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This recent season, I found myself navigating in gridlocked traffic on the scorching streets of Marseille. 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 continue straight. Fatigued and overheated, I heeded the app's advice. Moments later, we were stranded at a roadwork site.

A minor event, maybe. But one that captures a central dilemma of our era, where technology permeates nearly every facet of existence: whom do we trust more – fellow humans and our personal instincts, or the machine?

A Call for Intellectual Maturity and A Contemporary Backslide

The influential German philosopher Immanuel Kant famously described the Enlightenment as "humanity's emergence from its self-imposed nonage." This immaturity, he argued, "represents the inability to use one's personal reason without guidance from an external source." For centuries, that directing force for society was frequently the priest, the monarch, or the feudal lord – entities purporting to speak for divine will. To explain natural events like changing seasons, people sought answers in religion. In organizing the fabric of society, from economics to love, faith served as the primary guide.

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

Kant maintained that humans always possessed the ability to think rationally. They just didn't have the boldness to use it. With revolutions in America and France, a new dawn emerged: reason would supplant blind faith, and the intellect, liberated from authority, would become the driver of advancement and a more ethical world.

Now, two and a half centuries later, one might question if we are quietly regressing into a form of dependency. An app suggesting a direction is just one example. Artificial intelligence risks becoming our new "other" – a unseen guide that influences our choices and behaviors. We are in danger of ceding the hard-won autonomy to think independently – and this time, not to deities or rulers, but to computer programs.

The Rapid Rise and Hidden Risks of Algorithmic Reliance

ChatGPT was launched a mere three years ago, and yet a global survey found that an vast number of people had engaged with artificial intelligence in the previous six months. Whether deciding on a breakup or choosing a candidate, individuals are increasingly turning to machines for counsel. Research suggests a significant portion of user prompts relate to non-work topics. Even more striking than our use of AI for advice is what happens when we allow it speak for us. Writing is now one of the top uses for generative AI, second only to everyday tasks. The celebrated American author Joan Didion once remarked, “I write entirely to find out what I am thinking.” What transpires when we cease writing? Do we lose that path?

Alarmingly, some evidence suggests the outcome may be yes. A study conducted by the Massachusetts Institute of Technology used brain monitoring to track the cognitive activity of essay writers who had access to AI, traditional search engines, or nothing. Those who could rely on AI displayed the lowest brain activity and had difficulty quoting their own work. Maybe most concerning was that after a few months, participants in the AI group grew increasingly reliant, pasting entire blocks of text.

“Laziness and cowardice,” Kant wrote, “are the reasons why so many of men … stay in perpetual nonage.”

Certainly, AI's appeal lies in its convenience. It is fast, reduces effort and – importantly – offers a novel way to abdicate accountability. In his 1941 book, Escape from Freedom, the German psychoanalyst Erich Fromm proposed that the appeal of authoritarianism could be understood by a preference to surrender personal freedom in for the sake of the reassuring certainty of obedience. AI offers a modern method of surrendering the burden of having to decide for oneself.

The Opacity Dilemma: Trust Without Understanding

AI's primary draw is its capacity to accomplish things outside our minds – sifting through vast datasets at unprecedented speed. Sitting in the car in Marseille, this was, ultimately, why I chose to trust the app over my friend (a decision she interpreted as an insult). With knowledge of real-time information, certainly the algorithm had superior insight – or so I thought.

The core issue is that AI operates as a opaque system. It generates answers, but without necessarily deepening human understanding. We do not truly know the process behind its decisions – even its programmers admit this. Nor can we verify its reasoning against clear, objective criteria. So when we follow AI's advice, we are not being guided by reason. We are returning to the domain of faith. In dubio pro machina: when in doubt, side with the machine – that may become our future guiding principle.

Using Without Losing: The Essential Challenge

AI can be a formidable ally for humanity in rational inquiry. It can aid in inventing drugs, free us from "bullshit jobs", or handle taxes – duties that are repetitive and offer little satisfaction. All to the good. But Kant and his contemporaries did not champion reason over faith just so humans could assemble better furniture or have extra free time. Independent thought was not just about productivity – it was a practice of liberty and human self-determination.

Human thought is inherently messy and error-prone, but it compels us to argue, to doubt, to test ideas – and to acknowledge the boundaries of our own knowledge. It builds confidence, both individually and collectively. For Kant, the exercise of reason was never solely about information; it was about enabling people to become authors of their own destinies, and to oppose domination. It was about building a moral community based on the shared principle of rational discourse, rather than unquestioning acceptance.

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