Our King, Our Priest, Our Feudal Lord – The Way AI Returns Us to the Medieval Era.

This recent season, I found myself navigating in gridlocked traffic on the scorching streets of Marseille. At an intersection, my friend in the front seat advised a right turn toward a renowned spot for bouillabaisse. Yet, the navigation app on my phone commanded us to go forward. Weary and overheated, I heeded the app's advice. Moments later, we were stuck at a construction site.

A seemingly trivial incident, perhaps. But one that encapsulates a defining question of our era, where technology permeates almost every aspect of our lives: whom do we trust more – fellow humans and our own intuition, or the algorithm?

The Enlightenment's Promise and A Contemporary Backslide

The renowned German philosopher Immanuel Kant once defined the Enlightenment as "man's release from its self-imposed nonage." This state, he wrote, "is the inability to use one's own understanding without direction from an external source." For centuries, that directing force for human thought was frequently the priest, the king, or the landowner – figures purporting to channel divine will. To explain phenomena like volcanic eruptions, people sought answers in religion. In shaping the fabric of society, from economics to love, faith acted as the primary guide.

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

Kant maintained that humans had the ability to think rationally. They simply lacked the confidence to employ it. With revolutions in America and France, a new dawn emerged: logic would replace blind faith, and the human mind, liberated from authority, would become the driver of advancement and a better world.

Now, 250 years later, one might question if we are quietly regressing into a state of dependency. An app dictating a direction is merely the start. Artificial intelligence risks becoming our new "other" – a silent guide that influences our decisions and actions. We risk ceding the hard-won autonomy 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 only in 2022, and already a recent study indicated that an overwhelming majority of respondents had engaged with artificial intelligence in the previous six months. Whether contemplating ending a relationship or selecting a vote, individuals are increasingly turning to machines for counsel. Data suggests a large majority of user queries relate to non-work topics. Even more intriguing than our reliance on AI for advice is what occurs when we let it speak for us. Writing is now one of the top uses for generative AI, second only to everyday tasks. The celebrated American author Joan Didion once remarked, “I write entirely to discover what I am thinking.” What transpires when we cease writing? Do we lose that path?

Alarmingly, some evidence suggests the answer may be yes. A study from the Massachusetts Institute of Technology used brain monitoring to track the mental engagement of essay writers who had could use AI, traditional search engines, or no aids. Those who could rely on AI displayed the least cognitive engagement and had trouble accurately recalling their own work. Perhaps most troubling was that after a few months, individuals in the AI group became progressively lazier, copying entire blocks of text.

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

Of course, AI's appeal lies in its efficiency. It saves time, minimizes work and – critically – offers a new method to offload responsibility. 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 for the sake of the comforting security of obedience. AI offers a digital avenue for surrendering the burden of having to decide for oneself.

The Opacity Dilemma: Trust Without Understanding

AI's primary draw is its ability to perform tasks outside our minds – analyzing oceans of data at unprecedented speed. Stuck in the car in Marseille, this was, after all, why I chose to trust the app over my companion (a decision she took as an insult). With access to real-time information, certainly the app had superior insight – or so I thought.

The fundamental problem is that AI is a opaque system. It produces answers, but not always fostering human understanding. We do not truly know how AI reaches its decisions – even its programmers admit this. Nor can we verify its reasoning against clear, objective criteria. So when we follow AI's advice, we are not being led by logic. We are back in the realm of belief. In dubio pro machina: when in doubt, side with the machine – that could be our 21st-century credo.

Using Without Losing: The Essential Challenge

AI can be a formidable ally for mankind in scientific pursuit. It can help inventing drugs, free us from "bullshit jobs", or handle administrative chores – duties that are repetitive and are unfulfilling. 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. Critical thinking was not merely about efficiency – it was a discipline of freedom and human self-determination.

Human thought is often chaotic and fallible, but it forces us to argue, to question, to challenge concepts – and to acknowledge the limits of our own knowledge. It builds confidence, both individually and as a society. For Kant, the use of reason was never solely about information; it was about enabling people to become agents of their own destinies, and to resist domination. It was about building a moral community grounded in the shared principle of rational discourse, rather than blind belief.

With all the advantages AI offers, the key question is this: how can we harness its potential of advanced capability without eroding human rationality, the cornerstone of the Enlightenment and of liberal democracy themselves? That is likely one of the defining questions of our time. It is a question we must strive not to delegate to the algorithm.