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This recent season, I found myself navigating in congested traffic on the sweltering streets of Marseille. At an intersection, my companion in the front seat advised a right turn toward a famous spot for fish soup. However, the digital guide on my phone commanded us to go forward. Fatigued and overheated, I followed the algorithm's directive. Moments later, we were stuck at a construction site.

A seemingly trivial event, maybe. But one that encapsulates a defining question of our era, where technology permeates nearly every facet of our lives: whom do we 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 once defined the Enlightenment as "humanity's emergence from its self-inflicted nonage." This immaturity, he wrote, "is the incapacity to use one's own understanding without direction from another." For ages, that directing force for human thought was frequently the clergyman, the king, or the feudal lord – entities claiming to channel God's voice. To comprehend phenomena like volcanic eruptions, people sought answers in theology. In organizing the social world, from commerce to love, religious doctrine served as the main compass.

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

Kant maintained that humans always possessed the capacity for reason. They just didn't have the confidence to employ it. With revolutions in America and France, a new dawn arrived: reason would supplant blind faith, and the intellect, liberated from authority, would become the engine of advancement and a more ethical world.

Today, two and a half centuries later, one might question if we are quietly regressing into a state of dependency. An app dictating a direction is merely the start. AI threatens to become our new "other" – a unseen overseer that steers our choices and actions. We risk ceding the hard-won autonomy to think independently – and this time, not to gods or kings, but to lines of code.

The Swift Adoption and Subtle Dangers of Algorithmic Reliance

ChatGPT debuted only in 2022, and yet a global survey found that an overwhelming majority of people had used AI in the preceding half-year. Whether contemplating ending a relationship or choosing a candidate, individuals are looking to machines for guidance. Research suggests a significant portion of user prompts relate to personal life matters. Even more striking than our reliance on AI for judgment is what happens when we allow it speak for us. Composition is now among the most common uses for tools like ChatGPT, just behind practical requests. The late American author Joan Didion famously said, “I write entirely to find out what I am thinking.” What occurs when we stop composing? Do we cease discovering?

Worryingly, emerging research suggests the answer may be yes. A study conducted by the Massachusetts Institute of Technology used electroencephalography to observe the cognitive activity of participants who had could use AI, traditional search engines, or no aids. Those who could use AI displayed the lowest brain activity and had difficulty accurately recalling their own work. Maybe most troubling was that over time, participants in the AI group grew increasingly reliant, copying entire blocks of text.

“Inertia and fear,” Kant wrote, “are the reasons why so great a proportion of men … stay in lifelong immaturity.”

Of course, AI's appeal stems from its convenience. It is fast, minimizes work and – critically – offers a new method to offload accountability. In his 1941 book, Escape from Freedom, the German psychoanalyst Erich Fromm argued that the rise of fascism could be partly explained by a human tendency to surrender autonomy in exchange for the reassuring certainty of subordination. AI offers a modern avenue for surrendering the burden of having to decide for oneself.

The Opacity Dilemma: Trust Without Understanding

AI's greatest allure is its ability to perform tasks outside human capability – sifting through oceans of data at lightning pace. Sitting in the car in Marseille, this was, after all, why I chose to believe the app over my companion (a decision she took as an insult). With access to real-time information, certainly the app must know best – or so I believed.

The fundamental problem is that AI is a black box. It produces answers, but not always deepening human comprehension. We cannot fully grasp how AI reaches its conclusions – including its programmers admit this. Nor can we check its logic against clear, objective criteria. So when we follow AI's advice, we are not being led by logic. We are back in the realm of belief. In dubio pro machina: when in doubt, side with the machine – that could be our future credo.

Using Without Losing: The Critical Balance

AI can be a powerful tool for humanity in scientific pursuit. It can help medical research, liberate us from "bullshit jobs", or manage taxes – duties that demand little thought and offer little satisfaction. This is beneficial. But Kant and his contemporaries did not advocate for enlightenment just so humans could assemble better furniture or have more leisure. Critical thinking was not merely about efficiency – it was a discipline of liberty and human self-determination.

Human thought is inherently messy and error-prone, but it compels us to debate, to doubt, to challenge concepts – and to acknowledge the limits of our own understanding. It builds self-reliance, both individually and collectively. For Kant, the use of reason was never solely about information; it was about enabling people to become agents of their own destinies, and to resist domination. It was about creating a moral community based on the common foundation of reason and debate, rather than blind belief.

With all the advantages AI offers, the key question remains: how can we leverage its promise of advanced capability without eroding human rationality, the cornerstone of the Enlightenment and of free societies themselves? That may be one of the central dilemmas of our time. It is a question we would do well not to outsource to the algorithm.