What Lives? A meta-analysis of diverse opinions on the definition of life

TL;DR

This paper uses large language models and advanced clustering techniques to analyze diverse definitions of life, revealing a continuous conceptual landscape that bridges reductionist and holistic perspectives across disciplines.

Contribution

It introduces a novel computational methodology combining semantic analysis and clustering to map and understand the complex, multi-disciplinary landscape of the definition of life.

Findings

Revealed a continuous landscape of life definitions

Identified distinct conceptual archetypes within the definitions

Bridged reductionist and holistic approaches through semantic analysis

Abstract

The question of "what is life?" has challenged scientists and philosophers for centuries, producing an array of definitions that reflect both the mystery of its emergence and the diversity of disciplinary perspectives brought to bear on the question. Despite significant progress in our understanding of biological systems, psychology, computation, and information theory, no single definition for life has yet achieved universal acceptance. This challenge becomes increasingly urgent as advances in synthetic biology, artificial intelligence, and astrobiology challenge our traditional conceptions of what it means to be alive. We undertook a methodological approach that leverages large language models (LLMs) to analyze a set of definitions of life provided by a curated set of cross-disciplinary experts. We used a novel pairwise correlation analysis to map the definitions into distinct feature vectors, followed by agglomerative clustering, intra-cluster semantic analysis, and t-SNE projection to reveal underlying conceptual archetypes. This methodology revealed a continuous landscape of the themes relating to the definition of life, suggesting that what has historically been approached as a binary taxonomic problem should be instead conceived as differentiated perspectives within a unified conceptual latent space. We offer a new methodological bridge between reductionist and holistic approaches to fundamental questions in science and philosophy, demonstrating how computational semantic analysis can reveal conceptual patterns across disciplinary boundaries, and opening similar pathways for addressing other contested definitional territories across the sciences.