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This recent season, I was caught in congested traffic on the scorching streets of a southern French city. At an intersection, my companion in the front seat advised a right turn toward a renowned spot for fish soup. However, the digital guide on my phone instructed us to go forward. Fatigued and in a stifling car, I followed the app's advice. Minutes later, we were stranded at a roadwork site.

A minor incident, perhaps. But one that captures a defining question of our time, where digital tools touches nearly every facet of existence: whom do we trust to a greater degree – fellow humans and our own intuition, or the machine?

The Enlightenment's Promise and A Contemporary Backslide

The renowned German philosopher Immanuel Kant famously described the Enlightenment as "humanity's emergence from its self-inflicted immaturity." This immaturity, he wrote, "is the incapacity to use one's personal reason without guidance from another." For ages, that directing force for human thought was frequently the clergyman, the king, or the feudal lord – entities purporting to channel divine will. To comprehend natural events like changing seasons, people sought answers in religion. In organizing the fabric of society, from commerce to love, religious doctrine acted as the main compass.

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

Kant maintained that humans had the ability to think rationally. They just didn't have the confidence to employ it. With revolutions in the 18th century, a fresh era arrived: logic would supplant blind faith, and the intellect, liberated from authority, would become the engine of advancement and a better world.

Today, 250 years later, one might question if we are quietly regressing into a form of dependency. An app suggesting a direction is merely the start. Artificial intelligence threatens to become our contemporary authority – a unseen guide that influences our decisions and behaviors. We risk ceding the hard-won autonomy to think independently – and this time, not to deities or rulers, but to lines of code.

The Swift Adoption and Hidden Risks of AI Dependence

ChatGPT was launched a mere three years ago, and yet a global survey found that an overwhelming majority of respondents had used AI in the preceding half-year. Whether contemplating a breakup or choosing a candidate, individuals are looking to algorithms for guidance. Data suggests a large majority of user prompts concern non-work topics. Even more intriguing than our use of AI for judgment is what happens when we let it express for us. Composition is now one of the top uses for generative AI, just behind everyday tasks. The late American author Joan Didion famously said, “I write entirely to find out what I am thinking.” What transpires when we stop composing? Do we lose that path?

Alarmingly, emerging research suggests the outcome may be affirmative. A study from the Massachusetts Institute of Technology used brain monitoring 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 lowest brain activity and had trouble quoting their own work. Perhaps most troubling was that after a few months, participants in the AI group became increasingly reliant, pasting large sections of text.

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

Certainly, AI's appeal lies in its convenience. It saves time, reduces effort and – critically – offers a new method to offload responsibility. In his 1941 book, Escape from Freedom, the German psychoanalyst Erich Fromm proposed that the appeal of authoritarianism could be partly explained by a human tendency to surrender personal freedom in for the sake of the comforting security of subordination. AI presents a modern avenue for surrendering the burden of having to think and choose.

The Black Box Problem: Trust Without Understanding

AI's greatest allure is its capacity to perform tasks beyond our minds – sifting through vast datasets at lightning pace. Stuck in the car in Marseille, this was, ultimately, why I chose to trust the machine over my companion (a decision she took as an affront). With access to all the data, certainly the algorithm must know best – or so I believed.

The fundamental problem is that AI is a opaque system. It generates knowledge, but not always deepening human understanding. We cannot fully grasp the process behind its decisions – even its creators admit this. Nor can we verify its logic against transparent standards. So when we heed AI's recommendation, we are not being led by logic. We are back in the realm of belief. In dubio pro machina: when in doubt, trust the machine – that could be our future credo.

Using Without Losing: The Critical Balance

AI can be a powerful tool for humanity in scientific pursuit. It can help medical research, liberate us from "bullshit jobs", or manage taxes – work that demand little thought and offer little satisfaction. This is beneficial. But Kant and his peers did not advocate for reason over faith just so humans could assemble better furniture or have more leisure. Critical thinking was not merely about productivity – it was a discipline of freedom and human emancipation.

Human thought is often chaotic and error-prone, but it compels us to argue, to question, to test ideas – and to acknowledge the boundaries of our own understanding. It fosters self-reliance, both personally and collectively. For Kant, the use of reason was never solely about information; it was about empowering people to become authors of their own destinies, and to oppose 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 eroding human rationality, the bedrock of the Enlightenment and of liberal democracy themselves? That is likely one of the defining questions of our time. It is a question we would do well not to delegate to the algorithm.