For over a decade John Searle's ingenious argument against the possibility of artificial intelligence has held a prominent place in contemporary philosophy. This is not just because of its striking central example and the apparent simplicity of its argument. As its appearance in Scientific American testifies, it is also due to its importance to the wider scientific community. If Searle is right, artificial intelligence in the strict sense, the sense that would claim that mind can be instantiated through a formal (...) program of symbol manipulation, is basically wrong. No set of formal conditions can provide us with the characteristic feature of mind which is the intentionally of its mental contents. Formally regarded, such intentionally is an irreducible primitive. It cannot be analyzed into non-intentional (purely syntactic, symbolic) components. This paper will argue that this objection is based on a misunderstanding. Intentionality is not simply something given which is incapable of further analysis. It only appears so when we mistakenly abstract it from time. When we regard its temporal structure, it shows itself as a rule-governed, synthetic process, one capable of being instantiated both by machines and men. (shrink)

Employing Searle’s views, I begin by arguing that students of Mathematics behave similarly to machines that manage symbols using a set of rules. I then consider two types of Mathematics, which I call Cognitive Mathematics and Technical Mathematics respectively. The former type relates to concepts and meanings, logic and sense, whilst the latter relates to algorithms, heuristics, rules and application of various techniques. I claim that an upgrade in the school teaching of Cognitive Mathematics is necessary. The aim is to (...) change the current mentality of the stakeholders so as to compensate for the undue value presently attached to Technical Mathematics, due to advances in technology and its applications, and thus render the two sides of Mathematics equal. Furthermore, I suggest a reorganization/systematization of School Mathematics into a cognitive network to facilitate students’ understanding of the subject. The final goal is the transition from mechanical execution of rules to better understanding and in-depth knowledge of Mathematics. (shrink)

Tato práce se zabývá otázkou, zda mohou stroje myslet. Sleduje tedy proměny její tematizace u~vybraných filosofů a myslitelů, jimiž jsou: Descartův dualizmus, Turingův test, Searlův čínský pokoj, umělé neuronové sítě manželů Churchlandových a Rapaportova abstrakce a implementace a syntaktická sémantika. Poté, co ukáže, jak se tyto tematizace liší a v~čem se naopak shodují, ptá se práce po povaze vztahu mezi myšlením a jeho projevy, který je ústřední pro oprávněnost Turingova testu. Dále práce akcentuje nutnost kombinace vhodné rozlišovací schopnosti s~reprezentativní mírou (...) komplexity pro adekvátnost myšlenkového experimentu s čínským pokojem. Konečně se práce také zabývá vztahy mezi duplikací, abstrakcí a implementací fenoménu myšlení. (shrink)