Aristotle on building scientific databases: tools for pre-demonstrative reasoning

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Aristotle is well known to logicians for two achievements found in his Analytics: first, for his syllogistic, both assertoric and modal, which he develops in Prior Analytics I 1–26 by providing a systematic presentation of “syllogisms,” inference patterns in which two premises and oneconclusion share three common terms (either subject or predicate). Second, for his theory of demonstrative science, mainly developed in the first book of the Posterior Analytics, in which he defines scientific knowledge (episteme), which is the highest form of understanding there is, as requiring demonstration (apodeixis), adding further requirements to the basic syllogistic patterns of the Prior Analytics: the premises of scientific syllogisms must be true, prior to the conclusion, better known than it and cause of it. The picture of Aristotle that emerges from these twoachievements is that of a logician sure of himself and confident that his art offers a failsafe method for securing scientific knowledge, understood as true, necessary, and causally justified knowledge. As suggested by the limited set of texts from which it is built, this picture is partial.In this presentation, I will not focus on Aristotle’s syllogistic or his theory of demonstration; I will rather focus on the pre-demonstrative stage of scientific inquiry, a stage that has been dwelled upon in recent studies (see the bibliography) and that is so steeped into the content under inquirythat the reasoning patterns used are not as obvious as they are in the case of syllogisms. As I will argue, this pre-demonstrative stage is mainly a database building stage: before researchers can even think about demonstrations, they need to be well acquainted with their subject matter,which, for Aristotle, means potentially building structured lists of terms relevant to the subject matter.My presentation will consist in sketching out the database-building machinery at work in Aristotle’s conception of scientific inquiry as it is being carried out, that is, before it has found its final and stable — demonstrated — form. As James Lennox has stressed, the stage of Aristotle’szoological work History of Animals is set in the pre-demonstrative stage of scientific inquiry; I will use passages from this work to show how it can work as a database with indications as how such a database can be produced. This, arguably, is the bedrock of Aristotelian science. What is more,in the pons asinorum of Prior Analytics I 26–31, the chapters that immediately follow syllogistic, Aristotle develops a machinery built on lists of terms that is supposed to render people capable of actually putting syllogistic into practice, using actual content. Reading this machinery with hisdatabase-building scientific work shows a continuity between Aristotle’s work as a logician and his work as a zoologist, allowing to read the Analytics as providing tools for producing a science, a science that is therefore still in the making, full of obscurities, incompatibilities, and partial data.This historical study provides a picture of Aristotle as a logician also interested in the difficulties linked to the subject matter itself, to what can be called material logic, something that may never be fully formalized but that provides deep insights into formal logic (Aristotle’s and our modernones) as well as scientific reasoning as it is carried out.ReferencesBronstein, D. (2016). Aristotle on Knowledge and Learning: The Posterior Analytics. Oxford:Oxford University Press.Ferejohn, M. (1991). The Origin of Aristotelian Science. New Haven: Yale University Press.Lennox, J. (2001). Aristotle’s Philosophy of Biology. Studies in the Origin of Life Science. Cambridge: Cambridge University Press.Lennox, J. (2021). Aristotle on Inquiry. Erotetic Frameworks and Domain-Specific Norms. Cambridge: Cambridge University Press.