Toward a Bayesian Epistemology of Anthropology and Archaeology

Summary

This is an abstract from the "The Expanding Bayesian Revolution in Archaeology" session, at the 88th annual meeting of the Society for American Archaeology.

To date, the “Bayesian Revolution” in archaeology has focused primarily on statistical inference: the move from hypothesis testing to credence building. Bayesian thinking extends far beyond the practicalities of statistical inference. Bayesian theory is about epistemology; it describes how we acquire knowledge of the world by reducing the uncertainty of our predictions by updating prior expectations. We encounter the uncertain world and extract information from these interactions, which we then use to build inferences that make predictive models of that now less-uncertain world. We do this when we learn the layout of a new city, or when we make stone tools, or when we excavate a site, or when we model data. Importantly, this is no metaphor: mathematically, information is the reduction of uncertainty gained from an interaction. In this talk, I highlight how Bayesian inference is the natural language that bridges key concepts in anthropology, such as cognition, learning, and adaptation. Moreover, from a Bayesian perspective, the archaeological record is quite literally the embodied information of human-environment interactions in the past. Using examples of stone tool technologies in ethnohistoric hunter-gatherer societies, I show how Bayesian inference lies at the intersection of information theory, statistical inference, and anthropology.

This Resource is Part of the Following Collections

• The Expanding Bayesian Revolution in Archaeology   •
• Society for American Archaeology 88th Annual Meeting, Portland, OR (2023)

Keywords

Record Identifiers

Abstract Id(s): 37613.0