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This past summer, I was caught in gridlocked traffic on the sweltering streets of a southern French city. At an intersection, my companion in the front seat advised a right turn toward a renowned spot for fish soup. Yet, the navigation app on my phone commanded us to go forward. Weary and in a stifling car, I heeded the algorithm's directive. Moments later, we were stranded at a roadwork site.

A seemingly trivial incident, maybe. But one that encapsulates a defining dilemma of our era, where digital tools permeates almost every aspect of existence: who gets our trust to a greater degree – 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 nonage." This immaturity, he argued, "represents the inability to use one's personal reason without guidance from an external source." For ages, that guiding "other" for society was frequently the priest, the king, or the feudal lord – figures purporting to speak for divine will. To comprehend natural events like volcanic eruptions, people sought answers in theology. In shaping the fabric of society, from commerce to love, religious doctrine served as the main compass.

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

Kant argued that humans had the capacity for reason. They just didn't have the boldness to employ it. With upheavals in the 18th century, a fresh era arrived: logic would supplant blind faith, and the human mind, liberated from authority, would become the driver of progress and a more ethical world.

Now, two and a half centuries later, one might wonder if we are quietly regressing into a state of intellectual immaturity. An app dictating a direction is merely the start. Artificial intelligence risks becoming our contemporary authority – a unseen overseer that influences our decisions and actions. We risk ceding the hard-won courage to reason for ourselves – and now, not to gods or kings, but to computer programs.

The Rapid Rise and Hidden Risks of Algorithmic Reliance

ChatGPT was launched only in 2022, and yet a recent study indicated that an overwhelming majority of respondents had used AI in the previous six months. Whether contemplating a breakup or selecting a vote, individuals are increasingly turning to machines for guidance. Data suggests a large majority of user prompts concern non-work topics. Even more intriguing than our use of AI for advice is what happens when we allow it express for us. Composition is now one of the top uses for generative AI, just behind practical requests. The celebrated American author Joan Didion once remarked, “I write entirely to discover what I am thinking.” What occurs when we stop composing? Do we lose that path?

Worryingly, emerging research hints the outcome may be affirmative. A study from the Massachusetts Institute of Technology used brain monitoring to observe the cognitive activity of participants who had could use AI, Google, or no aids. Those who could use AI showed the lowest cognitive engagement and had trouble quoting their own work. Perhaps most troubling was that over time, individuals in the AI group grew increasingly reliant, copying 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 convenience. It saves time, reduces effort and – importantly – offers a new method to offload responsibility. In his 1941 book, Escape from Freedom, the German psychoanalyst Erich Fromm argued that the rise of fascism 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 surrendering the weight of having to think and choose.

The Opacity Dilemma: Trust Without Understanding

AI's greatest allure is its ability to accomplish things beyond human capability – analyzing 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 insult). With knowledge of real-time information, surely the algorithm must know best – or so I believed.

The fundamental problem is that AI is a black box. It produces knowledge, but without necessarily fostering human comprehension. We do not truly know how AI reaches its decisions – even its creators acknowledge the opacity. Nor can we verify its logic against clear, objective criteria. So when we follow AI's advice, we are not being led by logic. We are returning to the domain of faith. In dubio pro machina: when in doubt, trust the machine – that may become our 21st-century guiding principle.

Harnessing Without Eroding: The Essential Challenge

AI can be a formidable ally for mankind in rational inquiry. It can help medical research, liberate us from "bullshit jobs", or handle administrative chores – duties that demand little thought and offer little satisfaction. All to the good. But Kant and his peers did not champion enlightenment just so humans could optimize chores or have more leisure. Critical thinking was not just about productivity – it was a discipline of liberty and human self-determination.

Human thought is inherently messy and error-prone, but it compels us to debate, to doubt, to test ideas – and to acknowledge the limits of our own understanding. It fosters confidence, both individually and as a society. For Kant, the use of reason was never only about information; it was about empowering people to become authors of their own lives, and to resist control. It was about building a ethical society grounded in the common foundation of rational discourse, rather than blind belief.

With all the advantages AI brings, the paramount challenge remains: how can we harness its potential of superhuman intelligence without eroding human rationality, the cornerstone of the Enlightenment and of liberal democracy itself? That may be one of the central dilemmas of our time. It is a question we would do well not to outsource to the machine.