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This past summer, I found myself navigating in congested traffic on the sweltering streets of Marseille. At a crossing, my friend in the passenger seat advised a right turn toward a renowned spot for fish soup. Yet, the digital guide on my phone instructed us to continue straight. Fatigued and in a stifling car, I followed the app's advice. Minutes later, we were stranded at a roadwork site.

A minor event, maybe. But one that captures a defining question of our time, where technology permeates almost every aspect of existence: who gets our trust more – other people and our personal instincts, 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 argued, "represents the incapacity to use one's personal reason without direction from another." For ages, that guiding "other" for human thought was often the clergyman, the monarch, or the feudal lord – entities claiming to speak for God's voice. To explain natural events like changing seasons, people looked for explanations in religion. In organizing the fabric of society, from commerce to matters of the heart, faith served as the primary guide.

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

Kant maintained that humans had the ability to think rationally. They simply lacked the confidence to employ it. With revolutions in America and France, a new dawn arrived: logic would replace blind faith, and the intellect, freed from dogma, would become the engine of progress and a more ethical world.

Today, two and a half centuries later, one might wonder if we are slipping back into a state of dependency. An app dictating a direction is merely the start. AI threatens to become our new "other" – a unseen overseer that steers our decisions and actions. We risk relinquishing the historically earned autonomy to think independently – and now, not to gods or kings, but to lines of code.

The Swift Adoption and Hidden Risks of AI Dependence

ChatGPT was launched only in 2022, and already a recent study indicated that an vast number of people had engaged with artificial intelligence in the previous six months. Whether contemplating a breakup or selecting a vote, individuals are looking to algorithms for guidance. Research suggests a large majority of user prompts relate to personal life matters. Even more striking than our reliance on AI for judgment is what happens when we allow it speak for us. Composition is now one of the top uses for tools like ChatGPT, just behind everyday tasks. The late American author Joan Didion once remarked, “I write entirely to find out what I am thinking.” What transpires when we cease writing? Do we cease discovering?

Alarmingly, some evidence hints the answer may be yes. A study from the Massachusetts Institute of Technology used brain monitoring to track the mental engagement of participants who had could use AI, traditional search engines, or nothing. Those who could use AI displayed the lowest cognitive engagement and had difficulty quoting their own work. Perhaps most concerning was that after a few months, participants in the AI group grew increasingly reliant, pasting 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 stems from its convenience. It is fast, reduces effort 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 preference to surrender personal freedom in exchange for the comforting security of subordination. AI offers a modern method of surrendering the weight of having to think and choose.

The Opacity Dilemma: Trust Without Understanding

AI's greatest allure is its capacity to perform tasks beyond our minds – sifting through oceans of data at lightning pace. Stuck in the car in Marseille, this was, after all, why I chose to trust the machine over my friend (a decision she took as an insult). With access to all the data, certainly the app had superior insight – or so I thought.

The fundamental problem is that AI is a opaque system. It generates knowledge, but without necessarily fostering human comprehension. We cannot fully grasp the process behind its conclusions – including its creators acknowledge the opacity. Nor can we check its reasoning against transparent standards. So when we heed AI's recommendation, we are not being led by logic. We are returning to the domain of belief. In dubio pro machina: when in doubt, trust the machine – that could be our 21st-century credo.

Harnessing Without Eroding: The Critical Balance

AI can be a powerful tool for mankind in rational inquiry. It can help medical research, free us from "bullshit jobs", or handle administrative chores – work 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 optimize chores or have extra free time. Independent thought was not merely about productivity – it was a discipline of liberty and human self-determination.

Human thought is inherently messy and error-prone, but it forces us to debate, to question, to test ideas – and to acknowledge the limits of our own understanding. It builds confidence, both individually and collectively. 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 oppose domination. It was about creating a moral community based on the shared principle of rational discourse, rather than unquestioning acceptance.

With all the advantages AI brings, the paramount challenge remains: how can we leverage its potential of superhuman intelligence without undermining human rationality, the cornerstone of the Enlightenment and of liberal democracy themselves? That may be one of the central dilemmas of our time. It is a question we must strive not to delegate to the algorithm.