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This past summer, I was caught in gridlocked traffic on the scorching streets of Marseille. At a crossing, my companion in the front seat advised a right turn toward a renowned spot for bouillabaisse. However, the navigation app on my phone commanded us to go forward. Weary and overheated, I followed the app's advice. Minutes later, we were stranded at a construction site.

A seemingly trivial incident, perhaps. But one that captures a defining question of our era, where digital tools permeates almost every aspect of our lives: who gets our trust more – other people and our personal instincts, or the machine?

The Enlightenment's Promise and Our Modern Relapse

The influential German philosopher Immanuel Kant once defined the Enlightenment as "humanity's emergence from its self-inflicted immaturity." This immaturity, he wrote, "represents the incapacity to use one's own understanding without direction from another." For ages, that guiding "other" for society was often the priest, the monarch, or the landowner – entities claiming to channel divine will. To explain phenomena like changing seasons, people looked for explanations in religion. In shaping the social world, from economics to matters of the heart, faith served as the main compass.

“Sapere aude!” or “Have courage to use your reason!”

Kant argued that humans always possessed the capacity for reason. They just didn't have the confidence to employ it. With upheavals in America and France, a fresh era arrived: reason would replace superstition, and the intellect, liberated from dogma, would become the engine of advancement and a more ethical world.

Now, two and a half centuries later, one might question if we are slipping back into a form of dependency. An app suggesting a driving route is just one example. Artificial intelligence threatens to become our new "other" – a silent guide that steers our choices and actions. We are in danger of relinquishing the historically earned courage to think independently – and this time, not to gods or kings, but to lines of code.

The Rapid Rise and Subtle Dangers of Algorithmic Reliance

ChatGPT was launched only in 2022, and already a global survey indicated that an overwhelming majority of people had engaged with artificial intelligence in the previous six months. Whether contemplating ending a relationship or selecting a vote, individuals are looking to algorithms for counsel. Data suggests a large majority of user prompts relate to non-work topics. Even more striking 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, just behind everyday tasks. The late American author Joan Didion famously said, “I write purely to discover what I am thinking.” What occurs when we stop composing? Do we cease discovering?

Worryingly, emerging research hints the outcome may be yes. A study from the Massachusetts Institute of Technology used electroencephalography to observe the cognitive activity of participants who had access to AI, traditional search engines, or no aids. Those who could rely on AI displayed the least cognitive engagement and had trouble quoting their own work. Perhaps most concerning was that over time, participants in the AI group became increasingly reliant, copying entire blocks of text.

“Laziness and cowardice,” Kant wrote, “are the reasons why so great a proportion of men … remain in lifelong immaturity.”

Of course, AI's appeal stems from its efficiency. 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 argued that the rise of fascism could be understood by a human tendency to surrender autonomy in exchange for the comforting security of obedience. AI offers a digital method of surrendering the burden of having to decide for oneself.

The Opacity Dilemma: Faith Over Reason

AI's greatest allure is its capacity to perform tasks beyond our minds – analyzing vast datasets at lightning pace. Stuck in the car in Marseille, this was, after all, why I chose to believe the machine over my friend (a choice she interpreted as an insult). With access to real-time information, certainly the app must know best – or so I thought.

The fundamental problem is that AI operates as a opaque system. It generates knowledge, but not always deepening human comprehension. We cannot fully grasp how AI reaches its conclusions – even its programmers acknowledge the opacity. Nor can we check its logic against clear, objective criteria. So when we heed AI's advice, we are not being led by logic. We are back in the realm of faith. In dubio pro machina: when in doubt, trust the machine – that could be our 21st-century guiding principle.

Harnessing Without Eroding: The Essential Challenge

AI can be a formidable ally for humanity in scientific pursuit. It can help medical research, liberate us from "bullshit jobs", or handle taxes – duties that are repetitive and are unfulfilling. All to the good. But Kant and his peers did not champion reason over faith just so humans could assemble better furniture or have extra free time. Independent thought was not merely about efficiency – it was a discipline of liberty and human emancipation.

Human thought is inherently messy and fallible, but it compels us to debate, to question, to test ideas – and to recognize the boundaries of our own understanding. It fosters self-reliance, both personally and as a society. For Kant, the exercise of reason was never only about information; it was about empowering people to become authors of their own lives, and to resist domination. It was about building a ethical society based on the shared principle of rational discourse, rather than unquestioning acceptance.

With all the advantages AI offers, the key question remains: how can we leverage its potential of advanced capability without undermining human rationality, the cornerstone of the Enlightenment and of liberal democracy themselves? That may be one of the defining questions of our time. It is a question we must strive not to outsource to the machine.