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This recent season, I was caught in gridlocked traffic on the sweltering streets of a southern French city. At a crossing, my companion in the passenger seat advised a right turn toward a famous spot for fish soup. Yet, the navigation app on my phone instructed us to go forward. Fatigued and overheated, I heeded the algorithm's directive. Moments later, we were stranded at a roadwork site.

A minor event, perhaps. But one that captures a defining question of our time, where technology touches nearly every facet of our lives: whom do we trust more – fellow humans and our personal instincts, or the algorithm?

The Enlightenment's Promise and A Contemporary Backslide

The renowned German philosopher Immanuel Kant once defined the Enlightenment as "humanity's emergence from its self-imposed immaturity." This immaturity, he wrote, "represents the incapacity to use one's own understanding without direction from an external source." For ages, that directing force for society was often the priest, the monarch, or the feudal lord – figures purporting to speak for divine will. To explain phenomena like changing seasons, people looked for explanations in religion. In organizing the social world, from economics to love, faith acted as the primary guide.

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

Kant maintained that humans always possessed the capacity for reason. They simply lacked the confidence to use it. With upheavals in America and France, a fresh era emerged: logic would supplant superstition, and the human mind, freed from authority, would become the driver of advancement and a more ethical world.

Today, 250 years later, one might wonder if we are quietly regressing into a state of dependency. An app suggesting a direction is merely the start. Artificial intelligence risks becoming our new "other" – a unseen guide that influences our decisions and actions. We risk relinquishing the hard-won autonomy to think independently – and this time, not to deities or rulers, but to computer programs.

The Rapid Rise and Subtle Dangers of AI Dependence

ChatGPT was launched only in 2022, and yet a global survey indicated that an overwhelming majority of people had engaged with artificial intelligence in the previous six months. Whether deciding on ending a relationship or selecting a vote, individuals are looking to algorithms for counsel. Research suggests a significant portion of user prompts relate to personal life matters. Even more intriguing than our use of AI for judgment is what happens when we allow it express for us. Composition is now among the most common uses for generative AI, second only to everyday tasks. The celebrated American author Joan Didion famously said, “I write entirely to discover what I am thinking.” What transpires when we stop composing? Do we cease discovering?

Worryingly, emerging research suggests 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 access to AI, traditional search engines, or nothing. Those who could rely on AI showed the lowest cognitive engagement and had trouble quoting their own work. Perhaps most troubling was that over time, individuals in the AI group became increasingly reliant, copying 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 efficiency. It is fast, reduces effort and – importantly – offers a novel way to offload accountability. In his 1941 book, Escape from Freedom, the German psychoanalyst Erich Fromm proposed that the rise of fascism could be understood by a human tendency to give up personal freedom in exchange for the comforting security of obedience. AI presents a digital avenue for relinquishing the weight of having to think and choose.

The Opacity Dilemma: Trust Without Understanding

AI's primary draw is its ability to perform tasks beyond human capability – analyzing vast datasets at lightning pace. Sitting in the car in Marseille, this was, ultimately, why I chose to trust the machine over my friend (a decision she interpreted as an affront). With access to real-time information, surely the algorithm must know best – or so I believed.

The fundamental problem is that AI operates as a opaque system. It generates answers, but not always deepening human understanding. We do not truly know the process behind its decisions – even its creators acknowledge the opacity. Nor can we check its reasoning against transparent standards. So when we follow AI's advice, we are not being led by logic. We are back in the domain of belief. In dubio pro machina: when in doubt, trust the machine – that may become our future guiding principle.

Using Without Losing: The Critical Balance

AI can be a formidable ally for mankind in scientific pursuit. It can help inventing drugs, liberate us from "bullshit jobs", or manage taxes – work that demand little thought and offer little satisfaction. All to the good. But Kant and his contemporaries did not advocate for enlightenment just so humans could optimize chores or have extra free time. Independent thought was not merely about productivity – it was a discipline of freedom and human emancipation.

Human thought is inherently messy and fallible, but it compels us to debate, to doubt, to challenge concepts – and to acknowledge the limits of our own knowledge. It fosters confidence, both individually and as a society. For Kant, the use of reason was never only about information; it was about empowering people to become agents of their own lives, and to oppose control. It was about creating a moral community based on the common foundation of reason and debate, rather than unquestioning acceptance.

With all the undeniable benefits AI offers, the key question is this: how can we harness its promise of superhuman intelligence without undermining human rationality, the bedrock of the Enlightenment and of liberal democracy themselves? That may be one of the defining questions of our time. It is a question we would do well not to outsource to the machine.