This recent season, I found myself navigating in congested traffic on the sweltering streets of a southern French city. At a crossing, my companion in the front seat suggested a right turn toward a famous spot for fish soup. However, the digital guide on my phone commanded us to go forward. Weary and in a stifling car, I followed the algorithm's directive. Moments later, we were stranded at a roadwork site.
A minor event, maybe. But one that encapsulates a central dilemma of our time, where digital tools touches almost every aspect of our lives: whom do we trust more – fellow humans and our own intuition, or the machine?
The Enlightenment's Promise and A Contemporary Backslide
The renowned German philosopher Immanuel Kant famously described the Enlightenment as "humanity's emergence from its self-inflicted nonage." This immaturity, he argued, "is the incapacity to use one's personal reason without direction from an external source." For ages, that guiding "other" for society was often the clergyman, the king, or the feudal lord – entities purporting to speak for God's voice. To explain natural events like changing seasons, people sought answers in religion. In shaping the fabric of society, from commerce to matters of the heart, religious doctrine acted 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 confidence to employ it. With upheavals in the 18th century, a fresh era emerged: logic would supplant blind faith, and the intellect, liberated from dogma, would become the engine of advancement and a better world.
Now, two and a half centuries later, one might question if we are slipping back into a form of dependency. An app suggesting a driving route is merely the start. AI risks becoming our new "other" – a unseen overseer that influences our decisions and actions. We are in danger of relinquishing the historically earned courage to think independently – and this time, not to gods or kings, but to lines of code.
The Rapid Rise and Hidden Risks of Algorithmic Reliance
ChatGPT was launched only in 2022, and already a recent study indicated that an vast number of people had engaged with artificial intelligence in the previous six months. Whether deciding on ending a relationship or choosing a candidate, individuals are increasingly turning to machines for guidance. Research suggests a significant portion of user queries relate to personal life matters. Even more intriguing than our reliance on AI for advice is what happens when we allow it express for us. Composition is now among the top uses for generative AI, just behind practical requests. The celebrated American author Joan Didion once remarked, “I write purely to discover what I am thinking.” What occurs when we stop composing? Do we cease discovering?
Alarmingly, emerging research hints the outcome may be yes. A study from the Massachusetts Institute of Technology used electroencephalography to observe the cognitive activity of participants who had access to AI, Google, or nothing. Those who could rely on AI displayed the lowest cognitive engagement and had difficulty accurately recalling their own work. Maybe most troubling was that over time, participants in the AI group grew increasingly reliant, pasting entire blocks of text.
“Laziness and cowardice,” Kant wrote, “are the reasons why so many of men … stay in lifelong immaturity.”
Certainly, AI's appeal lies in its efficiency. It is fast, reduces effort and – critically – offers a new method to offload accountability. In his 1941 book, Escape from Freedom, the German psychoanalyst Erich Fromm argued that the appeal of authoritarianism could be understood by a human tendency to surrender autonomy in exchange for the comforting security of obedience. AI presents a modern method of surrendering the burden of having to think and choose.
The Opacity Dilemma: Faith Over Reason
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, after all, why I chose to believe the machine over my companion (a choice she interpreted as an insult). With access to all the data, surely the algorithm had superior insight – or so I believed.
The core issue is that AI is a black box. It generates answers, but not always deepening human comprehension. We cannot fully grasp how AI reaches its conclusions – even its programmers acknowledge the opacity. Nor can we check its reasoning against clear, objective criteria. So when we heed AI's advice, we are not being led by logic. We are returning to 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 mankind in scientific pursuit. It can aid in medical research, liberate us from "bullshit jobs", or manage administrative chores – duties that demand little thought and are unfulfilling. This is beneficial. But Kant and his contemporaries did not advocate for 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 freedom and human self-determination.
Human thought is inherently messy and error-prone, but it compels us to debate, to question, to test ideas – and to acknowledge the boundaries of our own knowledge. It builds self-reliance, both personally and as a society. For Kant, the exercise of reason was never only about information; it was about empowering people to become agents of their own destinies, and to oppose domination. It was about building a ethical society based on the shared principle of rational discourse, rather than blind belief.
With all the advantages AI brings, the key question remains: how can we leverage its potential of superhuman intelligence without undermining human reasoning, the cornerstone of the Enlightenment and of free societies themselves? That is likely one of the defining questions of our time. It is a question we would do well not to outsource to the algorithm.
