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This past summer, I was caught in congested traffic on the sweltering streets of Marseille. At a crossing, my friend in the passenger seat suggested a right turn toward a famous spot for bouillabaisse. Yet, the digital guide on my phone commanded us to go forward. Weary and in a stifling car, I heeded the app's advice. Moments later, we were stuck at a roadwork site.

A seemingly trivial event, maybe. But one that captures a central dilemma of our era, where digital tools permeates almost every aspect of our lives: whom do we trust to a greater degree – other people and our own intuition, or the algorithm?

The Enlightenment's Promise and A Contemporary Backslide

The renowned German philosopher Immanuel Kant famously described the Enlightenment as "man's release from its self-inflicted immaturity." This immaturity, he wrote, "is the inability to use one's own understanding without guidance from an external source." For ages, that directing force for human thought was often the priest, the monarch, or the landowner – figures purporting to speak for divine will. To comprehend natural events like volcanic eruptions, people looked for explanations in theology. In shaping the social world, from economics to love, religious doctrine acted as the primary guide.

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

Kant maintained that humans had the capacity for reason. They simply lacked the boldness to use it. With upheavals in America and France, a new dawn emerged: logic would supplant superstition, and the human mind, liberated from authority, would become the driver of advancement and a better world.

Now, 250 years 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 threatens to become our contemporary authority – a silent guide that influences our choices and behaviors. We are in danger of ceding the historically earned courage to think independently – and this time, not to gods or kings, but to computer programs.

The Swift Adoption 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 choosing a candidate, individuals are increasingly turning to algorithms for counsel. Data suggests a large majority of user queries relate to personal life matters. Even more striking than our reliance on AI for judgment is what occurs when we let it express for us. Composition is now among the most common 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 transpires when we stop composing? Do we cease discovering?

Alarmingly, emerging research suggests the answer may be yes. A study conducted by the Massachusetts Institute of Technology used electroencephalography to track the cognitive activity of essay writers who had access to AI, Google, or nothing. Those who could rely on AI showed the least brain activity and had difficulty quoting their own work. Maybe most troubling was that over time, individuals in the AI group became progressively lazier, copying entire blocks of text.

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

Certainly, AI's appeal lies in its convenience. It saves time, minimizes work and – importantly – offers a novel way to offload accountability. In his 1941 book, Escape from Freedom, the German psychoanalyst Erich Fromm argued that the rise of fascism could be partly explained by a preference to give up autonomy in exchange for the comforting security of obedience. AI offers a modern method of surrendering the burden of having to think and choose.

The Opacity Dilemma: Trust Without Understanding

AI's primary draw is its capacity to perform tasks outside human capability – sifting through oceans of data at unprecedented speed. Stuck in the car in Marseille, this was, after all, why I opted to trust the machine over my friend (a choice she took as an insult). With access to real-time information, surely the algorithm must know best – or so I believed.

The core issue is that AI is a opaque system. It produces knowledge, but not always deepening human understanding. We cannot fully grasp how AI reaches its decisions – even its programmers acknowledge the opacity. Nor can we verify its reasoning against transparent standards. So when we follow AI's recommendation, we are not being led by logic. We are back in the domain of faith. In dubio pro machina: when in doubt, side with the machine – that may become our future credo.

Using Without Losing: The Essential Challenge

AI can be a formidable ally for mankind in rational inquiry. It can help medical research, liberate us from tedious tasks, or handle administrative chores – 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 optimize chores or have extra free time. Critical thinking was not merely about productivity – it was a practice of liberty and human emancipation.

Human thought is inherently messy and error-prone, but it forces us to argue, to question, to challenge concepts – and to acknowledge the limits of our own knowledge. It builds confidence, both personally and as a society. For Kant, the exercise of reason was never only about acquiring knowledge; it was about enabling people to become authors of their own lives, and to resist control. It was about building a moral community grounded in the common foundation of reason and debate, rather than unquestioning acceptance.

With all the advantages AI brings, the key question remains: how can we harness its promise of advanced capability without undermining human rationality, the bedrock of the Enlightenment and of liberal democracy themselves? That may be one of the central dilemmas of our time. It is a question we would do well not to outsource to the algorithm.