Work in the society of the future

I watched “É ou não é” about the future of work. In the society of the future there will not be work for everyone and it will be difficult to requalify everyone. And even requalification will be temporary. There is no profession that will not be affected by Artificial Intelligence (AI) and Karl Marx’s worst nightmare, the total exemption of man from work and production, could become a reality.

Last year, I published the book – Intelciety: Intelligent Society. Are we ready for the challenge? – in which I sought to contribute to the reflection on the impact of AI on society.

Everything we take for granted will change. The intelligent society, which I call Intelciety, will be something between the realization of what science fiction has been able to imagine1 and much more beyond that; a fully autonomous, automated, and self-sufficient society capable of managing itself, completely regulated by intelligence, (human and/or artificial, or both) capable of dispensing with human supervision.

Although we are on the way, we are still a long way from achieving Intelciety. We are currently living in a period of transition between the society we took for granted and the one that is emerging. Obviously, this transition period – pre-Intelciety – does not unfold linearly. It will take place with ruptures and bounces; it will occur at different speeds and times all over the planet.

How do we navigate this ongoing disruption we live in? This is the big question. The problem is that what we thought would only happen decades from now is happening at dizzying speed.

It is important to note that the impact of AI on the labor market will be diverse. AI will directly replace people, but it will not perform tasks as a human being would; it will increase productivity due to the reduction in the number of people needed to carry out tasks and it will change business strategies, causing restructurings that could close and create new departments.

As this reflection is about change, it is important to mention this at the very beginning. There is no civilizational and social evolution that has not led to change and rupture. The control of fire, the transition from hunting and gathering to agriculture and the domestication of animals, and so on, from the Stone Age to the Age of Metals, from the Ancient or Classical Age to the Middle Ages, the Modern Age, the Contemporary Age. Even the transition from prehistory to history had technical and social (economic and political) consequences. All developments have led to social disruptions and restructurings, including the withering away of human activities and the emergence of new professions. Since the Industrial Revolution, the cadence of the emergence and disappearance of new professions and human specializations is a more noticeable reality. More recently, the products of the fourth industrial revolution have further accelerated these mutations. In other words, new professions are not just signs of our times. They always have been. And as innovation and development have given rise to new professions and activities, professions that have become obsolete faded to the point of disappearance.

The substitution of human labor has been ongoing since the 1960s (even earlier when considering the moving assembly line developed for the Ford Model T on October 7, 1913). So, if this trend has persisted for decades, why is the current generation of machines problematic? It is because these machines can eliminate the need for specialized human labor, prompting a shift from centralized to decentralized collaborative production. We’re not just talking about simple mechanization or automation. It’s critical to understand that this new generation of robots represents genuine cyber-physical systems, which will extend beyond industrial applications. Consequently, the substitution of human labor can happen on an unprecedented scale, something unthinkable until now.

In my opinion, three factors are now different.

• First, the (artificial) intelligence factor, which can (or will) eliminate supervision and even the need for human collaboration.
• Second, it will be machines (robots) that will replace human labor. Not only in the blue-collar areas (agriculture, construction, production lines, assembler and machine operator, etc.). It should also be pointed out that AI agents will make many white-collar functions obsolete and faster.
• Third, how promptly change happens. Some of the professions that have appeared in the last ten years are now among those most likely to be replaced by AI and robotics.

Future preparation begins with education, focusing on the essentials: A solid grasp of language and mathematics, coupled with skills in critical thinking, problem-solving, active learning, resilience, stress tolerance, and flexibility.

It might not seem like it, but the greatest challenge we face today is in education (transmission of knowledge). Two immediate changes are necessary: Firstly, our teaching methods, and secondly, our curriculum content. We are preparing young people for jobs that will either vanish or become specialty niches that too may become obsolete. Regardless of educational level, and even though numerous laws and postulates forming the foundation of various scientific fields are being challenged as “dogmas,” their established validity ensures that the scientific underpinning of knowledge will persist. Thankfully, the validity of knowledge is not altered by protests nor by ignorance or cancellations. However, the issue lies with the current teaching methodology, which is clearly inadequate. If we persist with these outdated methods, our children will struggle to keep pace, much less compete with machines. This suggests that society (along with its various structures) will undergo significant transformation. Secondly, we cannot continue to focus primarily on the measurement and evaluation of knowledge. It seems imperative to me to give students skills that allow them to adapt to the new circumstances that change brings about.

Everything indicates that a generalist has a better chance of keeping his job for longer than a specialist. The distinction between a generalist and a specialist, which leads to a superior adaptability, is straightforward. A generalist has a broad knowledge base that enables him to delve deeply into a subject when needed. In contrast, a specialist, confined to a specific area of expertise that may become outdated, will find it more challenging to transition into a new domain than a generalist. Consequently, generalists are often more equipped to thrive in an environment of constant change.

Prioritizing equal outcomes over equal opportunities has only served to diminish human potential and leave young people ill-prepared for life. Persisting in lowering standards to avoid offending sensitivities and self-esteem of the youth, allowing them to advance to university without sufficient knowledge — a reality prevalent in various countries — is a serious mistake. Acknowledging these issues is crucial for overcoming them. Only by recognizing their existence can we turn weaknesses into strengths.

Certainly, such a reform, which entails a break and potential upheaval, will have its consequences, including some adverse effects. Nonetheless, the consequences and repercussions will be far more significant and profound if no action is taken. It is impossible to prepare people for living an intelligent society with obsolete assumptions that do not align with current reality.

Consequently, an educational reform is imperative and should be immediate, not delayed for years. This reform should be rooted in the foundational elements of knowledge and communication: the alphanumeric system. As such, there are three principal learning vectors: read and write (language), count (mathematics) and think, desirably, think critically (philosophy). These should be teaching core pillars from the earliest stages through to university. The teaching curriculum must also encompass foreign languages, social sciences (history, economics, geography, citizenship), natural sciences (physics, chemistry, biology), physical education, and computing, specifically, data science.

Why data science? In addition to the increased demand for data scientists, the fact that it is a multidisciplinary area and an interface between statistics and computer science makes it an area with greater employment longevity. Data science integrates scientific methods, processes, algorithms, and systems to analyze a vast array of data types, whether noisy, vibrant, fuzzy, structured, or unstructured. It encompasses the study and analysis of scientific, social, economic, financial, political, geographic, historical, marketing, demographic, biological, and psychological data, facilitating quicker and more robust knowledge acquisition for decision-making. Although data science has been around for over three decades, the advent of extensive databases and machine learning has recently enhanced its significance and value. In my view, it is a field with a promising future. Moreover, since data scientists are involved in the development, maintenance, and oversight of AI, this role offers the potential for greater career longevity. Fundamental skills such as reading, writing, arithmetic, critical thinking, and computer literacy are crucial across various domains, ranging from linguistics to medicine, and encompassing fields like engineering, architecture, etc.

Thus, it is crucial to revise the foundations of reasoning and analysis. The society of the future is unlikely to be managed based on present assumptions. The rapid pace and extensive scope of technological disruption render the unforeseen commonplace and perpetual challenges routine. No nation or economy in the world will be immune or able to stand apart from this (r)evolution.

Teaching methodologies must change. The model adopted by Pedro Santa Clara at Escola 42 and Tumo – which fosters student cooperation and collaboration while holding them accountable and allowing progression based on effort and ambition – merits serious consideration.

Using the example of this model, I think that the systems of the great philosophical schools of ancient Greek philosophical schools, where students engaged in debates, could be modernized. Viewing knowledge as both transversal and detailed can lead to reimagined intersections that facilitate interdisciplinary learning, nurturing critical thinking and problem-solving skills. While I may be mistaken, it appears to be a positive move towards equipping youth for the real world, and beyond that, it could also enhance imagination, curiosity, and innovation. Additionally, adapting the Japanese educational model, characterized by five principles: (1) instilling proper behavior and respect for individuals from all economic backgrounds; (2) fostering independence and teamwork, with students managing school cleanliness from an early age; (3) cultivating environmental appreciation and preservation; (4) prioritizing the importance of knowledge, not grades; and (5) focusing on respect, courtesy, and punctuality, can also be beneficial.

Regarding the use of AI in teaching, these four ideas – 1) Personalized learning; 2️) Intelligent Tutoring; 3) Enhanced administrative tasks; 4) Data-driven insights – presented by Charlotte Joy Trudgill, is also worth considering. Nonetheless, the principal transformation lies in altering our perception of children and students and, paramountly, fostering critical thinking skills.

It can never be said enough. Critical thinking is the factor that will help man’s relevance in the future.

One thing is certain. It is not possible to continue training young people for professions that will disappear or become niche specialties, which are also likely to disappear.