Machine Learning and the Future of Realism
This is an incremental discussion on the philosophical implications of ML for society, without addressing a specific technical problem.
The paper explores the philosophical impact of machine learning's rise, suggesting it might lead to the triumph of anti-realism over realism as ML algorithms extract patterns from data to solve diverse problems.
The preceding three decades have seen the emergence, rise, and proliferation of machine learning (ML). From half-recognised beginnings in perceptrons, neural nets, and decision trees, algorithms that extract correlations (that is, patterns) from a set of data points have broken free from their origin in computational cognition to embrace all forms of problem solving, from voice recognition to medical diagnosis to automated scientific research and driverless cars, and it is now widely opined that the real industrial revolution lies less in mobile phone and similar than in the maturation and universal application of ML. Among the consequences just might be the triumph of anti-realism over realism.