I have a partly joking, partly serious argument: if there’s anyone to blame for the sad state of the world today, it’s the men in cafés of Vienna in the late nineteenth and early twentieth centuries.
The Viennese Influence on Selfhood and Science
In those cafés, men sketched new accounts of the self and the study of the universe at large. At first, there was Freud’s psychoanalysis. A generation later, these men codified a new scientific philosophy: the Vienna Circle’s logical empiricism.
Across the Western tradition, the self kept being remade. Augustine made us ask “Who am I?”, Descartes rationalized it, Locke personalized identity through memory, and Freud psychologized it.
While logical empiricism contributed to scientific research and finally to AI, it also reduced complex historical, cultural, and social phenomena to physical or observational descriptions. A lot of academic research lost sight of what matters most to humans: symbols, intentions, purpose, meaning, and context.
Seeds of Individualism and Mass Persuasion
The Viennese mix helped seed two powerful ideas of our time: individualism and the art of mass persuasion. These ideas paved the way for consumer culture, contributing to widespread suffering among living entities on the planet. Freud’s concepts found a public afterlife in propaganda, public relations, and advertising. In Vienna, the ideas of mass persuasion made an impression on a young Adolf Hitler. Today, consumer culture continues to rely heavily on mass persuasion, as do the dictators of our time.
Impact on Artificial Intelligence
Are these ideas also present in the way we think about and develop Artificial Intelligence (AI) today? If we critically examine the common uses of AI, the answer is obvious: Yes.
We crave recognition and want to be not only someone but better off than others. In social media, we collect “likes” and show off how well we’re doing. Our leaders show us the path: More money, oil, minerals, or land are better than less. The one who has the most is the best—perhaps worthy of a peace prize. Social media plays a role here too; personal media lets you tell the rest, the losers.
The social media platforms—so-called platform capitalism—with business models based on advertising focus on individualism and mass persuasion. Their AI is optimized for these purposes. The economy reliant on consumer culture adapted first to the AI era; power and politics came second.
Reconsidering AI in Education
So, should we discuss this when considering using AI in teaching and learning? I am critical about the idea of AI in education. I see (deep) human learning as so complex—historical, cultural, social, political, and situated—that (narrow) AI, such as ChatGPT, can help very little. You may bounce ideas with AI, but it doesn’t teach you to think.
The first step in Ai in education would be to balance the playing field in terms of the culture of individualism and mass persuasion. Education should help people move beyond individualism and consumerism, not to strength it.
Rethinking Thinking and Learning
It is a common claim that thinking comes first and then we learn something. We think all the time. When we learn, we gain a relatively lasting change in our way of thinking, understanding, and acting. It doesn’t take much thinking to see how silly this dichotomy between thinking and learning is.
Thinking, acting in the physical world, and learning are all intertwined. We think not only with our brains but with our entire nervous system, enabling continuous flow of information to and from the body—endless sensation. Some people call this the mind-body connection. As living entities, we change all the time, as does our immediate surrounding and environment. This is the idea of life—continuing change.
So if learning is thinking and thinking is learning, why do we separate these concepts? Is learning something humans can automate, like riding a bike? A super useful skill, learned and not needing much thought.
A lot of thinking can be automated too. It saves energy and often makes life easier. You simply believe what someone tells you and adapt to their way of thinking. A lot of human activity is precisely this: doing things as they are done.
Machine learning and artificial intelligence are about automatization, not about thinking. When contemplating learning and aiming to learn to think, somehow it feels better to aim to think and act with a thinking things, rather than something that is automated. Right?
The paradox: Back to Cafés?
Thinking together is powerful. So head to a café, turn off your AI assistant, shut your laptop, and turn toward other thinking beings.
Teemu Leinonen 