🔗 Share this article

This past summer, I was caught in gridlocked traffic on the sweltering streets of Marseille. At an intersection, my companion in the front seat suggested a right turn toward a renowned spot for fish soup. However, the navigation app on my phone instructed us to continue straight. Weary and overheated, I heeded the app's directive. Minutes later, we were stuck at a construction site.

A minor incident, maybe. But one that captures a defining dilemma of our era, where technology permeates nearly every facet of existence: who gets our trust more – other people and our own intuition, or the machine?

The Enlightenment's Promise and A Contemporary Backslide

The influential German philosopher Immanuel Kant famously described the Enlightenment as "humanity's emergence from its self-inflicted nonage." This immaturity, he argued, "represents the incapacity to use one's own understanding without guidance from an external source." For ages, that guiding "other" for society was frequently the priest, the king, or the feudal lord – figures purporting to channel God's voice. To explain phenomena like volcanic eruptions, people looked for explanations in religion. In shaping the social world, from commerce to matters of the heart, religious doctrine served as the main compass.

“Sapere aude!” or “Have courage to use your own understanding!”

Kant argued that humans had the capacity for reason. They simply lacked the confidence to employ it. With revolutions in the 18th century, a fresh era emerged: reason would supplant superstition, and the human mind, liberated from dogma, would become the driver of progress and a better world.

Today, 250 years later, one might wonder if we are slipping back into a state of dependency. An app dictating a driving route is just one example. Artificial intelligence threatens to become our new "other" – a silent overseer that influences our decisions and behaviors. We are in danger of ceding the historically earned courage to reason for ourselves – and this time, not to gods or kings, but to computer programs.

The Swift Adoption and Hidden Risks of Algorithmic Reliance

ChatGPT was launched a mere three years ago, and yet a global survey indicated that an vast number of respondents had used AI in the previous six months. Whether deciding on a breakup or choosing a candidate, individuals are looking to algorithms for counsel. Research suggests a significant portion of user queries concern personal life matters. Even more intriguing than our reliance on AI for judgment is what occurs when we allow it express for us. Writing is now one of the top uses for tools like ChatGPT, second only to practical requests. The late American author Joan Didion famously said, “I write entirely to discover what I am thinking.” What transpires when we cease writing? Do we cease discovering?

Alarmingly, some evidence hints the answer may be affirmative. A study from the Massachusetts Institute of Technology used brain monitoring to observe the cognitive activity of participants who had access to AI, Google, or nothing. Those who could use AI displayed the least cognitive engagement and had trouble accurately recalling their own work. Maybe most concerning was that over time, participants in the AI group became increasingly reliant, pasting entire blocks of text.

“Laziness and cowardice,” Kant wrote, “are the reasons why so many of men … remain in lifelong immaturity.”

Certainly, AI's attraction stems from its efficiency. It is fast, reduces effort and – importantly – offers a new method to abdicate accountability. In his 1941 book, Escape from Freedom, the German psychoanalyst Erich Fromm proposed that the appeal of authoritarianism could be understood by a preference to surrender personal freedom in exchange for the comforting security of obedience. AI offers a digital avenue for relinquishing the burden of having to decide for oneself.

The Opacity Dilemma: Trust Without Understanding

AI's greatest allure is its ability to perform tasks beyond human capability – sifting through oceans of data at unprecedented speed. Stuck in the car in Marseille, this was, ultimately, why I chose to believe the machine over my companion (a choice she took as an affront). With access to all the data, certainly the algorithm had superior insight – or so I believed.

The core issue is that AI is a black box. It produces answers, but without necessarily deepening human understanding. We do not truly know the process behind its decisions – even its creators admit this. Nor can we verify its reasoning against transparent standards. So when we follow AI's recommendation, we are not being led by logic. We are back in the realm of faith. In dubio pro machina: when in doubt, side with the machine – that may become our 21st-century guiding principle.

Using Without Losing: The Critical Balance

AI can be a powerful tool for humanity in scientific pursuit. It can aid in medical research, liberate us from tedious tasks, or manage taxes – work that are repetitive and are unfulfilling. This is beneficial. But Kant and his peers did not champion enlightenment just so humans could optimize chores or have extra free time. Independent thought was not merely about productivity – it was a practice of liberty and human self-determination.

Human thought is inherently messy and fallible, but it forces us to argue, to question, to test ideas – and to recognize the limits of our own knowledge. It builds self-reliance, both individually and collectively. For Kant, the exercise of reason was never only about acquiring knowledge; it was about empowering people to become agents of their own lives, and to resist control. It was about creating a moral community based on the shared principle of reason and debate, rather than unquestioning acceptance.

With all the advantages AI brings, the key question is this: how can we harness its promise of superhuman intelligence without eroding human rationality, the bedrock of the Enlightenment and of free societies itself? That may be one of the central dilemmas of our century. It is a question we must strive not to outsource to the machine.