Companies that build algorithms do so for two purposes: to gather as much information as possible about our needs and desires, and to induce us to satisfy them through the products they promote. These desires can be material, intellectual, political, spiritual, etc., each with its corresponding product.
Due to a recurring mirage in human history, we come to believe that the above is only a feature of our era, that is, of today’s technology; however, it is understandable that, in reality, desiring and inducing desires is one of the typically human ways of conducting ourselves: we have always been subject to (or, with luck, motivated, and even inspired) placing limits on our desires and needs, and on those of others.
Certainly, Maria Montessori’s great contribution to education was to highlight the indeterminate potential with which children are born and the way adults try to channel it according to their—usually narrow—point of view.
Be that as it may, (for better or for worse), adults usually operate as an algorithm for children. The process is, in the best of cases, like this: compelled to attend to their infinite needs (infinite because they include intellectual, emotional, and even spiritual aspects), we try to identify them, first, as best as possible, and we proceed to satisfy them with the resources that are within our reach or that we can develop from that moment on. However, as these are always limited, we try to convince our children that what we offer them is the best or, flatly, the only thing, showing them the possible penalties they will face if they do not accept it. Although we say that there are no recipes for parenting, in reality, this is a process with a high degree of prior programming. Thus, parents operate, I insist, as an algorithm, a biological, social,and cultural algorithm, at least when they must educate someone.
I say “algorithm,” and there will be no shortage of people who think the worst: that I am turning the human person into a program. And they will be right. But if we accept this as a metaphor, we can say that not all programs are the same, and that while some limit the user to what suits them, others seek human growth and try to stock up on new resources for flourishing. To describe programs/algorithms, one can also use the metaphor of good parents.
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Certainly, this whole way of seeing things may seem reductionist. Still, in reality it is nothing more than a very refined synthesis of something that we have all perceived over the centuries: that the best mothers and fathers, teachers, governors, businesspeople, communicators, etc., see their benefit in the well-being of their daughters and sons, students, customers, interlocutors, etc.; in short, that the best people grow and flourish together with their counterparts, and, on the other hand, the worst, try to limit their peers even more than themselves.
Thus, the metaphor of the family algorithm extends to many other fields. Beyond the home (the first school) and the school (the second home), we have also faced social algorithms. Let’s do a little history, starting with the immediate past.
A few years ago, before the recent boom in AI, I described in this Observatory the attempts of the television stations of the last century (that is, the ones in my youth) to make us act in their interests. I said that these attempts began by identifying, with the greatest clarity, our desires – either by simple intuition or through market research – and by using their “star” actors and actresses to pretend to be our friends and induce us to satisfy those desires through the consumption of certain products. Thus, through their stars, the television stations were our old algorithm, well-suited to the society of that time.
This happened in the last century, but, as I say, it has always happened. We can think of the leaders of the theocratic era: it is not that they imposed beliefs on us, but that they helped us channel our spirituality towards the resources they had, sometimes for everyone’s convenience and other times privileging their own. The same happened with the primitive chieftains of the clan or tribe, who did not always resort to aggression to persuade: usually, they began with empathy, showing – or pretending – that they shared our desires and exhorting the clan to satisfy them according to their proposals, which did not always bring them a true benefit.
The idea of an algorithmic tool could go further and hold that language itself, spoken or written, is such: a complex algorithm with which human beings try to communicate, know their mutual desires, and develop together resources to satisfy them. Aren’t words instruments that channel our potential in terms established by the collective? Isn’t language an instrument of knowledge and expression to channel, altogether, our experience? Aren’t the words that we inherit and use every day reservoirs of enormous wisdom, as shown by etymologies, that remind us that mother, wood, and matter are all in our origin? Do not some words even hold knowledge that transcends the human and synthesizes attributes of nature, such as the word “whistle,” which evokes birds?
However, the question arises: if our current algorithms are very similar to those of the past, how do they differ? The most common answer is that the difference lies in their immense scope and omnipresence. While those of the past assaulted us in public places (in the form of all kinds of posters) or on TV, today’s algorithms travel with us everywhere, on our mobile devices. Such ubiquity seems unprecedented, yet it is only an illusion: one need only think of what, in the theocratic age, the existence of an omnipresent god or gods represented as they omniregulated our ways of thinking, feeling, speaking, and acting.
The truth is that human beings are always willing to follow those who seem to be looking out for us and make us feel acknowledged. It is impossible to underestimate the importance of the latter point. (For someone who has never felt heard, being acknowledged can be a crucial motivator). Therefore, it is a mistake to say that algorithms automate people, that they reduce them to blind and mechanical obedience, in which their subjectivity disappears: If something of a person is always preserved, it is their inner self.
Maria Montessori discovered that error one day, watching a little girl arrange breadcrumbs on the floor in a line. The educator observed something no one in her time was accustomed to seeing. Where others saw a small child repeating a mechanical pattern with what she had at hand, Montessori saw someone unleashing her full inner potential with the little life offered her in that moment (some crumbs), bringing order to them because, in that harmonized way, of something in her own spirit. It was one of the great discoveries, not only in education, but also in the universal way of perceiving children (and everyone else, by the way).
We are someone, not something, not an object that inevitably obeys strict laws, and, even in the narrowest conditions, we remain so. After all, even behind the most forced, most “induced,” almost “obligatory” choices, there is a human being, never a zombie. *
Undoubtedly, great terrors lurk within these algorithms. One is the terror of cyberzombies, meaning that once they detect us, these electronic microbes leave nothing of us, completely sucking out our brains. Another, similar terror is cybersimulation, where the algorithm completely encloses us within ourselves, making us believe we are in contact with the outside world when everything happens only in our minds (living in a kind of solipsism, as it would be called in philosophical terms).
Although these kinds of fears may suit movie scripts, there’s no doubt their threat feels real. Terror has always accompanied technology. That’s why, in the face of something like this, it’s not uncommon for us to become nostalgic and purist and say that we’d be better off returning to a previous way of life, even to a state before speech, to an animal form of life where these conditioning algorithms don’t prevail.
However, it seems a given that once language emerged, there was no turning back. Perhaps some authoritarian and rebellious ape tried to prevent the development of what we now consider our most visible characteristic—that of forming increasingly larger groups through a common language—but such an ape’s rebellion would have failed: increasingly, we admit our condition as technological beings, and we try to embrace technology as essential for our flourishing as a species. (Perhaps in millions of years, we will admit that we are not rational beings, but artificial animals).
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In short… All of the above is nothing more than a way of saying what we already know: the problem with algorithms (and with artificial intelligence in general) is not technology, but how we treat each other through it. The problem is not spoken language, or writing, or books, or any of our wonderful resources, but forgetting that behind the use we make of machines, we are always humans, perhaps reduced or deceived, but always capable of exercising critical thinking and establishing supportive relationships for true well-being and to avoid abuses.
The problem is that we stop in the face of the problem and remain stuck, confused, and isolated. In this sense, school education can focus its efforts not on teaching students to recognize algorithms and move away from them, but on helping them develop their own thinking in the face of any message and communicate effectively and critically with any interlocutor.
It is a fact that, through technology, we create relationships and forms of communication that are less face-to-face; however, it is also true that this process did not begin with the Internet and social networks but with the first person who sent a messenger in their place to say something to another.
Are we, then, inaugurating—in timid, clumsy, and even risky ways—a new paradigm of collectivity, which includes communication through electronic algorithms?
Maybe that’s the case. I don’t lose hope that communication (the art of making things common) will lead us to a better world. So, I want to conclude with what seems to me to be a very good example of hope’s potential. I’m speaking about the movie Miracle on 34th Street, which recreates a true dream algorithm (there are two versions: one released in 1994 and another, classic and perhaps more beautiful, in 1947). The action takes place at Christmas time. The protagonist is Santa Claus (the film suggests he is the real Santa, although we are not sure; however, his unlimited knowledge of children, gifts, and where to get them at the best price—yes, like a magic algorithm—seems to indicate that he is). Among his feats is that of thinking about satisfying the desires of girls and boys without worrying about the interests of the company for which he works. (There, in his beautiful red and white suit, he dedicates himself to listening to the little ones who line up to sit on his lap). Thus, if a girl wants a toy that isn’t in the store or is too expensive, he immediately refers her parents to another store where it is available or on sale, giving them the exact location and price. As a side effect, this generates a wave of prestige for the store and a radical increase in sales. But Santa does not care about that: what matters to him is the children’s happiness, to the point of putting his own freedom at risk.
But we are talking about miracles; at least, in movies (which sometimes resemble them). We humans, have limits, just like our algorithms. However, we know that even within these limits, we can grow. Somehow, as long as there is an algorithm in which ethics prevail, we will remain safe. For now, we must hold on to the few or many that still exist: identify them, leverage them, and protect them as the immensely valuable and powerful tools that they are.
Finally, all that’s left is to wish everyone a Merry Chris…
Oh, sorry!
Translation by Daniel Wetta
