PhilArchive
open access
Is Design Inference Epistemically Special?
Design inferences from cosmic fine-tuning are routinely dismissed as epistemically defective -- a leap to an opaque cause where mechanistic explanation fails. Yet opacity alone has never been a disqualifying feature of rational inference. Scientific practice and artificial intelligence research both rely on black-box reasoning wherever explanatory power or strong evidential indicators compensate for incomplete transparency in causal mechanism. The fine-tuning inference, I argue, exploits precisely this structure: it earns provisional acceptance as an inference to the best explanation, not despite its opacity but through the same epistemic trade-offs that license reliance on empirically successful but interpretively opaque models elsewhere. Keith Lehrer’s distinction between acceptance and belief clarifies the doxastic attitude such an inference warrants. The conclusion is affirmative: design inference from fine-tuning is a defeasible but epistemically legitimate exercise of abductive reasoning.
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Is cosmic fine-tuning evidence against design? A Bayesian reply#694544
- Idealization and Structural Explanation in Physics#744957
- Inductive Risk, Understanding, and Opaque Machine Learning Models#103476
- A debunking dilemma for the fixity of the past#691299
- Debunking decreases mistaken causal inferences: A direct replication of Irving et al. (2022)#397123
Record · ID 691479
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive