About

The researcher

Adam Zachary Wasserman is an independent researcher and author working at the intersection of philosophy of science, artificial intelligence, and the nature of cognition. Author of Honest Code (2026) and The Chaos Factory (2017, favorably reviewed by Bloor Research); in preparation: The Robot in the Dark and The Linguistic Telescope.

Forty years of operational practice building enterprise software systems in regulated industries, including CTO of the International Air Transport Association (IATA), Director of Consulting at CGI, and senior technical-leadership roles at Bombardier and Yellow Pages. Since 2017, the writing has been public: articles, essays, and books on coding paradigms, the foundations of language and cognition, and the limits of scientific instruments.

• ORCID: 0009-0002-8865-6583
• Hub: adamzacharywasserman.com
• Substack archive: emusings.substack.com (40+ essays since 2022)

Collaborators

• David Beauchemin (Université Laval)

  NLP researcher and Quebec-French language-model evaluation specialist with a published track record in cross-linguistic structure and benchmark development. Co-creator of the QFrBLiMP and QFrCoLA native-Quebec-French minimal-pair benchmarks (Beauchemin et al. 2025) on which the empirical case study depends. Co-author with Wasserman on the BabyLM 2026 / EMNLP 2026 paper Right Tool, Right Job and on the EMNLP main-conference submission extending the Scaling Hypothesis Is Language-Contingent line. Written commitment on file.

• Hafedh Mili (Université du Québec à Montréal)

  Full Professor in the Department of Computer Science at UQAM, with a long publication record in formal methods, software engineering, and computational correctness. Connected to the related computational-correctness work that extends the foundational discipline operationally.

• Edward Levin (VM4AI)

  Architect of VM4AI (Virtual Machine for AI), a geometry-aware cognitive controller that applies topological constraints to structure AI reasoning. Joint researcher on the geometric-loss-function study testing whether VM4AI's topologies (Polytope, Sphere) applied as training-time loss-function regularizers can replicate the structural advantages morphologically rich languages provide naturally. Pre-registrations in preparation. Repository: github.com/adamzwasserman/wasserman-levin-2026.

• Phase 2: 4E cognition (collaboration in formation)

  The Phase 2 empirical track on 4E cognition (embodied, embedded, enacted, extended) will be led with a philosopher of cognitive science working in that framework. Outreach is a Phase 1 deliverable; the collaboration is not yet confirmed, so the prospective collaborator is described by role rather than named here.

Selected bibliography

Foundational philosophical and theological sources

• Al-Ghazali. (1095). Tahafut al-Falasifa (The Incoherence of the Philosophers).
• Augustine of Hippo. (c. 408-414). De Genesi ad Litteram.
• Averroes (Ibn Rushd). (c. 1180). Tahafut al-Tahafut (The Incoherence of the Incoherence).
• Bellarmine, Robert, S.J. (1615). Letter to Paolo Antonio Foscarini.
• Cartwright, Nancy. (1999). The Dappled World: A Study of the Boundaries of Science. Cambridge University Press.
• Chalmers, David. (1995). “Facing Up to the Problem of Consciousness.”
• Clark, Andy. (2008). Supersizing the Mind: Embodiment, Action, and Cognitive Extension.
• Deacon, Terrence W. (2011). Incomplete Nature: How Mind Emerged from Matter.
• Dennett, Daniel C. (1987). The Intentional Stance.
• Friston, Karl. (2010 onward). The Free Energy Principle and active inference.
• Gödel, Kurt. (1931). “Über formal unentscheidbare Sätze der Principia Mathematica und verwandter Systeme I.”
• Hutchins, Edwin. (1995). Cognition in the Wild.
• Jaynes, Julian. (1976). The Origin of Consciousness in the Breakdown of the Bicameral Mind.
• Kauffman, Stuart A. (1993). The Origins of Order: Self-Organization and Selection in Evolution.
• Kuhn, Thomas S. (1962). The Structure of Scientific Revolutions.
• Levin, Michael. (2010 onward). Bioelectric signaling and morphogenesis at the Allen Discovery Center, Tufts.
• Maimonides, Moses. (c. 1190). Dalalat al-Ha'irin (Guide for the Perplexed).
• Margulis, Lynn. (1967, 1970, and onward). Endosymbiotic theory; bacterial and cellular agency.
• Maturana, Humberto R., and Francisco J. Varela. (1980). Autopoiesis and Cognition.
• McGilchrist, Iain. (2009). The Master and His Emissary: The Divided Brain and the Making of the Western World. Yale University Press.
• McGilchrist, Iain. (2021). The Matter With Things: Our Brains, Our Delusions, and the Unmaking of the World. Perspectiva Press. (Supported by Templeton World Charity Foundation.)
• Nagarjuna. (c. second century). Mulamadhyamakakarika (Fundamental Verses on the Middle Way).
• Spinoza, Baruch. (1677). Ethics, Demonstrated in Geometrical Order. Particularly Part 2 (Of the Nature and Origin of the Mind), Propositions 1-13.
• Tetlock, Philip E. (2005). Expert Political Judgment: How Good Is It? How Can We Know?
• Tomasello, Michael. (2003). Constructing a Language: A Usage-Based Theory of Language Acquisition.
• Tononi, Giulio, and Christof Koch. Integrated Information Theory (foundational papers, 2004 onward).
• Wittgenstein, Ludwig. (1922). Tractatus Logico-Philosophicus.
• Wittgenstein, Ludwig. (1953). Philosophical Investigations.

Empirical and machine-learning sources

• Beauchemin, David, et al. (2025). QFrBLiMP and QFrCoLA: Quebec-French native minimal-pair benchmarks.
• Biderman, Stella, et al. (2023). “Pythia: A Suite for Analyzing Large Language Models Across Training and Scaling.”
• Hoffmann, Jordan, et al. (2022). “Training Compute-Optimal Large Language Models” (Chinchilla scaling laws).
• Kaplan, Jared, et al. (2020). “Scaling Laws for Neural Language Models.”
• Wasserman, Adam Z. (2026). The Scaling Hypothesis Is Language-Contingent. Zenodo 10.5281/zenodo.19423151.
• Wasserman, Adam Z. (2026). English Considered Harmful. Zenodo 10.5281/zenodo.19443358.
• Wasserman, Adam Z. (2026). The 70% Rule. Zenodo 10.5281/zenodo.19423101.
• Wasserman, Adam Z., and David Beauchemin. (2026). Right Tool, Right Job: Why Training Language Matters More Than Training Data. Submitted to BabyLM 2026 / EMNLP 2026 Budapest.
• Wasserman, Adam Z., and Edward Levin. (2026). Geometric Loss Functions and Cross-Linguistic Training Dynamics. In preparation.

Public-facing essay archive

• Wasserman, Adam Z. (2022-2026). Essential Musings Substack archive at emusings.substack.com, including the foundational Weinstein vs. Dawkins three-part series (May 2022).