Our King, Our Priest, Our Feudal Lord – The Way AI Returns Us to the Dark Ages.
This past summer, I was caught in gridlocked traffic on the scorching streets of Marseille. At a crossing, my companion in the passenger seat suggested a right turn toward a famous spot for fish soup. Yet, the navigation app on my phone commanded us to go forward. Fatigued and in a stifling car, I followed the app's directive. Moments later, we were stranded at a construction site.
A minor event, perhaps. But one that encapsulates a central dilemma of our era, where digital tools touches nearly every facet of our lives: who gets our trust more – fellow humans and our personal instincts, or the algorithm?
The Enlightenment's Promise and Our Modern Relapse
The renowned German philosopher Immanuel Kant famously described the Enlightenment as "humanity's emergence from its self-imposed immaturity." This state, he argued, "represents the inability to use one's own understanding without direction from another." For centuries, that directing force for human thought was often the priest, the king, or the feudal lord – entities purporting to channel God's voice. To comprehend phenomena like changing seasons, people looked for explanations in religion. In organizing the social world, from economics to matters of the heart, religious doctrine served as the primary guide.
“Sapere aude!” or “Have courage to use your own understanding!”
Kant maintained that humans always possessed the ability to think rationally. They simply lacked the boldness to employ it. With revolutions in the 18th century, a fresh era arrived: logic would replace superstition, and the intellect, freed from authority, would become the driver of progress and a better world.
Now, 250 years later, one might wonder if we are slipping back into a form of intellectual immaturity. An app suggesting a driving route is just one example. AI threatens to become our contemporary authority – a silent guide that steers our choices and behaviors. We risk ceding the historically earned autonomy to reason for ourselves – and now, not to deities or rulers, but to computer programs.
The Rapid Rise and Subtle Dangers of Algorithmic Reliance
ChatGPT debuted only in 2022, and yet a recent study found that an vast number of people had used AI in the previous six months. Whether contemplating a breakup or choosing a candidate, individuals are increasingly turning to algorithms for counsel. Research suggests a significant portion of user queries relate to non-work topics. Even more striking than our reliance on AI for advice is what occurs when we let it speak for us. Writing is now among the most common uses for generative AI, second only to practical requests. The celebrated American author Joan Didion once remarked, “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 mental engagement of participants who had could use AI, Google, or nothing. Those who could rely on AI showed the lowest brain activity and had trouble quoting their own work. Maybe most troubling was that over time, participants in the AI group became progressively lazier, pasting large sections of text.
“Laziness and cowardice,” Kant wrote, “are the reasons why so great a proportion of men … remain in perpetual nonage.”
Of course, AI's appeal stems from its convenience. It saves time, reduces effort 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 understood by a preference to surrender personal freedom in exchange for the comforting security of subordination. AI presents a digital method of surrendering the weight of having to think and choose.
The Black Box Problem: Trust Without Understanding
AI's primary draw is its capacity to accomplish things outside our minds – sifting through oceans of data at lightning pace. Stuck in the car in Marseille, this was, ultimately, why I chose to believe the app over my friend (a choice she took as an insult). With knowledge of all the data, surely the app had superior insight – or so I thought.
The core issue is that AI operates as a opaque system. It produces answers, but without necessarily fostering human understanding. We cannot fully grasp how AI reaches its decisions – including its programmers admit this. Nor can we check its logic against clear, objective criteria. 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 may become our 21st-century credo.
Using Without Losing: The Essential Challenge
AI can be a formidable ally for humanity in scientific pursuit. It can help inventing drugs, free us from tedious tasks, or handle taxes – duties that demand little thought and are unfulfilling. All to the good. But Kant and his peers did not champion reason over faith just so humans could assemble better furniture or have extra free time. Critical thinking was not just about productivity – it was a discipline of liberty and human self-determination.
Human thought is often chaotic and error-prone, but it forces us to argue, to question, to challenge concepts – and to acknowledge the boundaries of our own understanding. It builds self-reliance, both personally and as a society. For Kant, the use of reason was never only about information; it was about enabling people to become agents of their own destinies, and to oppose control. It was about building a ethical society grounded in the common foundation of rational discourse, rather than blind belief.
With all the undeniable benefits AI offers, the paramount challenge remains: how can we harness its promise of superhuman intelligence without undermining human reasoning, the bedrock 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 machine.