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This past summer, I found myself navigating in gridlocked traffic on the sweltering streets of a southern French city. At a crossing, my friend in the passenger seat suggested a right turn toward a renowned spot for bouillabaisse. Yet, the digital guide on my phone instructed us to go forward. Fatigued and in a stifling car, I followed the app's advice. Minutes later, we were stranded at a construction site.

A seemingly trivial incident, perhaps. But one that encapsulates a central question of our time, where digital tools permeates almost every aspect of our lives: who gets our trust to a greater degree – other people and our own intuition, or the machine?

The Enlightenment's Promise and Our Modern Relapse

The influential German philosopher Immanuel Kant famously described the Enlightenment as "man's release from its self-imposed nonage." This immaturity, he wrote, "is the incapacity to use one's own understanding without direction from an external source." For ages, that directing force for human thought was often the clergyman, the monarch, or the feudal lord – entities claiming to speak for God's voice. To explain phenomena like changing seasons, people looked for explanations in religion. In organizing the social world, from economics to love, faith served as the primary guide.

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

Kant argued that humans had the capacity for reason. They just didn't have the confidence to use it. With revolutions in America and France, a new dawn arrived: logic would replace superstition, and the human mind, liberated from dogma, would become the engine of advancement and a more ethical world.

Now, 250 years later, one might wonder if we are slipping back into a state of dependency. An app dictating a direction is just one example. Artificial intelligence risks becoming our contemporary authority – a unseen overseer that influences our decisions and behaviors. We risk ceding the hard-won autonomy to think independently – and now, not to gods or kings, but to lines of code.

The Swift Adoption and Subtle Dangers of AI Dependence

ChatGPT debuted only in 2022, and yet a global survey found that an overwhelming majority of people had used AI in the previous six months. Whether deciding on ending a relationship or choosing a candidate, individuals are looking to machines for guidance. Research suggests a significant portion of user queries concern personal life matters. Even more intriguing than our use of AI for advice is what occurs when we let it express for us. Composition is now among the top uses for tools like ChatGPT, second only to everyday tasks. The celebrated American author Joan Didion once remarked, “I write entirely to discover what I am thinking.” What occurs when we cease writing? Do we cease discovering?

Worryingly, emerging research suggests the outcome may be affirmative. A study from the Massachusetts Institute of Technology used electroencephalography to track the mental engagement of participants who had access to AI, traditional search engines, or nothing. Those who could rely on AI displayed the least brain activity and had trouble accurately recalling their own work. Maybe most concerning was that over time, participants in the AI group became increasingly reliant, copying large sections of text.

“Inertia and fear,” Kant wrote, “are the reasons why so many of men … stay in lifelong immaturity.”

Certainly, AI's appeal lies in its efficiency. It saves time, reduces effort and – critically – offers a novel way to abdicate accountability. In his 1941 book, Escape from Freedom, the German psychoanalyst Erich Fromm argued that the appeal of authoritarianism could be partly explained by a human tendency to surrender personal freedom in exchange for the reassuring certainty of subordination. AI offers a modern method of surrendering the weight of having to think and choose.

The Opacity Dilemma: Trust Without Understanding

AI's primary draw is its ability to accomplish things beyond human capability – analyzing oceans of data at unprecedented speed. Sitting in the car in Marseille, this was, after all, why I chose to trust the app over my friend (a choice she took as an insult). With knowledge of real-time information, surely the algorithm had superior insight – or so I believed.

The fundamental problem is that AI is a black box. It generates answers, but without necessarily fostering human understanding. We do not truly know how AI reaches its conclusions – even its creators admit this. Nor can we check its reasoning against transparent standards. So when we follow AI's advice, we are not being led by logic. We are returning to the domain of faith. In dubio pro machina: when in doubt, side with the machine – that could be our future guiding principle.

Harnessing Without Eroding: The Essential Challenge

AI can be a formidable ally for mankind in scientific pursuit. It can aid in medical research, liberate 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 advocate for reason over faith just so humans could optimize chores or have more leisure. Independent thought was not merely about productivity – it was a discipline of liberty and human self-determination.

Human thought is inherently messy and error-prone, but it forces us to debate, to question, to test ideas – and to acknowledge the boundaries of our own understanding. It fosters confidence, both individually and as a society. For Kant, the exercise of reason was never solely about acquiring knowledge; it was about enabling people to become authors of their own destinies, and to oppose domination. It was about creating a moral community grounded in the common foundation of reason and debate, rather than blind belief.

With all the advantages AI offers, the key question remains: how can we leverage its potential of advanced capability without eroding human rationality, the bedrock of the Enlightenment and of liberal democracy 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.