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This recent season, I found myself navigating in congested traffic on the scorching streets of Marseille. At a crossing, my companion in the passenger seat suggested a right turn toward a renowned spot for fish soup. However, the navigation app on my phone instructed us to go forward. Fatigued and in a stifling car, I heeded the algorithm's advice. Minutes later, we were stranded at a construction site.

A seemingly trivial incident, maybe. But one that captures a defining question of our era, where digital tools touches almost every aspect of existence: whom do we trust to a greater degree – other people and our personal instincts, or the machine?

The Enlightenment's Promise and Our Modern Relapse

The renowned German philosopher Immanuel Kant once defined the Enlightenment as "man's release from its self-imposed immaturity." This state, he argued, "is the incapacity to use one's own understanding without direction from an external source." For ages, that guiding "other" for society was frequently the clergyman, the monarch, or the landowner – entities claiming to speak for divine will. To comprehend natural events like volcanic eruptions, people sought answers in theology. In shaping the social world, from economics to love, religious doctrine acted as the main compass.

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

Kant argued that humans had the ability to think rationally. They simply lacked the confidence to employ it. With revolutions in America and France, a fresh era emerged: logic would supplant blind faith, and the intellect, liberated from dogma, would become the engine of progress and a more ethical world.

Now, 250 years later, one might wonder if we are quietly regressing into a state of intellectual immaturity. An app suggesting a driving route is merely the start. Artificial intelligence threatens to become our new "other" – a unseen overseer that steers our decisions and actions. We are in danger of relinquishing the historically earned courage to think independently – and this time, not to deities or rulers, but to lines of code.

The Rapid Rise and Subtle Dangers of Algorithmic Reliance

ChatGPT was launched a mere three years ago, and already a recent study found that an overwhelming majority of respondents had used AI in the preceding half-year. Whether deciding on ending a relationship or choosing a candidate, individuals are increasingly turning to algorithms for guidance. Research suggests a large majority of user prompts concern non-work topics. Even more intriguing than our use of AI for judgment is what happens when we allow it express for us. Writing is now one of the most common uses for tools like ChatGPT, just behind practical requests. The late American author Joan Didion famously said, “I write purely to find out what I am thinking.” What occurs when we cease writing? Do we lose that path?

Worryingly, emerging research suggests the answer may be yes. A study from the Massachusetts Institute of Technology used electroencephalography to observe the mental engagement of essay writers who had could use AI, Google, or no aids. Those who could use AI displayed the least brain activity and had difficulty accurately recalling their own work. Maybe most troubling was that after a few months, individuals in the AI group grew increasingly reliant, pasting entire blocks of text.

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

Certainly, AI's appeal stems from its convenience. It is fast, minimizes work and – importantly – offers a novel way to abdicate responsibility. In his 1941 book, Escape from Freedom, the German psychoanalyst Erich Fromm proposed that the appeal of authoritarianism could be partly explained by a human tendency to surrender autonomy in exchange for the reassuring certainty of subordination. AI presents a digital method of relinquishing the burden of having to think and choose.

The Black Box Problem: Trust Without Understanding

AI's greatest allure is its ability to accomplish things outside our minds – sifting through oceans of data at lightning pace. Sitting in the car in Marseille, this was, ultimately, 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 app had superior insight – or so I believed.

The fundamental problem is that AI operates as a black box. It generates answers, but not always fostering human understanding. We cannot fully grasp how AI reaches its conclusions – even its programmers admit this. Nor can we check its logic against clear, objective criteria. So when we heed AI's recommendation, we are not being led by logic. We are back in the domain of belief. In dubio pro machina: when in doubt, side with the machine – that may become our future 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 manage administrative chores – duties that are repetitive and offer little satisfaction. All to the good. But Kant and his contemporaries did not champion enlightenment just so humans could assemble better furniture or have extra free time. Critical thinking was not just about productivity – it was a practice of liberty and human emancipation.

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 builds confidence, both personally and collectively. For Kant, the use of reason was never solely about information; it was about enabling people to become authors of their own destinies, and to resist control. It was about building a moral community grounded in the common foundation of reason and debate, rather than blind belief.

With all the advantages AI offers, the key question is this: how can we harness its potential of advanced capability without undermining human reasoning, the cornerstone of the Enlightenment and of liberal democracy itself? That is likely one of the central dilemmas of our time. It is a question we must strive not to outsource to the algorithm.