Causal Provenance and the Epistemology of Artificial Minds: Construct Validity, Inferential Non-Transferability, and Measurement Dependence in Artificial-Mind Attribution
Marcelo Maximiliano Filippin
Zenodo (CERN European Organization for Nuclear Research) October 5, 2026 preprint DOI: 10.5281/zenodo.23167621 (opens in new tab)
Study at a glance
AI-extracted from the abstract| Characteristics | Theoretical or philosophical paper |
|---|---|
| Topics | Addiction |
| Key points | Argues that indicators of artificial mental constructs cannot be trusted when the evaluated system has been exposed to descriptions of those constructs and their detection methods, since an observed indicator then does not identify its own causal source. Proposes a three-tier framework combining causal versus epistemic provenance, a construct-validity standard, and a principle of "inferential non-transferability", operationalised by a five-stage provenance protocol. |
Abstract
Artificial systems are increasingly evaluated with behavioural, computational, and mechanistic indicators of cognitive constructs such as metacognition, self-modelling, global availability, and potentially consciousness. A problem arises when the evaluated system has itself been exposed, in training or deployment, to descriptions of those constructs, to their proposed indicators, and to the evaluative practices used to detect them. In that case an observed indicator does not identify its own causal source. This paper offers a framework for artificial-mind attribution built on three ideas: a distinction between causal and epistemic provenance, a construct-validity standard for moving from mechanism to construct, and a principle of inferential non-transferability that forbids carrying evidence from one computational unit to another without an explicit invariance argument. The framework is organised as a three-tier architecture and operationalised, at its final tier, by a five-stage provenance protocol. A worked example shows the protocol applied to a hypothetical metacognition claim, and a partial reading of published work on language-model introspection shows where such evidence currently stops. The aim is neither to decide consciousness by counting indicators nor to disqualify systems for having met human concepts, but to state the conditions under which evidence for an artificial mental construct can be attributed to the construct itself.
Comparable studies
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| Ayahuasca’s entwined efficacy: An ethnographic study of ritual healing from ‘addiction’ | 2017 | Theoretical or philosophical paper | |
| Hypotheses Regarding the Mechanisms of Ayahuasca in the Treatment of Addictions | 2012 | Theoretical or philosophical paper | |
| Biosynthesis of an Anti-Addiction Agent from the Iboga Plant. | 2019 | Theoretical or philosophical paper |