Our King, Our Priest, Our Feudal Lord – How AI Is Taking Us Back to the Dark Ages.

This past summer, I was caught in gridlocked traffic on the scorching streets of a southern French city. At an intersection, my friend in the front seat suggested a right turn toward a renowned spot for fish soup. Yet, the navigation app on my phone instructed us to continue straight. Weary and in a stifling car, I heeded the app's directive. Minutes later, we were stranded at a construction site.

A minor incident, maybe. But one that captures a central dilemma of our time, where technology permeates nearly every facet of existence: whom do we 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-inflicted nonage." This immaturity, he wrote, "is the inability to use one's own understanding without guidance from another." For centuries, that guiding "other" for society was frequently the priest, the king, or the landowner – figures claiming to channel God's voice. To comprehend natural events like volcanic eruptions, people sought answers in religion. In organizing the social world, from economics to love, faith served as the main compass.

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

Kant maintained that humans always possessed the capacity for reason. They just didn't have the confidence to employ it. With upheavals in the 18th century, a new dawn arrived: logic would replace blind faith, and the human mind, freed from dogma, would become the engine of progress and a better world.

Now, two and a half centuries later, one might wonder if we are quietly regressing into a form of dependency. An app suggesting a driving route is merely the start. AI threatens to become our contemporary authority – a silent guide that influences our decisions and actions. We are in danger of ceding the historically earned courage to think independently – and this time, not to gods or kings, but to lines of code.

The Swift Adoption and Subtle Dangers of Algorithmic Reliance

ChatGPT was launched a mere three years ago, and yet a recent study found that an overwhelming majority of respondents had used AI in the preceding half-year. Whether deciding on a breakup or choosing a candidate, individuals are looking to machines for counsel. Research suggests a significant portion of user prompts relate to personal life matters. Even more striking than our reliance on AI for judgment is what happens when we allow it express for us. Composition is now among the top uses for generative AI, just behind everyday tasks. The late American author Joan Didion once remarked, “I write purely to find out what I am thinking.” What occurs when we stop composing? Do we lose that path?

Worryingly, some evidence hints the outcome may be affirmative. A study from the Massachusetts Institute of Technology used electroencephalography to track the mental engagement of participants who had access to AI, traditional search engines, or no aids. Those who could rely on AI displayed the least cognitive engagement and had difficulty quoting their own work. Perhaps most troubling was that after a few months, participants in the AI group grew progressively lazier, pasting entire blocks of text.

“Inertia and fear,” Kant wrote, “are the reasons why so great a proportion of men … stay in perpetual nonage.”

Of course, AI's attraction stems from its convenience. It is fast, minimizes work and – importantly – offers a new method to abdicate responsibility. In his 1941 book, Escape from Freedom, the German psychoanalyst Erich Fromm argued that the appeal of authoritarianism could be partly explained by a human tendency to give up personal freedom in exchange for the comforting security of subordination. AI offers a modern avenue for relinquishing the weight of having to decide for oneself.

The Opacity Dilemma: Faith Over Reason

AI's greatest allure is its ability to accomplish things outside human capability – sifting through vast datasets at lightning pace. Sitting 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 not always deepening human comprehension. We do not truly know the process behind its conclusions – including its programmers admit this. Nor can we verify its reasoning against transparent standards. So when we heed AI's advice, we are not being guided by reason. We are back in the domain of belief. In dubio pro machina: when in doubt, trust the machine – that may become our future credo.

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 handle taxes – duties that demand little thought and offer little satisfaction. This is beneficial. But Kant and his peers did not champion reason over faith just so humans could assemble better furniture or have more leisure. Critical thinking was not just about efficiency – it was a practice of freedom and human emancipation.

Human thought is inherently messy and error-prone, but it forces us to argue, to question, to test ideas – and to acknowledge the limits of our own understanding. It builds confidence, both individually and as a society. For Kant, the exercise of reason was never solely about information; it was about enabling people to become agents of their own destinies, and to oppose control. It was about creating a ethical society based on the shared principle of rational discourse, rather than blind belief.

With all the advantages AI offers, the paramount challenge remains: how can we harness its potential of advanced capability without undermining human rationality, the cornerstone of the Enlightenment and of free societies itself? 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.