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This recent season, I found myself navigating in gridlocked traffic on the sweltering streets of a southern French city. At an intersection, my companion in the passenger seat advised a right turn toward a renowned spot for bouillabaisse. However, the navigation app on my phone instructed us to go forward. Fatigued and overheated, I followed the algorithm's advice. Moments later, we were stranded at a roadwork site.

A minor event, perhaps. But one that captures a central dilemma of our time, where technology permeates nearly every facet of our lives: who gets our trust more – fellow humans and our personal instincts, or the algorithm?

The Enlightenment's Promise and Our Modern Relapse

The influential German philosopher Immanuel Kant famously described the Enlightenment as "humanity's emergence from its self-inflicted immaturity." This immaturity, he wrote, "represents the inability to use one's own understanding without guidance from an external source." For centuries, that directing force for human thought was often the clergyman, the king, or the landowner – figures claiming to speak for divine will. To comprehend phenomena like changing seasons, people looked for explanations in religion. In shaping the fabric of society, from economics to matters of the heart, faith served as the primary guide.

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

Kant maintained that humans always possessed the ability to think rationally. They simply lacked the boldness to employ it. With revolutions in the 18th century, a new dawn emerged: logic would replace superstition, and the intellect, freed from authority, would become the driver of progress and a better world.

Today, 250 years later, one might question if we are slipping back into a state of dependency. An app suggesting a direction is merely the start. AI risks becoming our new "other" – a silent guide that steers our choices and actions. We are in danger of ceding the hard-won autonomy to reason for ourselves – and now, not to gods or kings, but to lines of code.

The Rapid Rise and Subtle Dangers of Algorithmic Reliance

ChatGPT debuted only in 2022, and yet a global survey found that an vast number of respondents had engaged with artificial intelligence in the preceding half-year. Whether contemplating ending a relationship or selecting a vote, individuals are looking to algorithms for counsel. Data suggests a large majority of user queries relate to non-work topics. Even more intriguing than our reliance on AI for advice is what happens when we let it speak for us. Writing is now one of the most common uses for generative AI, second only to practical requests. The celebrated American author Joan Didion once remarked, “I write purely to discover what I am thinking.” What occurs when we stop composing? Do we cease discovering?

Alarmingly, emerging research suggests the answer may be affirmative. A study from 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 least cognitive engagement and had difficulty accurately recalling their own work. Maybe most concerning was that after a few months, individuals in the AI group became progressively lazier, copying large sections of text.

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

Certainly, AI's attraction lies in its efficiency. It is fast, reduces effort and – critically – offers a new method to offload responsibility. In his 1941 book, Escape from Freedom, the German psychoanalyst Erich Fromm argued that the appeal of authoritarianism could be partly explained by a preference to surrender autonomy in exchange for the reassuring certainty of subordination. AI presents a modern method of relinquishing the burden of having to think and choose.

The Opacity Dilemma: Trust Without Understanding

AI's primary draw is its ability to perform tasks outside human capability – sifting through vast datasets at unprecedented speed. Sitting in the car in Marseille, this was, after all, why I chose to trust the app over my friend (a choice she interpreted as an affront). With access to all the data, surely the algorithm must know best – or so I believed.

The fundamental problem is that AI is a black box. It generates answers, but not always fostering human comprehension. We do not truly know how AI reaches its conclusions – even its creators admit this. Nor can we verify its logic against clear, objective criteria. So when we heed AI's recommendation, we are not being guided by reason. We are returning to the domain of belief. In dubio pro machina: when in doubt, side with the machine – that could be our 21st-century credo.

Harnessing Without Eroding: The Essential Challenge

AI can be a formidable ally for humanity in scientific pursuit. It can aid in medical research, free us from "bullshit jobs", or manage taxes – work that demand little thought and offer little satisfaction. This is beneficial. But Kant and his peers did not advocate for enlightenment just so humans could optimize chores or have more leisure. Critical thinking was not just about efficiency – it was a practice of freedom and human emancipation.

Human thought is inherently messy and fallible, but it forces us to debate, to question, to test ideas – and to recognize the limits of our own understanding. It builds confidence, both personally 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 destinies, and to oppose domination. It was about building a ethical society based on the common foundation of reason and debate, rather than unquestioning acceptance.

With all the undeniable benefits AI offers, the key question remains: how can we harness its promise of superhuman intelligence without eroding human reasoning, the bedrock of the Enlightenment and of liberal democracy itself? That may be one of the central dilemmas of our century. It is a question we must strive not to delegate to the machine.