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This recent season, I found myself navigating in gridlocked traffic on the scorching streets of a southern French city. At an intersection, my friend in the front seat advised a right turn toward a renowned spot for bouillabaisse. Yet, the digital guide on my phone instructed us to continue straight. Weary and in a stifling car, I heeded the algorithm's directive. Moments later, we were stuck at a construction site.

A minor event, perhaps. But one that encapsulates a defining question of our era, where technology permeates almost every aspect of existence: who gets our trust to a greater degree – other people and our personal instincts, or the algorithm?

The Enlightenment's Promise and A Contemporary Backslide

The renowned German philosopher Immanuel Kant once defined the Enlightenment as "humanity's emergence from its self-inflicted nonage." This immaturity, he wrote, "represents the incapacity to use one's personal reason 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 explain natural events like volcanic eruptions, people looked for explanations in religion. In organizing the fabric of society, from commerce to matters of the heart, religious doctrine served as the primary guide.

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

Kant maintained that humans had the capacity for reason. They simply lacked the confidence to use it. With upheavals in the 18th century, a new dawn arrived: logic would replace blind faith, and the intellect, liberated from authority, would become the driver of progress and a better world.

Today, two and a half centuries later, one might wonder if we are quietly regressing into a state of dependency. An app suggesting a driving route is merely the start. AI risks becoming our new "other" – a silent overseer that steers our choices and actions. We are in danger of ceding the hard-won autonomy to think independently – and now, not to gods or kings, but to computer programs.

The Swift Adoption and Hidden Risks of Algorithmic Reliance

ChatGPT was launched a mere three years ago, and yet a recent study found that an overwhelming majority 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 algorithms for guidance. Research suggests a significant portion of user queries relate to non-work topics. Even more intriguing than our use of AI for judgment is what occurs when we allow it express for us. Writing is now one of the most common uses for tools like ChatGPT, second only to practical requests. The celebrated American author Joan Didion famously said, “I write purely to find out what I am thinking.” What transpires when we cease writing? Do we lose that path?

Alarmingly, emerging research hints the answer may be affirmative. A study from the Massachusetts Institute of Technology used electroencephalography to track the mental engagement of essay writers who had access to AI, Google, or no aids. Those who could rely on AI displayed the lowest brain activity and had difficulty quoting their own work. Maybe most concerning was that over time, individuals in the AI group grew increasingly reliant, copying entire blocks of text.

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

Certainly, AI's attraction stems from its efficiency. It saves time, minimizes work and – importantly – offers a new method 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 surrender autonomy in for the sake of the reassuring certainty of obedience. AI offers a digital method of relinquishing the weight of having to decide for oneself.

The Black Box Problem: Trust Without Understanding

AI's primary draw is its capacity to accomplish things beyond human capability – analyzing vast datasets at lightning pace. Sitting in the car in Marseille, this was, ultimately, why I opted to believe the app over my companion (a choice she interpreted as an affront). With knowledge of all the data, surely the algorithm must know best – or so I believed.

The core issue is that AI is a opaque system. It produces answers, but not always deepening human comprehension. We cannot fully grasp the process behind its decisions – including its programmers acknowledge the opacity. Nor can we verify its reasoning against transparent standards. So when we heed AI's advice, we are not being guided by reason. We are back in the domain of belief. In dubio pro machina: when in doubt, trust the machine – that could be our future guiding principle.

Using Without Losing: The Critical Balance

AI can be a powerful tool for mankind in rational inquiry. It can help medical research, liberate us from "bullshit jobs", or manage administrative chores – duties that demand little thought and are unfulfilling. This is beneficial. But Kant and his peers did not advocate for reason over faith just so humans could assemble better furniture or have more leisure. Independent thought was not just about efficiency – it was a practice of liberty and human self-determination.

Human thought is often chaotic and fallible, but it compels us to argue, to question, to test ideas – and to recognize the limits of our own knowledge. It builds self-reliance, both individually and as a society. For Kant, the use of reason was never only about information; it was about enabling people to become authors of their own lives, and to oppose domination. It was about building a moral community based on the shared principle of reason and debate, rather than blind belief.

With all the undeniable benefits AI brings, the key question remains: how can we leverage its potential of advanced capability without eroding human rationality, the cornerstone 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 machine.