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Digital Philosophy

Studying Smarter with AI?

Max Gottschlich on sense and nonsense when using AI in academia.

Artificial intelligence is becoming an ubiquitous companion in our lives and institutions. As we strive for greater convenience and efficiency, we’re increasingly outsourcing our intellectual activities in judging, reasoning, and decision-making to what Bruno Liebrucks called ‘automated thinking’. In former times, it was believed that the divine intellect alone could comprehend a large totality at one glance. But nowadays, any AI user can feel like a voluntaristic deity, capable of commanding entire worlds of data at will. AI is especially appealing when thinking is hard work – as it is in education, and particularly at university. In subjects involving large amounts of text, using AI seems to offer a convenient shortcut. But this is only a seductive semblance. Cutting through this illusion requires a quite developed insight into the point of studying at all.

Artificial Intelligence Knowledge Alenoach 2023 Public Domain

The central problem is that the use of AI in the academy poses a threat to independent thinking. It undermines the tension thinking needs for a critical engagement with science and represents the final closure of an attitude of consumption established well before it. Why exert oneself when the hard work can be outsourced? Yet this attitude is contrary to the idea of university education. Being a student means acquiring the current level of knowledge achieved in your chosen discipline, reflecting critically upon it and ultimately perhaps even extending it. All of this takes hard work. Hegel called it the ‘sour labour of the concept’. AI evokes the seductive illusion that such labour is no longer necessary, but what in fact happens is that control is abandoned to automated thinking all too easily.

It is an error to believe that one can avoid thinking for oneself. Indeed it begins already in the lecture hall. The universally accepted method of writing notes during the lecture is practiced less and less. It seems to have become unnecessary. Devices like smartphones evoke the semblance of easy availability. A photo is taken of something which is then regarded as acquired and secured. But then why is taking notes on the lecture so important? Because it represents an elemental activity of acquisition. Each sentence heard has to be actively thought through and instantaneously decided upon: is what has been heard essential in terms of the matter at hand and hence to be recorded, or not? This discriminating judgment separating essential from inessential is itself already an activity of comprehending. It can only be acquired by exercise. Initially this will be difficult and almost everything said will be written down. But improvement makes it easier to distinguish and then the clearer and more pertinent the notes become.

In general neither speaking nor learning can be reduced to automatic operations on signs. This becomes especially obvious in the case of scientific texts. For those not yet initiated into a discipline, these texts will be opaque. The student knows neither the terminology nor the problem at issue nor its relevance. It’s all a lot of signs without meaning. Nevertheless it remains true both for difficult texts and for straightforward ones: the meaning within them has to be revived to new life by speaking, reading, thinking. To that end the student must remain permanently active on their own initiative. From what is read only those meanings can be received that one is capable of evoking in oneself. The more we occupy ourselves with the matter the more concrete our comprehension and the more meaningful the texts become.

Growth Thrives on Resistance

AI promises the attractive possibility of an abbreviation where none is available. The illusion of the easy availability of texts arbitrarily generated and arranged is highly seductive, but this semblance is the greatest obstacle to the acquisition of knowledge and finding new information. Whoever wishes to avoid personal engagement with the matter, including the experience of failure, of failure to understand, whoever prefers not to exercise their own insight against the resistance of a text that initially appears completely opaque, denies themselves the possibility of genuine insight and new knowledge. Growth does not happen without resistance. We know this from the physical powers of our bodies and it holds just as much for the mental capabilities of our minds. The body degenerates without gravity and in the weightlessness of automatically generated stocks of information the mind decays.

If this engagement is abandoned to AI then the mind falls into a double dependency. There is firstly a dependency on algorithms which fundamentally do nothing more than combine signs according to probabilities. Reliance on the data material currently accessible on the net also has its dangers. Such dependence represents the opposite of critical thinking. In contrast to this kind of automated thinking, the critical kind is characterised by its capacity to ground itself, reflecting upon the sources and presuppositions of its knowledge and steering its own development in an awareness of its path forward and its goal. This critical thinking is precisely what should be cultivated in university study.

The meaningful utilisation of AI, for example as translation support, thus requires that we always be even ‘better’ than the AI software and that means being able to assess and evaluate the quality of the results it delivers. This sovereignty of critical judgment can only be achieved by autonomous thinking. AI’s role in this could be that of a vehicle making it easier to traverse a known distance. But the goal of the journey must be known in advance as well as the pathway to it.

Courage for Autonomous Thinking

A good knowledge of a foreign language is a great advantage in using translation software. As a rule each sentence delivered by AI will be refined from knowledge of terminology and semantics also with the help of software. Another example: obviously AI can be used as a source of inspiration in the preparation for a meeting. This can save time in a hectic business day. Even here though it is necessary to remain in overall command of the procedure and not to abandon control to the machine without a critical awareness.

Briefly then the use of AI as a substitute for the direct, personal engagement with a problem undermines the autonomy of the student in dealing with the given issue. Academic study is not about reaching a conclusion with the minimum effort possible.

Against the temptation to make life easy and comfortable for oneself with AI stands the impetus to the freedom of an autonomous critical thinking. Every academic study lives on the resilience of thinking. Immanuel Kant’s maxim of enlightenment has lost none of its force: Sapere aude! or in English “Have the courage to use your own understanding!” This courage is called upon more now than ever to avoid succumbing to the temptation of the illusion of easy accessibility with AI. What Kant means is clearly that the mind must free itself from bondage. That can only happen when its thinking is founded on the authority of reason and not on the tutelage of ‘intelligent’ systems.

Max Gottschlich is at the Institute for Practical Philosophy/Ethics at the Catholic Private University of Linz in Austria.