An important comparison of software for Scale Sensitive Fractal Analysis : are ancient and new results compatible?

Abstract

In this paper, I will explore some of the implications of machine learning for archaeological method and theory. Against a back-drop of the rise of Big Data and the Third Science Revolution, what lessons can be drawn from the use of new digital technologies and computational approaches as they are applied to archaeological typologies? In this paper, I explore two key aspects of these approaches - automation and epistemic novelty – and attempt to unravel their implications for archaeological practice. Furthermore, the paper will situate these topics within developments of the philosophy of science and technology and suggest an alternative way to think about machine learning that draws on re-thinking what we mean by machines and automation.