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This past summer, I was caught in gridlocked traffic on the sweltering streets of Marseille. At a crossing, my companion in the front seat advised a right turn toward a famous spot for bouillabaisse. Yet, the digital guide on my phone commanded us to go forward. Fatigued and overheated, I heeded the algorithm's advice. Moments later, we were stuck at a roadwork site.

A minor event, perhaps. But one that captures a central dilemma of our era, where technology permeates nearly every facet of our lives: who gets our trust to a greater degree – other people and our personal instincts, 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-imposed nonage." This state, he argued, "represents the inability to use one's personal reason without direction from an external source." For centuries, that directing force for society was frequently the clergyman, the king, or the landowner – entities purporting to speak for divine will. To explain phenomena like volcanic eruptions, people looked for explanations in religion. In shaping the social world, from commerce to matters of the heart, religious doctrine served as the main compass.

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

Kant argued that humans always possessed the capacity for reason. They simply lacked the confidence to employ it. With upheavals in the 18th century, a new dawn emerged: reason would supplant superstition, and the intellect, freed from authority, would become the driver of progress and a more ethical world.

Now, 250 years later, one might question if we are quietly regressing into a form of intellectual immaturity. An app dictating a direction is merely the start. Artificial intelligence threatens to become our new "other" – a silent guide that influences our choices and behaviors. We risk ceding the hard-won courage to think independently – and this time, not to gods or kings, but to lines of code.

The Swift Adoption and Hidden Risks of Algorithmic Reliance

ChatGPT was launched only in 2022, and already a global survey found that an overwhelming majority of respondents had used AI in the preceding half-year. Whether deciding on ending a relationship or choosing a candidate, individuals are looking to machines for counsel. Research suggests a large majority of user prompts relate to personal life matters. Even more intriguing than our use of AI for advice is what occurs when we allow it speak for us. Writing is now one of the most common uses for generative AI, second only to everyday tasks. The celebrated American author Joan Didion once remarked, “I write purely to discover what I am thinking.” What transpires when we cease writing? Do we cease discovering?

Worryingly, some evidence suggests the answer may be affirmative. A study from the Massachusetts Institute of Technology used electroencephalography to track the cognitive activity of participants who had access to AI, traditional search engines, or no aids. Those who could use AI displayed the lowest brain activity and had difficulty quoting their own work. Perhaps most concerning was that after a few months, individuals in the AI group grew increasingly reliant, pasting large sections of text.

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

Of course, AI's attraction lies in its convenience. It is fast, reduces effort and – importantly – offers a novel way to offload responsibility. In his 1941 book, Escape from Freedom, the German psychoanalyst Erich Fromm argued that the appeal of authoritarianism could be understood by a preference to give up personal freedom in for the sake of the reassuring certainty of subordination. AI presents a modern method of relinquishing the burden of having to decide for oneself.

The Opacity Dilemma: Trust Without Understanding

AI's greatest allure is its ability to accomplish things outside human capability – analyzing oceans of data at unprecedented speed. Stuck in the car in Marseille, this was, ultimately, why I opted to trust the machine over my companion (a decision she interpreted as an insult). With knowledge of real-time information, surely the app had superior insight – or so I thought.

The fundamental problem is that AI operates as a opaque system. It generates knowledge, but without necessarily deepening human understanding. We do not truly know how AI reaches its decisions – including its creators admit this. Nor can we check its reasoning against transparent standards. So when we heed AI's advice, we are not being led by logic. We are back in the realm of faith. In dubio pro machina: when in doubt, side with the machine – that could be our future credo.

Using Without Losing: The Critical Balance

AI can be a formidable ally for humanity in scientific pursuit. It can help medical research, liberate us from tedious tasks, or handle taxes – duties that demand little thought and offer little satisfaction. This is beneficial. But Kant and his contemporaries did not champion reason over faith just so humans could optimize chores or have more leisure. Independent thought was not just about productivity – it was a practice of liberty and human self-determination.

Human thought is often chaotic and error-prone, but it forces us to argue, to question, to test ideas – and to acknowledge the boundaries of our own understanding. It fosters self-reliance, both individually and as a society. For Kant, the use of reason was never solely about acquiring knowledge; it was about enabling people to become authors of their own destinies, and to resist control. It was about building a ethical society grounded in the shared principle of rational discourse, rather than blind belief.

With all the advantages AI brings, the key question remains: how can we harness its potential of advanced capability without eroding human reasoning, the cornerstone of the Enlightenment and of liberal democracy itself? That is likely one of the defining questions of our century. It is a question we would do well not to delegate to the algorithm.