To what future are the many faces of the work pointing, while digital technologies shake it? Three are the challenges we have to face: namely, the different skills to be acquired, as required by those technologies; the low-skilled occupations created; the entrepreneurial evolution of work. By winning them, the development of technology will not be going to point towards the replacement of people, but to connect them in entirely new ways.
It all begins with an act of intelligence: so wrote Carlo Cattaneo, founder of the prestigious journal Il Politecnico, about the work. It is the nature of intelligence that shows the paths of work. Its exploration, notes Melanie Mitchell, Professor of Computer Science at Portland State University, in her book Artificial Intelligence: A Guide for Thinking Humans (Farrar, Straus, and Giroux, New York, 2019), demands interdisciplinary studies, not increasingly extensive and large networks and data collections. Once the barriers between two or more disciplines have been broken down, the holistic approach of trans-disciplinarity is the next step.
What about artificial intelligence? As a result of machines that learn, tomorrow’s work will not differ from today’s practice, but brain automation will replace muscle automation. Immersed in this reality, we could say–paraphrasing the Austrian writer Robert Musil–that the worker takes the bait of technology, but does not see the line that hooks him. Fears are expressed in many quarters that machines will take over the work of large swathes of the current workforce. And why not, when companies constrain their human employees to act like machines?
In the years to come, with the accelerated progress of artificial intelligence, will the Algorithm (“A precise step-by-step plan for a computational procedure that possibly begins with an input value and yields an output value in a finite number of steps”) be the new deity that will replace human creativity in the most diverse forms of work? Or will human beings enhance their own freedom by leveraging technology?
It will be worth reflecting on what Zia Chishti, managing director of Affinity, the world’s leading company in applied artificial intelligence, wrote:
We have not moved a byte forward in understanding human intelligence. We have much faster computers, thanks to Moore’s law, but the underlying algorithms are mostly identical to those that powered machines 40 years ago. Instead, we have creatively rebranded those algorithms. Good old-fashioned “data” has suddenly become “big” (“Artificial Intelligence: winter is coming. Today’s AI is not much better at solving real world problems than its ancestors”, Financial Times, October 17, 2018).
We can therefore conceive the rise of Artificial Intelligence as an opportunity to reflect on work as a combinatory activity of knowing how to Do, Think, Imagine and Understand. – a union that requires familiarity with the arts.
In its survey on the future of work (Perspectives on new work, 2016) Sitra, a Finnish public foundation that invests in projects aimed at increasing the efficiency of the economy, improving the level of education and research, and studying future development scenarios, sheds light on the subjective motivations that intervene to change it. Curiosity prompts learning to keep one’s mind alert. The conservation of mental energy leads to the search for how to operate to reduce stress. Spontaneous socialisation, exchanging thoughts with each other, allows sharing the cognitive load and brings out collective intelligence. Turning our actions to the pleasure of working for and with others, recurring themes in work are communication and the cognitive skills it requires.
From this viewpoint, the worker of tomorrow will become the conceiver of ideas. The former grows the expertise, taking advantage of the experience accumulated to innovate with the constraint of maintaining the existing structures. By strapping a pair of wings to those structures, some incremental innovators think they have built a plane, ironically observed Professor Clayton Christensen, the well-known author of The Dilemma of the Innovator. The ideator fears becoming a stupid expert when two twin revolutions, one of knowledge and the other of technology, lay bare the worker who doesn’t know how to react to the challenges posed by those twins. It is the ideator who reinvents herself by asking questions and then discovering original answers which spawn work the human being will do better than the algorithm.