🔗 Share this article

This recent season, I found myself navigating in congested traffic on the sweltering streets of Marseille. At an intersection, my friend in the front seat suggested a right turn toward a renowned spot for bouillabaisse. However, the digital guide on my phone instructed us to continue straight. Fatigued and in a stifling car, I followed the algorithm's directive. Minutes later, we were stranded at a construction site.

A minor incident, maybe. But one that captures a defining dilemma of our era, where technology permeates nearly every facet of our lives: who gets our trust to a greater degree – fellow humans and our own intuition, or the algorithm?

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 immaturity." This state, he wrote, "represents the incapacity to use one's personal reason without direction from another." For centuries, that directing force for human thought was often the clergyman, the king, or the feudal lord – figures purporting to speak for God's voice. To explain natural events like changing seasons, people looked for explanations in theology. In shaping the social world, from commerce to matters of the heart, faith served as the primary guide.

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

Kant argued that humans always possessed the ability to think rationally. They simply lacked the boldness to employ it. With revolutions in America and France, a new dawn emerged: logic would supplant blind faith, and the human mind, freed from dogma, would become the driver of advancement and a more ethical world.

Today, two and a half centuries later, one might question if we are slipping back into a state of dependency. An app dictating a driving route is just one example. Artificial intelligence risks becoming our new "other" – a unseen overseer that influences our decisions and behaviors. We risk ceding the hard-won courage to think independently – and now, not to deities or rulers, but to lines of code.

The Swift Adoption and Subtle Dangers of Algorithmic Reliance

ChatGPT was launched a mere three years ago, and already a recent study indicated that an vast number of respondents had engaged with artificial intelligence in the previous six months. Whether deciding on a breakup or selecting a vote, individuals are increasingly turning to machines for guidance. Research suggests a large majority of user prompts relate to personal life matters. Even more striking than our use of AI for judgment is what happens when we let it express for us. Writing is now one of the most common uses for generative AI, second only to practical requests. The late American author Joan Didion once remarked, “I write entirely to find out what I am thinking.” What occurs when we stop composing? Do we lose that path?

Alarmingly, some evidence suggests the answer may be yes. A study from the Massachusetts Institute of Technology used electroencephalography to track the mental engagement of participants who had access to AI, Google, or no aids. Those who could use AI showed the lowest cognitive engagement and had difficulty accurately recalling their own work. Perhaps most concerning was that over time, individuals in the AI group grew increasingly reliant, pasting large sections of text.

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

Certainly, AI's appeal stems from its convenience. It saves time, minimizes work and – critically – offers a novel way 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 preference to surrender autonomy in exchange for the reassuring certainty of subordination. AI presents a modern method of relinquishing the burden of having to decide for oneself.

The Opacity Dilemma: Trust Without Understanding

AI's primary draw is its capacity to perform tasks beyond our minds – sifting through vast datasets at lightning pace. Sitting in the car in Marseille, this was, after all, why I opted to trust the app over my friend (a choice she took as an insult). With access to all the data, certainly the app must know best – or so I thought.

The fundamental problem is that AI operates as a opaque system. It produces answers, but not always deepening human understanding. We cannot fully grasp how AI reaches its decisions – even its creators acknowledge the opacity. Nor can we verify its logic against clear, objective criteria. So when we follow AI's recommendation, we are not being led by logic. We are back in the domain of belief. In dubio pro machina: when in doubt, side with the machine – that could be our 21st-century guiding principle.

Using Without Losing: The Critical Balance

AI can be a powerful tool for humanity in scientific pursuit. It can aid in inventing drugs, free us from tedious tasks, or manage administrative chores – duties that demand little thought and are unfulfilling. This is beneficial. But Kant and his peers did not champion enlightenment just so humans could assemble better furniture or have more leisure. Independent thought was not just about efficiency – it was a practice of freedom and human self-determination.

Human thought is often chaotic and fallible, but it forces us to argue, to doubt, to test ideas – and to acknowledge the limits of our own understanding. It builds self-reliance, both personally and collectively. For Kant, the use of reason was never solely about acquiring knowledge; it was about empowering people to become authors of their own destinies, and to oppose domination. It was about building a moral community grounded in the shared principle of rational discourse, rather than unquestioning acceptance.

With all the advantages AI offers, the key question remains: how can we leverage its potential of advanced capability without eroding human reasoning, the cornerstone of the Enlightenment and of free societies themselves? That is likely one of the central dilemmas of our time. It is a question we would do well not to outsource to the algorithm.