About

Summary

I study what actually happens inside large language models — the circuits, features, and representations underneath the fluent output — and I build tools on top of that research. I have worked at the intersection of artificial intelligence and human cognition for nearly four decades, beginning with neural networks in 1987: a PhD in Cognitive Science and Psychology from UC San Diego, a career leading research teams in natural-language systems, and, more recently, hands-on interpretability work on how models encode style, knowledge, and identity.

The through-line has never changed. My doctoral thesis, Artificial Languages, Virtual Brains, used neural networks to study language learning back when the networks were small enough to inspect every unit. The models have grown; the question — how would we actually know what one is doing? — has not.

Currently

• Inside the Black Box — a newsletter on mechanistic interpretability and artificial psycholinguistics, demystifying how LLMs work. insidetheblackbox.ai
• YourVoiceCraft — a privacy-first writing tool I created, built on this research: a private model trained on a writer’s own archive — it writes in their voice, quotes what they’ve actually written, catches drafts that contradict them, and keeps their work off Big AI’s servers. yourvoicecraft.ai
• Interpretability research — LoRA fine-tuning on open models, probing what changes inside a network when it learns a writing style, and using sparse autoencoders to compare fine-tuning strategies at the feature level.

Podcast Appearances

• Marketing in the Age of AI (Emanuel Rose) — Local AI, Clear Workflows, and the End of Fluency Theater. Listen →
• Champion Mindset Collective (Anthony Dahya) — 30 Years in AI: The Truth About How It Works (and How Humans Stay Ahead). Listen →
• Lift-Off (Keith Newman) — Why AI Still Lacks True Agency, and What Founders Must Know. Listen →
• Story-Driven Business Podcast (Susanna Rantanen) — AI Leadership and Trust: How Leaders Can Adopt AI. Listen →
• The Lighthouse Sessions (Jeff Borschowa) — a wide-ranging conversation on building with AI honestly.

Work Experience

Founder, YourVoiceCraft (Arvoinen.AI, LLC), Los Angeles, CA, 2022–present

Independent Researcher, Mechanistic Interpretability, Los Angeles, CA, 2025–present

Chief Scientist (Data Science and Deep Learning), CitizenNet / Condé Nast, Los Angeles, CA, 2010–2020

Senior Research Scientist/Engineer, Fox Audience Network (Fox Interactive Media/MySpace), Santa Monica, CA, 2008–2010

Principal Computer Scientist, MetaLINCS (e-discovery), San Jose, CA, 2007

Senior Scientist and Director of Research, H5 Technologies (search for legal document review), San Francisco, CA, 2005–2007

Senior Engineer and Project Lead, Entrieva (document categorization), Reston, VA, 2003–2005

Principal, Adaptive Lava (neural and NLP search), 2001–2003

Principal Scientist, Comprecorp (text classification), Nevada City, CA, 2001

Senior Engineer, Ask Jeeves (knowledge-base automation and answer accuracy), Emeryville, CA, 1999–2000

Postdoctoral Fellow, Carnegie Mellon University, 1995–1998

Skills and Research Interests

Interpretability & modeling. Mechanistic interpretability (circuits, features, superposition), LoRA fine-tuning, sparse autoencoders, transformer internals.

Languages & platforms. Python.

Research methods. The full experimental-psychology toolkit: literature review, hypothesis development, experimental design and control, protocols, and appropriate statistical analysis.

Standing interests. Language processing and acquisition in humans and neural networks; large-scale cognitive systems; how working memory and the broader cognitive system shape language; and, throughout, the gap between what a model produces and what it understands.

Selected Publications

Blackwell, A. (2012). A Gentle Introduction to Random Forests, Ensembles, and Performance Metrics in a Commercial System. Web blog post. CitizenNet.com.

Blackwell, A., Bates, E., & Fisher, D. (1996). The time course of grammaticality judgement. Language and Cognitive Processes, 11(4), 337–406.

Blackwell, A.W. & Bates, E. (1995). Inducing agrammatic profiles in normals: Evidence for the selective vulnerability of morphology under cognitive resource limitation. Journal of Cognitive Neuroscience, 7, 228–257.

Blackwell, A.W. (1995). Artificial Languages / Virtual Brains. Doctoral dissertation.

Warren, W. H., Mestre, D. R., Blackwell, A. W., & Morris, M. W. (1991). Perception of circular heading from optical flow. Journal of Experimental Psychology: Human Perception and Performance, 17(1), 28–43.

Warren, W. H., Blackwell, A. W., Kurtz, K. J., Hatsopoulos, N. G., & Kalish, M. L. (1991). On the sufficiency of the velocity field for perception of heading. Biological Cybernetics, 65(5), 311–320.

Warren, W. H., Blackwell, A. W., & Morris, M. W. (1989). Age differences in perceiving the direction of self-motion from optical flow. Journal of Gerontology, 44(5), P147–P153.

Education

Ph.D., University of California, San Diego, 1995: Cognitive Science and Psychology.

A.B., Brown University, 1987: Honors Cognitive Science and Honors Creative Writing.