In September 2007, at the Popper conference in Prague, Donald Gillies presented a paper “Problem Solving and the Problem of Induction”. This was included in the collection of conference articles, “Rethinking Popper” edited by Parusnikova and Cohen and published in 2009.
Gillies says Popper’s “induction is a myth’ quotation has become incorrect because science itself is changing. Gillies states in the article, with respect to studies on artificial intelligence: “Developments in machine learning since 1996 have only reinforced the claim that inductive rules of inference exist. Hence it can be argued that Popper’s 1963 ‘induction is a myth’ quotation can no longer be regarded as correct. In fact programs such as Quinlan’s ID3 or Muggleton’s GOLEM (and more recently developed machine learning programs) do make inductive inferences based on many observations and have become part of scientific procedure.”
It seems to me this is a big claim to make.
Challenge it seems to me could come from
- Is the “induction” Gillies refers to the same as what Popper means by induction?
- Does this machine learning only appear to be inductive?
Are the conclusions drawn by machine learning wider in scope than their premises or are they the result of testing and re-testing the programmed assumptions?
Datteri, Hosni and Tamburrini in “Machine Learning from Examples: A Non-Inductivist Analysis” 2005 rejected the view that mechanical learning systems perform epistemically justified inductive generalization and prediction and outlined an alternative deductive account. Gillies does not seem to accept their viewpoint.