Prof. Dr. Vincent C. Müller
Is AI really about K and I?
Lecture on December 12, 2025
The heated debate surrounding “AI” has a lot to do with the term itself—we no longer talk about “pattern recognition,” “computer-assisted language analysis,” or similar concepts, but rather about “artificial intelligence,” which comes with a completely different set of expectations. I will explain what the two parts of this term actually mean, i.e., “artificial” and “intelligence,” and what would be necessary to create such a system on computers. Finally, I will consider the question of whether current, foreseeable, or conceivable AI systems deserve the term “artificial intelligence” in this sense.
Prof. Dr. Vincent C. Müller
Vincent C. Müller is Alexander von Humboldt Professor of Philosophy and Ethics of Artificial Intelligence and Director of the Centre for Philosophy and AI Research (PAIR) at the University of Erlangen-Nuremberg (6 postdocs, 6 doctoral students). He previously worked in Eindhoven, Thessaloniki, Leeds, Oxford, and Princeton. Müller's work focuses primarily on philosophical problems related to artificial intelligence, both in ethics and theoretical philosophy. His website is at www.sophia.de.
Recording of the lecture on December 12, 2025
Review of the lecture evening with Prof. Dr. Vincent C. Müller
The lecture evening was devoted to the fundamental question of what “artificial intelligence” actually means and what expectations the term itself evokes. Prof. Dr. Vincent C. Müller showed that the current AI debate is less influenced by specific technical processes than by the meaning attached to the term “artificial intelligence,” which goes far beyond classic concepts such as pattern recognition or computer-assisted language analysis.
The lecture focused on a differentiated examination of the terms “artificial” and “intelligence.” Prof. Dr. Müller explained the philosophical, technical, and ethical requirements that would have to be met in order to speak of true intelligence at the machine level. In doing so, he critically questioned whether current or foreseeable AI systems actually meet this requirement.