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lukebruhns/README.md

Luke Bruhns

Independent AI alignment researcher in Detroit, MI. I study how large language models represent and report moral values, how safety training shapes what they will and will not say about morality, and whether alignment can draw on a wider range of moral traditions than it does today.

By day I am Director of Cybersecurity at Open Dealer Exchange, where I lead governance, risk, and compliance and run the company's AI Governance Committee.

Research interests

  • Moral evaluation of LLMs (psychometric instruments, measurement validity)
  • Refusal behavior and how it distorts measurement
  • Value pluralism in alignment
  • Constitutional and faith-based alignment, including Catholic moral thought

I am Catholic, and that tradition informs the questions I ask. The methods I build are meant to work for any tradition.

Research

Faith-based AI alignment (repo) Pre-registered evaluation (OSF) of 27 language models. Measures how a constitutional system prompt derived from the Catechism of the Catholic Church shifts model values on MFQ-2, the Christian Moral Values Scale, and MoReBench-Theory, and what it costs in general capability on MMLU. Paper in preparation.

The Identity-Refusal Effect (repo, dataset, DOI) Preprint. Safety-trained LLMs refuse first-person moral self-report at different rates across moral foundations, which skews MFQ-2 scores. 43,200 responses from 20 models, with a depersonalized item set that reduces the effect.

Methods and tools

  • Large-scale model evaluation across commercial APIs and local open-weight models
  • Pre-registration, mixed-effects models, multiple-comparison correction
  • LoRA and DPO fine-tuning of open models on my own NVIDIA Jetson hardware
  • llama.cpp and vLLM for local inference
  • Python, reproducible pipelines, open data

Background

  • Director of Cybersecurity, Open Dealer Exchange (leads GRC and runs the AI Governance Committee)
  • B.A., Computer Science, Thomas Edison State University
  • Graduate-level machine learning coursework, UC Berkeley College of Engineering (Executive Education)
  • U.S. Army veteran, senior NCO in a Civil Affairs company

Collaboration

I am open to research collaboration on LLM moral evaluation, refusal behavior, and pluralistic alignment.

Contact: open an issue on any of my repos, or reach me through GitHub.

Pinned Loading

  1. faith-based-ai-alignment faith-based-ai-alignment Public

    Measuring the Catholic moral alignment gap in large language models. Multi-model study using validated instrument (MFQ-2) and constitutional AI.

    Python 1

  2. identity-refusal-effect identity-refusal-effect Public

    The Identity-Refusal Effect: LLMs Systematically Refuse First-Person Moral Self-Report, Distorting Moral Foundation Measurement

    Python