The arrival of AI in the world of work cannot be reduced to a simple substitution of humans by machines. It represents a profound shift in the boundary between what can be automated and what cannot. As repetitive, codifiable, and predictable tasks are taken over by algorithmic systems, the value of human work is being redefined. It is shifting toward activities that require greater cognitive intensity but also a higher degree of emotional intelligence, intelligence of sensitivity, as I call it.<\/p>\n\n\n\n
Non-manual labor can no longer be confined to execution, however skilled; it must integrate abilities of interpretation, judgment, and anticipation. The value of work increasingly rests on the capacity to understand complex situations\u2014the subtlety and dynamics of human interaction\u2014to navigate uncertainty and to make decisions that cannot be entirely derived from past data.<\/p>\n\n\n\n
This is precisely where the \u201cintelligence of sensitivity\u201d\u2014or intuitive intelligence, as Kant called it\u2014becomes decisive. Where AI excels in processing vast amounts of data and detecting correlations, it remains limited in grasping human nuances: intentions, weak signals, the conditions of trust, implicit contexts and dynamics. Yet these dimensions lie at the heart of economic and social interactions.
Negotiating, convincing, cooperating, arbitrating, deciding\u2014all are acts that demand a fine understanding of others, both to comprehend and anticipate them.<\/p>\n\n\n\n
Anticipation is not merely projecting trends from data; it also implies perceiving what is not yet fully articulated, capturing emerging shifts, and sensing nascent imbalances. In other words, anticipation mobilizes a form of intelligence that surpasses calculation.<\/p>\n\n\n\n
As I emphasized in my book Crises et mutations, intelligence cannot be reduced to analytical capacity alone. It lies in the interplay between reason and sensitivity, between modeling and intuition. Judgment is indispensable for anticipating and making sound decisions in a world whose future is barely probabilizable. It is not merely the mechanical execution of an optimization program under constraints.<\/p>\n\n\n\n
This idea resonates powerfully with philosophical thought.
\u201cWithout sensibility, no object would be given to us; and without understanding, none would be thought. Thoughts without content are empty; intuitions without concepts are blind. Consequently, it is equally necessary to make one\u2019s thoughts sensitive and one\u2019s intuitions intelligible. Neither faculty can exchange functions: understanding can intuit nothing, and the senses can think nothing. Only through their combination can knowledge arise.\u201d \u2014 Immanuel Kant, Critique of Pure Reason<\/p>\n\n\n\n
Kant\u2019s insight sheds striking light on contemporary challenges. AI embodies a powerful form of understanding\u2014but without sensibility: it calculates, structures, optimizes. Yet it does not \u201cfeel.\u201d Conversely, humans who rely solely on intuition without analytical rigor would risk error and bias. The decisive advantage of humanity lies, therefore, in the union of both faculties.<\/p>\n\n\n\n
The future of work will be neither humanity replaced nor humanity unchanged. It will be one of enhanced complementarity between human and machine, with human value concentrated in what eludes automation: creativity, sensitivity, discernment\u2014hence, responsibility and decision-making capacity.<\/p>\n\n\n\n
In this new landscape, developing and enhancing these skills become both a social and economic imperative. For it is precisely these capacities\u2014those that highlight the essence of human intelligence\u2014that will ensure the continued place of humankind in the world of work.<\/p>\n\n\n\n
Olivier Klein is Professor of Economics at HEC.<\/p>\n","protected":false},"excerpt":{"rendered":"
The arrival of AI in the world of work cannot be reduced to a simple substitution of humans by machines. It represents a profound shift in the boundary between what can be automated and what cannot. As repetitive, codifiable, and predictable tasks are taken over by algorithmic systems, the value of human work is being […]<\/p>\n","protected":false},"author":1,"featured_media":9166,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[136,134],"tags":[],"class_list":["post-10263","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-economical-policy","category-global-economy"],"acf":[],"yoast_head":"\n