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This recent season, I was caught in gridlocked traffic on the sweltering streets of Marseille. At a crossing, my friend in the front seat advised a right turn toward a renowned spot for fish soup. However, the digital guide on my phone instructed us to continue straight. Weary and in a stifling car, I followed the app's directive. Moments later, we were stranded at a construction site.

A seemingly trivial incident, perhaps. But one that captures a central question of our era, where technology permeates almost every aspect of our lives: who gets our trust more – other people and our own intuition, or the algorithm?

The Enlightenment's Promise and Our Modern Relapse

The renowned German philosopher Immanuel Kant famously described the Enlightenment as "man's release from its self-inflicted immaturity." This immaturity, he wrote, "represents the inability to use one's own understanding without direction from another." For ages, that guiding "other" for society was often the clergyman, the king, or the feudal lord – entities purporting to channel God's voice. To explain phenomena like changing seasons, people looked for explanations in theology. In organizing the fabric of society, from commerce to love, faith served 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 revolutions in the 18th century, a fresh era emerged: reason would replace blind faith, and the intellect, freed from authority, would become the engine of progress and a more ethical world.

Now, two and a half centuries later, one might question if we are quietly regressing into a state of dependency. An app suggesting a direction is merely the start. Artificial intelligence threatens to become our new "other" – a unseen overseer that influences our decisions and actions. We are in danger of ceding the historically earned courage to reason for ourselves – and this time, not to deities or rulers, but to lines of code.

The Swift Adoption and Subtle Dangers of AI Dependence

ChatGPT was launched a mere three years ago, and already a global survey found that an overwhelming majority of respondents had used AI in the preceding half-year. Whether deciding on a breakup or selecting a vote, individuals are increasingly turning to machines for counsel. Research suggests a significant portion of user queries relate to non-work topics. Even more striking than our use of AI for advice is what happens when we let it express for us. Writing is now one of the most common uses for tools like ChatGPT, second only to practical requests. The late American author Joan Didion famously said, “I write entirely to discover what I am thinking.” What occurs when we stop composing? Do we cease discovering?

Alarmingly, emerging research hints the answer may be yes. A study conducted by the Massachusetts Institute of Technology used brain monitoring to track the mental engagement of participants who had could use AI, traditional search engines, or no aids. Those who could use AI showed the lowest cognitive engagement and had difficulty quoting their own work. Maybe most troubling was that after a few months, 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 attraction stems from its convenience. It is fast, minimizes work and – critically – offers a new method to abdicate responsibility. In his 1941 book, Escape from Freedom, the German psychoanalyst Erich Fromm proposed that the rise of fascism could be understood by a human tendency to surrender autonomy in for the sake of the comforting security of subordination. AI offers a digital method of relinquishing the weight of having to think and choose.

The Black Box Problem: Trust Without Understanding

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

The fundamental problem is that AI operates as a black box. It produces answers, but not always fostering human understanding. We cannot fully grasp how AI reaches its decisions – even its programmers admit this. Nor can we verify its reasoning against clear, objective criteria. So when we follow AI's recommendation, we are not being guided by reason. We are returning to the domain of faith. In dubio pro machina: when in doubt, trust the machine – that may become our future credo.

Using Without Losing: The Critical Balance

AI can be a powerful tool for mankind in scientific pursuit. It can help inventing drugs, free us from tedious tasks, or manage administrative chores – duties that are repetitive and are unfulfilling. All to the good. But Kant and his contemporaries did not champion enlightenment just so humans could optimize chores or have extra free time. Independent thought was not just about efficiency – it was a practice of liberty and human emancipation.

Human thought is often chaotic and error-prone, but it forces us to debate, to doubt, to test ideas – and to acknowledge the limits of our own understanding. It fosters confidence, both individually and collectively. For Kant, the use of reason was never solely about acquiring knowledge; it was about empowering people to become authors of their own destinies, and to oppose control. It was about creating a ethical society based on the shared principle of reason and debate, rather than blind belief.

With all the undeniable benefits AI brings, the paramount challenge remains: how can we leverage its potential of advanced capability without undermining human reasoning, the cornerstone of the Enlightenment and of liberal democracy themselves? That is likely one of the central dilemmas of our time. It is a question we must strive not to outsource to the algorithm.