🔗 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 famous spot for fish soup. However, the navigation app on my phone instructed us to go forward. Weary and in a stifling car, I followed the algorithm's directive. Minutes later, we were stranded at a roadwork site.

A seemingly trivial event, maybe. But one that captures a central question of our time, where technology permeates almost every aspect of existence: whom do we trust more – fellow humans and our own intuition, or the machine?

A Call for Intellectual Maturity and Our Modern Relapse

The influential German philosopher Immanuel Kant once defined the Enlightenment as "man's release from its self-inflicted nonage." This immaturity, he wrote, "represents the incapacity to use one's personal reason without direction from another." For ages, that guiding "other" for human thought was often the priest, the monarch, or the feudal lord – figures purporting to speak for God's voice. To comprehend natural events like volcanic eruptions, people looked for explanations in theology. In organizing the social world, from economics to matters of the heart, religious doctrine acted as the main compass.

“Sapere aude!” or “Dare to use your own understanding!”

Kant maintained that humans always possessed the ability to think rationally. They just didn't have the confidence to use it. With revolutions in America and France, a fresh era arrived: logic would replace blind faith, and the human mind, freed from authority, would become the engine of advancement and a better world.

Today, 250 years later, one might wonder if we are quietly regressing into a state of dependency. An app suggesting a direction is merely the start. AI risks becoming our new "other" – a unseen guide that steers our choices and actions. We risk relinquishing the hard-won autonomy to think independently – and now, not to deities or rulers, but to computer programs.

The Swift Adoption and Subtle Dangers of Algorithmic Reliance

ChatGPT debuted a mere three years ago, and yet a global survey found that an overwhelming majority of respondents had engaged with artificial intelligence in the preceding half-year. Whether deciding on a breakup or selecting a vote, individuals are looking to machines for counsel. Data suggests a large majority of user prompts relate to personal life matters. Even more intriguing than our use of AI for advice is what happens when we let it express for us. Composition is now among the top uses for generative AI, second only to practical requests. The celebrated American author Joan Didion once remarked, “I write entirely to find out what I am thinking.” What transpires when we stop composing? Do we lose that path?

Alarmingly, some evidence suggests the outcome may be yes. A study conducted by the Massachusetts Institute of Technology used brain monitoring to observe the cognitive activity of participants who had access to AI, traditional search engines, or nothing. Those who could use AI showed the lowest cognitive engagement and had trouble quoting their own work. Perhaps most troubling was that over time, individuals in the AI group became increasingly reliant, copying entire blocks of text.

“Inertia and fear,” Kant wrote, “are the reasons why so great a proportion of men … remain in perpetual nonage.”

Certainly, AI's appeal lies in its efficiency. It saves time, minimizes work and – critically – offers a new method to offload responsibility. In his 1941 book, Escape from Freedom, the German psychoanalyst Erich Fromm proposed that the rise of fascism could be understood by a preference to surrender personal freedom in exchange for the comforting security of obedience. AI presents a digital avenue for relinquishing the weight of having to decide for oneself.

The Opacity Dilemma: Trust Without Understanding

AI's primary draw is its capacity to accomplish things beyond our minds – sifting through oceans of data at unprecedented speed. Sitting in the car in Marseille, this was, ultimately, why I opted to believe the app over my friend (a decision she took as an affront). With knowledge of real-time information, surely the app had superior insight – or so I thought.

The core issue is that AI is a opaque system. It produces knowledge, but without necessarily deepening human understanding. We do not truly know how AI reaches its conclusions – including its programmers admit this. Nor can we verify its reasoning against clear, objective criteria. So when we heed AI's advice, we are not being led by logic. We are returning to the domain of belief. In dubio pro machina: when in doubt, trust the machine – that could be our 21st-century credo.

Using Without Losing: The Essential Challenge

AI can be a formidable ally for mankind in rational inquiry. It can help inventing drugs, liberate us from tedious tasks, or manage administrative chores – work that are repetitive and offer little satisfaction. This is beneficial. But Kant and his contemporaries did not advocate for enlightenment just so humans could optimize chores or have more leisure. Critical thinking was not merely about productivity – it was a discipline of freedom and human self-determination.

Human thought is inherently messy and fallible, but it compels us to argue, to doubt, to challenge concepts – and to recognize the boundaries of our own understanding. It fosters self-reliance, both individually and collectively. For Kant, the exercise of reason was never solely about acquiring knowledge; it was about enabling people to become authors of their own lives, and to oppose domination. It was about creating a ethical society grounded in the common foundation of reason and debate, rather than blind belief.

With all the advantages AI offers, the key question is this: how can we harness its potential of superhuman intelligence without eroding human rationality, the cornerstone of the Enlightenment and of free societies themselves? That may be one of the defining questions of our time. It is a question we would do well not to delegate to the algorithm.