Abstract
According to logical psychologism that was popular in the nineteenth century, logic was regarded as a natural ability of human psychology. Consequently, logical competence as a realization of logic knowledge was treated as one of the innate features of human thinking. Nevertheless, within cognitive science, it was experimentally proved that our thinking is not free from cognitive biases, and to the same extent, our reasoning is not free from logical fallacies. Hence, we are forced to consciously clear the thinking of possible distortions to follow logical norms and to realize logical competence thereby. In the paper, it is shown that some cognitive biases are observed even at the level of cellular reactions to the environment and then at the level of animal behavior. Therefore not logic, but cognitive biases are a natural (biological) mechanism of human thinking. So, the problem of defining logical competence arises. In this paper, there are some arguments that logical competence has once appeared as an especial social practice and it has then been developed for a long time before the first treatises on logic.
Highlights
There may be two general approaches to an explication of logical knowledge: normative and phenomenological
Logical concepts and relationships are regarded as established through a creation of logical norms
This paper examines the nature of logical knowledge within the normative approach, namely, logic is presented as a logical competence – the normalized ability to build consistent conclusions, applying certain inference rules
Summary
There may be two general approaches to an explication of logical knowledge: normative and phenomenological. Mathematics is reducible to logic, and the logical competence itself is understood as an ability to draw correct conclusions based on meaningful sentences chosen as axioms or hypotheses (assumptions) This ability is associated exclusively with a knowledge of inference rules, which give consistent results. 3. Cognitive Biases and Informal Logic From the new understanding of logical competence as an ability to mechanically draw consistent conclusions, some plans arose to create artificial intelligence – abstract machines (such as Alan Turing’s machines), which themselves are able, based on the data received at the input of the system, to give new data (like conclusions) at the output from the system so that these new data contain already a new knowledge in the form of processing the received data according to the required algorithms. This experiment shows that even the scientists do not think purely logically with avoiding unintentional fallacies
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