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philosophy of science & artificial intelligence — university of pittsburgh

💾 SYSTEM STATUS: Chapter 4 — COMPLETE | Job Market — IN PROGRESS | Coffee — LOW

About_Me.exe

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Hi, I'm Conny — a PhD candidate in Philosophy at the University of Pittsburgh, advised by Bob Batterman. My dissertation asks how scientists can rely on AI models they can't fully see inside of.

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📂 Research.dir

My interests are in general philosophy of science, the philosophy of AI, and the philosophy and history of mathematics. More specifically, I've been working on questions about AI models used in science, the issue of generalization in deep learning, and trust and values in science.

🗂️ Dissertation.dir

"DLMs in Science: Epistemic Legitimacy without Representation"

I argue that DLMs pose particular epistemic risks given their opacity. But we can defuse them by approaching them similar to scientific instruments: I argue that the epistemic legitimacy of DLMs is conferred by workflow-conferred robustness — sensitivity analysis, independent-dataset performance, benchmarking, theoretical constraint-checking, and systematic error detection — rather than by mechanistic transparency, developed through cases including AlphaFold, IDx-DR/LumineticsCore, and EFM.

My dissertation consists of four chapters: (1) The Legitimacy Gap, a three-level opacity taxonomy; (2) Against Representation, a critique of DLMs-as-representational-scientific-models; (3) A Diagnostic Taxonomy of DLM deployments; (4) Workflow-Conferred Legitimacy, my positive account.

🍎 Teaching.dir

[Add courses, teaching philosophy, and syllabi or evaluations here.]

📄 Writing_Sample.doc

"Deep Learning Models in Science: Reliability Without Representation"
My job-market paper — a single-arc defense of a reliability approach, anchored by AlphaFold. Available on request.

📇 CV.pdf

[CV coming soon.]

✉️ Contact.txt

cok22 [at] pitt [dot] edu