🔗 Share this article

This past summer, I found myself navigating in congested traffic on the sweltering streets of Marseille. At an intersection, my friend in the front seat advised a right turn toward a famous spot for bouillabaisse. However, the navigation app on my phone commanded us to continue straight. Fatigued and in a stifling car, I heeded the app's advice. Minutes later, we were stuck at a roadwork site.

A seemingly trivial incident, perhaps. But one that encapsulates a central dilemma of our time, where digital tools touches nearly every facet of our lives: who gets our trust to a greater degree – other people and our personal instincts, or the machine?

The Enlightenment's Promise and A Contemporary Backslide

The influential German philosopher Immanuel Kant once defined the Enlightenment as "humanity's emergence from its self-inflicted nonage." This immaturity, he argued, "represents the inability to use one's personal reason without direction from an external source." For ages, that directing force for human thought was frequently the priest, the king, or the feudal lord – entities purporting to channel God's voice. To explain natural events like volcanic eruptions, people sought answers in theology. In shaping the fabric of society, from economics to love, faith served as the main compass.

“Sapere aude!” or “Dare to use your own understanding!”

Kant argued that humans had the ability to think rationally. They just didn't have the confidence to employ it. With revolutions in America and France, a new dawn arrived: logic would supplant superstition, and the human mind, freed from dogma, would become the engine of progress and a better world.

Now, 250 years later, one might question if we are quietly regressing into a form of intellectual immaturity. An app suggesting a driving route is just one example. AI threatens to become our contemporary authority – a unseen guide that influences our decisions and behaviors. We risk ceding the hard-won autonomy to reason for ourselves – and now, not to deities or rulers, but to computer programs.

The Rapid Rise and Hidden Risks of Algorithmic Reliance

ChatGPT was launched a mere three years ago, and already a recent study indicated that an vast number of people had engaged with artificial intelligence in the previous six months. Whether contemplating a breakup or choosing a candidate, individuals are looking to algorithms for guidance. Data suggests a large majority of user prompts concern non-work topics. Even more intriguing than our use of AI for advice is what happens when we allow it speak for us. Composition is now one of the top uses for generative AI, just behind practical requests. The late American author Joan Didion famously said, “I write purely to discover what I am thinking.” What transpires when we cease writing? Do we cease discovering?

Worryingly, emerging research hints the outcome may be affirmative. A study conducted by the Massachusetts Institute of Technology used electroencephalography to observe the mental engagement of essay writers who had access to AI, traditional search engines, or nothing. Those who could rely on AI showed the least cognitive engagement and had difficulty quoting their own work. Maybe most concerning was that after a few months, participants in the AI group became increasingly reliant, copying entire blocks of text.

“Laziness and cowardice,” Kant wrote, “are the reasons why so many of men … remain in perpetual nonage.”

Of course, AI's appeal stems from its convenience. It is fast, reduces effort and – critically – offers a novel way to offload accountability. In his 1941 book, Escape from Freedom, the German psychoanalyst Erich Fromm proposed that the rise of fascism could be partly explained by a human tendency to surrender personal freedom in for the sake of the reassuring certainty of subordination. AI offers a modern avenue for relinquishing the weight of having to think and choose.

The Black Box Problem: Faith Over Reason

AI's greatest allure is its capacity to perform tasks beyond our minds – sifting through vast datasets at unprecedented speed. Sitting in the car in Marseille, this was, after all, why I opted to trust the app over my companion (a choice she took as an insult). With knowledge of real-time information, certainly the app must know best – or so I believed.

The core issue is that AI operates as a opaque system. It generates knowledge, but not always deepening human comprehension. We cannot fully grasp how AI reaches its conclusions – including its creators acknowledge the opacity. Nor can we verify its logic against transparent standards. So when we follow 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, trust the machine – that may become our future guiding principle.

Using Without Losing: The Critical Balance

AI can be a powerful tool for mankind in rational inquiry. It can help inventing drugs, free us from tedious tasks, or handle administrative chores – duties that are repetitive and are unfulfilling. This is beneficial. But Kant and his peers did not champion enlightenment just so humans could optimize chores or have more leisure. Independent thought was not merely about productivity – it was a discipline of freedom and human emancipation.

Human thought is inherently messy and fallible, but it forces us to argue, to doubt, to test ideas – and to recognize the limits of our own knowledge. It fosters confidence, both individually and collectively. For Kant, the use of reason was never only about information; it was about empowering people to become agents of their own destinies, and to resist control. It was about creating a moral community based on the common foundation of reason and debate, rather than unquestioning acceptance.

With all the undeniable benefits AI brings, the key question is this: how can we harness its potential of superhuman intelligence without undermining human reasoning, the bedrock of the Enlightenment and of free societies themselves? That is likely one of the central dilemmas of our time. It is a question we must strive not to outsource to the algorithm.