Inferring Cultural Landscapes with the Inverse Ising Model

TL;DR

This paper adapts the Inverse Ising model and Minimum Probability Flow algorithm to analyze sparse, historical cultural data, revealing a complex landscape of religious and cultural configurations over millennia.

Contribution

It introduces a novel application of physics-inspired machine learning methods to historical cultural data, addressing challenges of data sparsity and bias.

Findings

Revealed a rugged cultural landscape with peaks around state-endorsed religions.

Identified diffuse regions with diverse religious practices.

Demonstrated reliable reconstruction of cultural constraints from incomplete data.

Abstract

The space of possible human cultures is vast, but some cultural configurations are more consistent with cognitive and social constraints than others. This leads to a ``landscape'' of possibilities that our species has explored over millennia of cultural evolution. But what does this fitness landscape, which constrains and guides cultural evolution, look like? The machine-learning algorithms that can answer these questions are typically developed for large-scale datasets. Applications to the sparse, inconsistent, and incomplete data found in the historical record have received less attention, and standard recommendations can lead to bias against marginalized, under-studied, or minority cultures. We show how to adapt the Minimum Probability Flow algorithm and the Inverse Ising model, a physics-inspired workhorse of machine learning, to the challenge. A series of natural extensions -- including dynamical estimation of missing data, and cross-validation with regularization -- enables reliable reconstruction of the underlying constraints. We demonstrate our methods on a curated subset of the Database of Religious History: records from 407 religious groups throughout human history, ranging from the Bronze Age to the present day. This reveals a complex, rugged, landscape, with both sharp, well-defined peaks where state-endorsed religions tend to concentrate, and diffuse cultural floodplains where evangelical religions, non-state spiritual practices, and mystery religions can be found.