# Inferring the size of the causal universe: features and fusion of causal attribution networks

## TL;DR

This paper introduces NetFUSES, a method to combine multiple causal attribution networks with ambiguous nodes, estimating that current surveys cover less than 6% of the total human causal attribution universe.

## Contribution

The paper presents NetFUSES, a novel approach for merging causal networks with ambiguous nodes and estimates the total size of human causal attribution networks.

## Key findings

- Existing surveys cover about 5.77% of causes and effects.
- Estimated total causal attribution network contains approximately 293,000 causes and effects.
- Current surveys capture less than 1% of all cause-effect relationships.

## Abstract

Cause-and-effect reasoning, the attribution of effects to causes, is one of the most powerful and unique skills humans possess. Multiple surveys are mapping out causal attributions as networks, but it is unclear how well these efforts can be combined. Further, the total size of the collective causal attribution network held by humans is currently unknown, making it challenging to assess the progress of these surveys. Here we study three causal attribution networks to determine how well they can be combined into a single network. Combining these networks requires dealing with ambiguous nodes, as nodes represent written descriptions of causes and effects and different descriptions may exist for the same concept. We introduce NetFUSES, a method for combining networks with ambiguous nodes. Crucially, treating the different causal attributions networks as independent samples allows us to use their overlap to estimate the total size of the collective causal attribution network. We find that existing surveys capture 5.77% $\pm$ 0.781% of the $\approx$293 000 causes and effects estimated to exist, and 0.198% $\pm$ 0.174% of the $\approx$10 200 000 attributed cause-effect relationships.