The debate on generative AI seems stuck, circling around questions of cheating, authenticity and technology. It is often framed in overtly moralistic terms, where the focus lies on when and how one is “allowed” to use it for text production. Yet the more decisive question concerns something else: what happens to judgement, understanding and responsibility when people choose to outsource their own thinking?
Of course one should use generative AI, but …
Is it acceptable to use generative AI to write texts? And if so, when and in what way? Are you “authentic” if you let AI generate a text based on your own ideas, and does authenticity even matter? Is it a democratic and inclusive tool that gives everyone a voice, or is it simply “cheating”? Does it impoverish discussion or broaden it? Positions are taken on what is reprehensible and what is permissible. The tone is heated, the moralism evident.
Much less attention is paid to what writing actually is and the function it serves. For the point of writing is not merely to produce text – nor, for some, the exquisite pleasure of finding the right words and arranging them in the right order. The point is also to understand things a little better than one did before. In the process of writing, thoughts are tested, broken down and replaced.
It is through writing that one discovers where one is wrong, where one is unclear and where one lacks sufficient knowledge. It is in writing that opinions change, understanding deepens and new patterns emerge. It is in writing that the obscure becomes clear. As Tegnér might be paraphrased: That which is obscurely written is obscurely thought.
This is why writing is often strenuous and involves resistance. Resistance from the train of thought, resistance from the content, resistance from the words themselves. Filling a page with text is not difficult, but filling a page with the right text may take as long as it takes. The resistance is not inefficiency, however much it may feel like it, but the very mechanism that develops understanding in the writer. This makes resistance essential: writing takes time because it must take time.
We often speak of independent thinking as a right, something contained within the formal recognition of freedom of thought and opinion. In practice, however, independent thinking is more accurately a discipline. It requires repeated effort, resistance and a certain willingness to stand apart. It cannot be handed out as a gift. It must be won, step by step, by each individual.
Freedom of thought and opinion may sound grand, but without independent thinking they amount to very little. In an age where technology offers shortcuts to ready-made answers, independent thinking therefore becomes both more difficult and more decisive.
None of this means that generative AI lacks value. On the contrary. As a tool, it can in many ways improve productivity, structure and clarity. The problem arises when its use shifts from support to substitution.
Cognitive discipline in complex systems
When one hands over all or large parts of writing to generative AI, one does not merely outsource production. One simultaneously outsources parts of one’s own thinking. One gives up practice. One reduces the cognitive effort required to develop analysis and judgement. What one gains in return is, at best, a more polished text and a higher rate of output. What one loses is harder to measure, but undoubtedly more important.
At its core, the mechanism is simple: those who abstain from cognitive effort become worse at it. This applies to understanding. It applies to analysis. It applies to judgement.
Historically, education, research and qualified professional work have been built on the assumption that individuals must develop this discipline themselves. Slowly, and often with frustration. The shortcut that generative AI now offers is naturally attractive, but it creates a structural dilemma: short-term efficiency stands in tension with long-term individual – and societal – capability.
In knowledge-intensive societies, the collective ability to reason, weigh alternatives and make decisions under uncertainty is a critical resource. If this ability gradually weakens, institutions and organisations are affected, and ultimately every political decision. A society in which people cannot formulate their own thoughts and make reasonably independent judgements is a society in which freedom and democracy have been reduced to empty words.
“The most courageous act is still to think for yourself.” – Coco Chanel
The paradox of efficiency and the logic of dependency
It is not difficult to see why generative AI is so appealing. Organisations typically reward rapid output and visible results. Producing more text, more analyses and more supporting material appears rational. Generative AI fits this logic extremely well.
In English, a distinction is drawn between efficiency and effectiveness. The former concerns doing things right – minimising waste of time, resources and effort. The latter concerns doing the right things – actually achieving the goals and outcomes one claims to pursue. Ideally, both are combined. In Swedish, this distinction is lacking, and we often settle for optimising the process and calling it success.
Yet one can be highly efficient in the sense of being fast and productive without coming any closer to what one truly seeks to achieve. And one can reach certain short-term goals while undermining long-term capability. Producing more texts more quickly may appear efficient, but when increased output comes at the cost of reduced understanding, the system becomes more efficient on the surface while its underlying competence – the ability to think independently – is gradually eroded.
Such a development can scarcely be called “success” in any serious sense of the word, regardless of what people choose to label it.
This is not a new phenomenon. Similar dynamics have accompanied other technological shifts, where automation has reduced the need for certain skills while increasing dependence on systems. The difference now is that this concerns not merely manual work, but cognitive processes themselves.
If one writes utilitarian texts – advertising, copy or communications – the consequences may be more limited, as these activities are more concerned with production than with understanding. There is, of course, a risk that writing competence will erode over time, but whether that is a problem is largely a matter of preference. Not everyone wants or needs to be skilled at producing text independently. Thinking, however, I would argue, matters to everyone.
By outsourcing analyses, positions and the development of ideas to generative AI, we outsource our own understanding and judgement. These are extremely difficult to rebuild once weakened. They require experience, effort and exposure to uncertainty. They require mistakes, and the correction of those mistakes. They require time.
Autonomy and intellectual freedom
The ancient Stoics were already clear: no one is free who does not master themselves. In a modern knowledge society, this translates into the ability to think independently. Those who lack this ability are, in practice, never free, regardless of how free the surrounding society may be. Formal freedom of expression, access to information and democratic institutions mean very little if individuals lack the capacity to evaluate, weigh and draw their own conclusions.
Dependence on the analyses of others entails a subtle but real asymmetry of power. Those who do not understand cannot question. Those who cannot evaluate information are at a disadvantage in relation to those who claim to know. Those who cannot formulate their own arguments lose influence to those who can.
Cognitive outsourcing thus creates a divide between those who develop understanding and those who consume ready-made conclusions. The question of generative AI is therefore far larger than matters of efficiency or the importance (according to some) of authenticity when posting on LinkedIn.
Ultimately, it is a question of individual freedom and autonomy, as well as of the very functioning of democratic society.
A choice with consequences
The central question, then, is not whether generative AI should be used. The question is how. If the technology is used to augment human thinking, it can be a powerful tool. If it is used to replace it, it will gradually weaken the intellectual discipline on which modern societies rest.
The issue has technical and organisational dimensions, but at its core it is individual. Systems change only when people change their behaviour. Those who do not take responsibility for their own understanding, who consistently avoid thinking for themselves, should not be surprised when the capacity eventually disappears. The choice is, in principle, free.
But this freedom is formal, not neutral.
Foucault wrote:
“Knowledge is a spiritual adventure and a transformation of the self. The one who knows differs from the one who does not not simply by knowing certain things, but by no longer being the same person. In other words, knowledge is that which transforms the very subjectivity of the knower.
To know, in this sense, is to change. It is a process that requires time, resistance and uncertainty. If we systematically opt out of this process, we also opt out of a part of the person we might otherwise have become.
The question, therefore, is not only what generative AI does to our productivity. The question is who we become when we grow accustomed to not thinking for ourselves.
The choice is free. But not without consequences.
