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This recent season, I found myself navigating in gridlocked traffic on the scorching streets of a southern French city. At a crossing, my friend in the front seat advised a right turn toward a famous spot for bouillabaisse. Yet, the digital guide on my phone instructed us to go forward. Weary and in a stifling car, I followed the app's advice. Minutes later, we were stranded at a roadwork site.

A seemingly trivial event, maybe. But one that captures a defining dilemma of our era, where digital tools permeates almost every aspect of our lives: who gets our trust to a greater degree – fellow humans and our personal instincts, or the machine?

The Enlightenment's Promise and A Contemporary Backslide

The influential German philosopher Immanuel Kant once defined the Enlightenment as "man's release from its self-inflicted immaturity." This state, he wrote, "is the incapacity to use one's own understanding without direction from an external source." For centuries, that guiding "other" for society was frequently the clergyman, the king, or the feudal lord – entities purporting to speak for divine will. To comprehend phenomena like volcanic eruptions, people looked for explanations in theology. In organizing the fabric of society, from economics to matters of the heart, religious doctrine acted as the primary guide.

“Sapere aude!” or “Dare to use your reason!”

Kant argued that humans always possessed the ability to think rationally. They simply lacked the confidence to use it. With upheavals in America and France, a new dawn arrived: logic would supplant superstition, and the human mind, freed from dogma, would become the driver of progress and a better world.

Now, 250 years later, one might question if we are slipping back into a form of dependency. An app dictating a driving route is just one example. Artificial intelligence risks becoming our new "other" – a unseen overseer that influences our choices and actions. We risk ceding the historically earned courage to reason for ourselves – and this time, not to gods or kings, but to lines of code.

The Swift Adoption and Hidden Risks of AI Dependence

ChatGPT debuted only in 2022, and yet a recent study found that an vast number of people had used AI in the previous six months. Whether deciding on ending a relationship or choosing a candidate, individuals are increasingly turning to machines for guidance. Research 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 among the top uses for generative AI, second only to practical requests. The celebrated 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 suggests the outcome may be yes. A study conducted by the Massachusetts Institute of Technology used electroencephalography to observe the cognitive activity of participants who had access to AI, Google, or nothing. Those who could rely on AI displayed the least brain activity and had trouble accurately recalling their own work. Perhaps most concerning 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 perpetual nonage.”

Of course, AI's appeal lies in its efficiency. It is fast, minimizes work 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 personal freedom in exchange for the comforting security of subordination. AI offers a digital method of surrendering the burden of having to think and choose.

The Black Box Problem: Faith Over Reason

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, ultimately, why I opted to trust the app over my friend (a decision she took as an affront). With access to real-time information, certainly the algorithm had superior insight – or so I believed.

The fundamental problem is that AI is a opaque system. It generates answers, but not always fostering human comprehension. We cannot fully grasp the process behind its conclusions – including its creators acknowledge the opacity. Nor can we check its logic against transparent standards. So when we heed AI's advice, we are not being guided by reason. We are returning to 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 Critical Balance

AI can be a formidable ally for mankind in scientific pursuit. It can aid in medical research, free us from tedious tasks, or handle administrative chores – work that demand little thought and are unfulfilling. All to the good. But Kant and his contemporaries did not champion enlightenment just so humans could optimize chores or have more leisure. Independent thought was not just about productivity – it was a discipline of freedom and human self-determination.

Human thought is often chaotic and fallible, but it compels us to argue, to doubt, to test ideas – and to recognize the boundaries of our own understanding. It fosters confidence, both individually and as a society. For Kant, the exercise of reason was never only about information; it was about enabling people to become agents of their own destinies, and to oppose control. It was about creating a moral community grounded in the shared principle of reason and debate, rather than unquestioning acceptance.

With all the undeniable benefits AI offers, the paramount challenge is this: how can we harness its promise of superhuman intelligence without undermining human reasoning, the bedrock of the Enlightenment and of liberal democracy themselves? That may be one of the central dilemmas of our century. It is a question we would do well not to delegate to the algorithm.