers to turn towards a more relational and human approach in their job, they must, above all else…want to do so.
The third illusion concerns performance. I speak of illusion because, curiously, performance constitutes the unmentionable word of people management. According to the situation, we can implicitly favour such or such a cause of this performance. If you consider that the quality of organisations, structures and processes are enough to generate performance, then AI will obviously be of great help in increasing it; it enables people and the use of their freedom to be replaced, increased or adjusted.
The problem is that business performance can have other causes such as, for example, the involvement of people in what they do, the quality of a relation or the attention they give. There are tasks where this personal investment makes performance happen and intelligence (at least until the year 2050 according to the specialists) will not be enough.
The question of the stakes and possible consequences of the development of AI is not a simple one and, as Davenport demonstrates, there is at times a gap between reality and the hyperbole of all these new experts. To help with discerning things, we can evoke three red flags. The first consists in constantly questioning our attitude towards innovation: is it fear, naive submission to novelty? Or is innovation seen as a means to help my business or as an imperative? In these situations, one should not forget that in the gold rush the real winners were those who sold the shovels.
The second red flag to watch out for is to remain attentive to the new needs in skills required for students, but also current employees; these new skills are not only necessary for specialists who ‘do’ AI, but also for professionals in each sector and trade who see their role and practices changing.
The third red flag is that in periods of history where everything seems to change, it is always useful to come back to what anthropology reveals as relatively unchanging in human nature: the opening out to history, philosophy and even good sense that make it happen. Until now, man has always succeeded in foiling plans aimed at dominating them. What does that tell us about the future – human nature or black swan?
[3] The black swan theory or theory of black swan events, developed by Nassim Nicholas Taleb, is a metaphor that describes an event that comes as a surprise, has a major effect, and is often inappropriately rationalized after the fact with the benefit of hindsight. The term is based on an ancient saying that presumed black swans did not exist – a saying that became reinterpreted to teach a different lesson after black swans were discovered in the wild. https://en.wikipedia.org/wiki/Black_swan_theory
Read Part 1 of this article
Useful links:
- Link up with Prof. Maurice Thévenet on LinkedIn
- Watch Prof. Thévenet’s research video The Quality of Work at Work (in French with English subtitles)
- Browse Maurice Thévente’s books and academic publications
- Read a related article by Prof. and Dean Hirokazu Kono.
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