collaborators

8 papers

cs.AI2026

Frame-Conditioned Moral Computation in LLaMA 3.1-8B-Instruct: A Mechanistic Interpretability Audit of Ethical Reasoning

Ali Dasdan, Manan Shah, W. Russell Neuman +3

Behavioral audits of Large Language Models on moral prompts measure what the model says, not the internal computation producing it. We use Transluce, an AI-driven mechanistic-inter…

cs.AI2026

Six Llamas: Comparative Religious Ethics Through LoRA-Adapted Language Models

Chad Coleman, W. Russell Neuman, Manan Shah +5

We present Six Llamas, a comparative study examining whether large language models fine-tuned on distinct religious corpora encode systematically different patterns of ethical reas…

cs.CY2026

The Human Condition as Reflected in Contemporary Large Language Models

W. Russell Neuman

This study seeks to uncover evidence of a latent structure in evolved human culture as it is refracted through contemporary large language models (LLMs). Drawing on parallel respon…

cs.AI2026

The Third Ambition: Artificial Intelligence and the Science of Human Behavior

W. Russell Neuman, Chad Coleman

Contemporary artificial intelligence research has been organized around two dominant ambitions: productivity, which treats AI systems as tools for accelerating work and economic ou…

cs.CL2025

"Amazing, They All Lean Left" -- Analyzing the Political Temperaments of Current LLMs

W. Russell Neuman, Chad Coleman, Ali Dasdan +3

Recent studies have revealed a consistent liberal orientation in the ethical and political responses generated by most commercial large language models (LLMs), yet the underlying c…

cs.AI2025

The Convergent Ethics of AI? Analyzing Moral Foundation Priorities in Large Language Models with a Multi-Framework Approach

Chad Coleman, W. Russell Neuman, Ali Dasdan +2

As large language models (LLMs) are increasingly deployed in consequential decision-making contexts, systematically assessing their ethical reasoning capabilities becomes a critica…