How meaningful is information acquired from measured data? AI and machine learning technology suggest that information can be "read" from data in a straightforward, objective manner. In an online seminar, prof.dr.ir. Mieke Boon discussed this philosophical issue, using a case-study of traditional scientific research in bioprocess-engineering
With the discussion of a biohydrometallurgy case, Mieke philosophically analysed the assumption above. In the case, the mechanism responsible for bioleaching of metals from ore was investigated. This is a naturally occurring process, used in industry for the recovery of metals from ores. There are many physically possible phenomena included in the research problem, which may happen simultaneously as a part of, or disturbing the mechanism. The hard part is that these phenomena cannot be detected independently.
Mieke showed how scientists think when dealing with complex issues in experimental research, and she philosophically analysed these reasoning strategies, which were called "epistemic strategies" in the talk, where "epistemic" means "aimed at knowledge". She also argued that revealing, and teaching and learning those strategies can contribute to the quality of science and (academic) engineering.
In her work, Mieke developed multiple epistemologies relevant to the engineering sciences. As an example, a recent article which addresses "an epistemology of scientific models".
Does this topic spark your interest? On the website of BEC, you can find the abstract, introduction video and the talk of Mieke, and all other contributors.