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This past summer, I was caught in gridlocked traffic on the sweltering streets of Marseille. At an intersection, my companion in the passenger seat advised a right turn toward a famous spot for fish soup. However, the navigation app on my phone commanded us to continue straight. Fatigued and in a stifling car, I heeded the app's advice. Moments later, we were stuck at a roadwork site.

A seemingly trivial incident, maybe. But one that captures a defining dilemma of our time, where technology permeates almost every aspect of our lives: who gets our trust to a greater degree – 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 "man's release from its self-imposed nonage." This immaturity, he wrote, "is the incapacity to use one's own understanding without guidance from another." For centuries, that guiding "other" for society was frequently the clergyman, the monarch, or the landowner – entities claiming to channel divine will. To comprehend natural events like volcanic eruptions, people sought answers in religion. In shaping the social world, from economics to love, religious doctrine acted as the primary guide.

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

Kant argued that humans always possessed the ability to think rationally. They just didn't have the confidence to use it. With upheavals in America and France, a fresh era arrived: reason would supplant blind faith, and the intellect, freed from dogma, would become the engine of advancement and a more ethical world.

Today, 250 years later, one might question if we are quietly regressing into a form of dependency. An app dictating a direction is merely the start. AI risks becoming our new "other" – a silent overseer that influences our decisions and behaviors. We risk relinquishing the historically earned courage to reason for ourselves – and this time, not to deities or rulers, but to computer programs.

The Swift Adoption and Hidden Risks of Algorithmic Reliance

ChatGPT debuted a mere three years ago, and already a global survey indicated that an vast number of respondents had used AI in the preceding half-year. Whether contemplating ending a relationship or selecting a vote, individuals are increasingly turning to machines for guidance. Data suggests a large majority of user prompts relate to personal life matters. Even more striking than our use of AI for advice is what occurs when we allow it express for us. Composition is now one of the most common uses for generative AI, just behind everyday tasks. The celebrated American author Joan Didion once remarked, “I write purely to discover what I am thinking.” What transpires when we stop composing? Do we lose that path?

Alarmingly, some evidence suggests the answer may be yes. A study from the Massachusetts Institute of Technology used electroencephalography to track the mental engagement of participants who had access to AI, traditional search engines, or nothing. Those who could rely on AI showed the least brain activity and had trouble quoting their own work. Maybe most troubling was that over time, individuals in the AI group became progressively lazier, pasting large sections of text.

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

Certainly, AI's appeal stems from its efficiency. It saves time, reduces effort and – critically – offers a novel way to abdicate responsibility. In his 1941 book, Escape from Freedom, the German psychoanalyst Erich Fromm argued that the appeal of authoritarianism could be understood by a preference to give up autonomy in exchange for the comforting security of subordination. AI presents a digital avenue for relinquishing the weight of having to think and choose.

The Black Box Problem: Trust Without Understanding

AI's primary draw is its ability to accomplish things outside our minds – sifting through oceans of data at unprecedented speed. Sitting in the car in Marseille, this was, after all, why I opted to believe the app over my companion (a choice she interpreted as an affront). With access to all the data, surely the algorithm had superior insight – or so I believed.

The fundamental problem is that AI operates as a opaque system. It produces knowledge, but not always fostering human comprehension. We do not truly know how AI reaches its decisions – including its creators admit this. Nor can we check its reasoning against clear, objective criteria. So when we follow AI's recommendation, we are not being guided by reason. We are back in the realm of belief. In dubio pro machina: when in doubt, side with the machine – that could be our 21st-century credo.

Using Without Losing: The Essential Challenge

AI can be a powerful tool for humanity in rational inquiry. It can help inventing drugs, free us from tedious tasks, or manage taxes – duties that demand little thought and are unfulfilling. This is beneficial. But Kant and his peers did not champion enlightenment just so humans could assemble better furniture or have extra free time. Independent thought was not merely about efficiency – it was a discipline of liberty and human emancipation.

Human thought is often chaotic and fallible, but it forces us to debate, to doubt, to challenge concepts – and to acknowledge the boundaries of our own knowledge. It fosters confidence, both personally and as a society. For Kant, the exercise of reason was never solely about information; it was about empowering people to become agents of their own lives, and to oppose control. It was about creating a ethical society grounded in the shared principle of reason and debate, rather than blind belief.

With all the undeniable benefits AI offers, the key question is this: how can we harness its promise of superhuman intelligence without undermining human rationality, the bedrock of the Enlightenment and of free societies themselves? That is likely one of the defining questions of our century. It is a question we would do well not to outsource to the algorithm.