Integrative perspectives are needed, holism, inter- and transdisciplinarity, no thinking in silos. It would already be a step in this direction to distinguish more clearly, at the purely conceptual level, between the efficiency and the effectiveness of AI. Two different questions follow from this. On the one hand: are given goals achieved quickly and with few resources by means of AI? On the other hand: are the goals achieved by means of AI meaningful for society and for the individual? These then belong to different types of discourse. As far as technical efficiency is concerned, AI is undoubtedly good and is getting better and better; the symptoms of intelligence prove this beyond doubt. There are scenarios in which artificial intelligence is superior to human intelligence; some texts by ChatGPT, for example, undoubtedly sound better than texts written by humans. But one can ask whether in such a case AI is also, to put it simply, good as regards its effectiveness. The paradigm case: AI can save lives in medicine through the rapid evaluation of huge pools of data; AI can destroy lives through a tactically targeted military deployment. In both cases the efficient use of AI is beyond question; the sore point is effectiveness. Or: does it make sense to have ChatGPT write texts for you? Yes and no. Sophisticated techniques of prompt engineering are undoubtedly important if one wants to use ChatGPT efficiently, and it is advisable in this respect to acquire the corresponding technical media literacy. But one could ask whether it is effective at all to enter into this "communication" with ChatGPT, for example to search for information or to have texts summarized or written, and so on. And whether one does not thereby manoeuvre oneself into a comfort zone, outsource central areas of intelligence and so – and this is the point – out of laziness and of one's own free will enter into this dependence and heteronomy and give up self-determination. Who would not think of Immanuel Kant here:

"Immaturity is the inability to make use of one's understanding without the guidance of another. This immaturity is self-incurred when its cause lies not in a lack of understanding but in a lack of resolution and courage to make use of it without the guidance of another. Sapere aude!"

AI has become a perennial topic in the media. A quick impression (which would of course first have to be substantiated by content analysis): the discussion is one-sidedly focused, the perspective of business dominates, AI companies are all the rage, a need to catch up is invoked, and the changing world of work, for example, is also a topic – deeper issues such as sustainability, global social justice and the like are underrepresented. Yet en passant there has always been more demand in the public sphere for a discourse on questions beyond the efficiency of AI, beyond the implementation of AI motivated predominantly by markets and business economics, beyond technical details, how-tos and individual cleverness in using AI.

That is, questions about the effectiveness of AI and its application scenarios. What, for example, are meaningful standards of media literacy in the use of AI, meaningful norms in ethics, regulation and legislation? How should AI competence (AI literacy) be formulated concretely? An efficient and technically competent use of AI is important. But to what extent is the effective, meaningful use of AI also in focus? How are the required competences to be specified if one wants to go beyond (unfortunately often merely slogan-like) formulations such as "reflection", "critical engagement" and so on? In this connection there are several desiderata (Hug 2024, pp. 141–142): overcoming the tool perspective and didactics that are primarily based on learning technology, taking into account media-anthropological dimensions (the use of AI shapes reality), and attending to depth-psychological dimensions. Furthermore: how do influencing and opinion-forming on the subject of AI work in the public sphere? How should AI be presented and discussed in the media and in educational institutions? Predominantly affirmatively and technology-centred, or more critically with regard to the possible consequences of AI for society and the individual? What expert and orientation knowledge can be offered to decision-makers in politics and business? There should be consensus on this much: the sciences should receive a clear mandate from politics to carry out theoretical foundational work objectively, democratically and "disinterestedly", and to help shape all questions concerning the development and use of AI. Markets and privatization alone are toxic; the oligarchs Musk, Bezos, Zuckerberg and their ilk must not be the only ones to set the course.