Our King, Our Priest, Our Feudal Lord – The Way AI Returns Us to the Dark Ages.

This recent season, I found myself navigating in congested traffic on the sweltering streets of Marseille. At a crossing, my friend in the front seat advised a right turn toward a famous spot for bouillabaisse. Yet, the navigation app on my phone commanded us to go forward. Weary and in a stifling car, I heeded the app's advice. Minutes later, we were stuck at a construction site.

A seemingly trivial incident, maybe. But one that captures a central question of our era, where technology permeates nearly every facet of our lives: whom do we trust more – fellow humans and our personal instincts, or the machine?

A Call for Intellectual Maturity and A Contemporary Backslide

The renowned German philosopher Immanuel Kant once defined the Enlightenment as "man's release from its self-inflicted immaturity." This state, he wrote, "is the incapacity to use one's own understanding without guidance from another." For ages, that guiding "other" for human thought was often the priest, the king, or the landowner – figures claiming to channel God's voice. To explain phenomena like changing seasons, people sought answers in theology. In shaping the fabric of society, from commerce to matters of the heart, religious doctrine acted as the main compass.

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

Kant argued that humans had the ability to think rationally. They simply lacked the confidence to employ it. With upheavals in the 18th century, a new dawn emerged: reason would replace superstition, and the intellect, freed from dogma, would become the driver of progress and a better world.

Today, 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 just one example. AI threatens to become our new "other" – a silent overseer that influences our decisions and behaviors. We risk ceding the hard-won autonomy to think independently – and this time, not to gods or kings, but to lines of code.

The Rapid Rise and Subtle Dangers of AI Dependence

ChatGPT was launched a mere three years ago, and already a recent study found that an overwhelming majority of people had engaged with artificial intelligence in the preceding half-year. Whether deciding on ending a relationship or selecting a vote, individuals are looking to machines for guidance. Research suggests a significant portion of user queries relate to personal life matters. 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 most common uses for tools like ChatGPT, second only to practical requests. The late American author Joan Didion once remarked, “I write entirely to find out what I am thinking.” What transpires when we cease writing? Do we cease discovering?

Worryingly, some evidence suggests the answer may be yes. A study conducted by the Massachusetts Institute of Technology used electroencephalography to observe the cognitive activity of essay writers who had could use AI, Google, or nothing. Those who could use AI showed the lowest brain activity and had difficulty accurately recalling their own work. Perhaps most troubling was that over time, individuals in the AI group grew increasingly reliant, pasting large sections of text.

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

Certainly, AI's attraction lies in its efficiency. It saves time, reduces effort and – importantly – offers a new method to offload responsibility. In his 1941 book, Escape from Freedom, the German psychoanalyst Erich Fromm proposed that the rise of fascism could be partly explained by a preference to surrender autonomy in for the sake of the comforting security of obedience. AI offers a modern avenue for surrendering the burden of having to decide for oneself.

The Black Box Problem: Faith Over Reason

AI's greatest allure is its capacity to perform tasks beyond human capability – sifting through oceans of data 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 knowledge of all the data, certainly the algorithm must know best – or so I believed.

The fundamental problem is that AI is a opaque system. It produces answers, but not always fostering human comprehension. We do not truly know how AI reaches its decisions – including its creators acknowledge the opacity. Nor can we verify its reasoning against clear, objective criteria. So when we heed AI's advice, we are not being guided by reason. We are back in the realm of faith. In dubio pro machina: when in doubt, trust the machine – that could be our 21st-century credo.

Harnessing Without Eroding: The Critical Balance

AI can be a formidable ally for humanity in rational inquiry. It can aid in medical research, free us from tedious tasks, or manage taxes – duties that are repetitive and are unfulfilling. All to the good. But Kant and his peers did not champion enlightenment just so humans could assemble better furniture or have extra free time. Critical thinking was not just about efficiency – it was a practice of freedom and human self-determination.

Human thought is inherently messy and fallible, but it forces us to debate, to question, to challenge concepts – and to recognize the limits 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 agents of their own destinies, and to oppose control. It was about creating a moral community based on the shared principle of reason and debate, rather than blind belief.

With all the advantages AI brings, the paramount challenge is this: how can we harness its promise of superhuman intelligence without undermining human reasoning, the cornerstone of the Enlightenment and of liberal democracy itself? That is likely one of the central dilemmas of our time. It is a question we must strive not to outsource to the algorithm.