Pseudochance vs. true chance in complex systems
Marshall Abrams, University of Alabama Birmingham
Abstract: Pseudorandom number generating algorithms play a variety of roles in scientific practice and raise a number of philosophical issues, but they have received little attention from philosophers of science. In this talk I focus on pseudorandom number generating algorithm implementations (PRNGs) in simulations used to model natural processes such as evolving biological populations. I argue that successful practices involving such simulations, and reflection on the modeled processes, provide reasons to think that many natural processes involve what I call “pseudochance”, which is an analogue of chance or objective probability, and which is what is realized by PRNGs. Pseudochance contrasts with what I call “true chance,” the kind of objective probability that many objective interpretations of probability claim to describe. On my view, when philosophers speak of “chance” or “objective probability,” they have probably intended the term to refer to true chance, but have often applied it to systems that, I would argue, plausibly exhibit only pseudochance.