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This past summer, I found myself navigating in congested traffic on the sweltering streets of Marseille. At a crossing, my friend in the passenger seat advised a right turn toward a famous spot for bouillabaisse. However, the navigation app on my phone instructed us to go forward. Fatigued and overheated, I heeded the app's directive. Moments later, we were stranded at a construction site.

A seemingly trivial incident, perhaps. But one that captures a defining question of our time, where digital tools touches nearly every facet of our lives: whom do we trust to a greater degree – other people and our own intuition, or the machine?

The Enlightenment's Promise and A Contemporary Backslide

The influential German philosopher Immanuel Kant famously described the Enlightenment as "man's release from its self-inflicted immaturity." This immaturity, he argued, "is the inability to use one's personal reason without guidance from an external source." For centuries, that directing force for society was often the priest, the monarch, or the feudal lord – entities claiming to channel divine will. To explain phenomena like volcanic eruptions, people looked for explanations in religion. In shaping the social world, from economics to love, faith acted as the primary guide.

“Sapere aude!” or “Have courage to use your own understanding!”

Kant maintained that humans had the ability to think rationally. They just didn't have the confidence to use it. With revolutions in America and France, a fresh era emerged: logic would replace superstition, and the intellect, freed from authority, would become the driver of progress and a better world.

Today, two and a half centuries later, one might wonder if we are slipping back into a form of dependency. An app dictating a driving route is merely the start. AI risks becoming our contemporary authority – a unseen guide that influences our choices and actions. We risk ceding the hard-won autonomy to reason for ourselves – and this time, not to deities or rulers, but to lines of code.

The Rapid Rise and Hidden Risks of Algorithmic Reliance

ChatGPT was launched only in 2022, and already a global survey found that an overwhelming majority of people had engaged with artificial intelligence in the preceding half-year. Whether contemplating a breakup or selecting a vote, individuals are looking to machines for counsel. Data suggests a large majority of user queries concern personal life matters. Even more intriguing than our reliance on AI for advice is what happens when we let it speak for us. Composition is now one of the most common uses for generative AI, second only to everyday tasks. The celebrated American author Joan Didion once remarked, “I write purely to find out what I am thinking.” What transpires when we cease writing? Do we lose that path?

Alarmingly, some evidence hints the outcome may be yes. A study conducted by the Massachusetts Institute of Technology used brain monitoring to track the mental engagement of participants who had access to AI, traditional search engines, or no aids. Those who could rely on AI showed the lowest brain activity and had trouble quoting their own work. Perhaps most troubling was that after a few months, individuals in the AI group grew progressively lazier, copying entire blocks of text.

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

Of course, AI's appeal stems from its efficiency. It saves time, reduces effort and – importantly – offers a new method to abdicate accountability. In his 1941 book, Escape from Freedom, the German psychoanalyst Erich Fromm proposed that the appeal of authoritarianism could be understood by a preference to surrender autonomy in for the sake of the comforting security of obedience. AI offers a digital method of relinquishing the burden of having to think and choose.

The Black Box Problem: Trust Without Understanding

AI's primary draw is its ability to accomplish things beyond human capability – sifting through vast datasets at unprecedented speed. Stuck in the car in Marseille, this was, after all, why I chose to trust the machine over my companion (a choice she took as an affront). With knowledge of all the data, surely the algorithm must know best – or so I believed.

The core issue is that AI operates as a black box. It produces knowledge, but not always deepening human understanding. We cannot fully grasp the process behind its decisions – including its programmers acknowledge the opacity. Nor can we check its reasoning against clear, objective criteria. So when we follow AI's recommendation, we are not being guided by reason. We are back in the realm of faith. In dubio pro machina: when in doubt, side with the machine – that could be our future credo.

Harnessing Without Eroding: The Essential Challenge

AI can be a formidable ally for mankind in scientific pursuit. It can aid in inventing drugs, free us from "bullshit jobs", or manage taxes – work that are repetitive and offer little satisfaction. This is beneficial. But Kant and his contemporaries did not advocate for reason over faith just so humans could assemble better furniture or have extra free time. Critical thinking was not merely about efficiency – it was a practice of liberty and human emancipation.

Human thought is often chaotic and fallible, but it compels us to argue, to doubt, to challenge concepts – and to acknowledge the boundaries of our own understanding. It builds self-reliance, both personally and collectively. For Kant, the exercise of reason was never only about information; it was about enabling people to become authors of their own destinies, and to oppose domination. It was about building a ethical society based on the shared principle of reason and debate, rather than blind belief.

With all the undeniable benefits AI offers, the key question is this: how can we harness its potential of advanced capability without undermining human reasoning, the bedrock of the Enlightenment and of liberal democracy itself? That is likely one of the defining questions of our time. It is a question we must strive not to outsource to the machine.