Abstract
Causal reasoning is an aspect of learning, reasoning, and decision-making that involves the cognitive ability to discover relationships between causal relata, learn and understand these causal relationships, and make use of this causal knowledge in prediction, explanation, decision-making, and reasoning in terms of counterfactuals. Can we fully automate causal reasoning? One might feel inclined, on the basis of certain groundbreaking advances in causal epistemology, to reply in the affirmative. The aim of this paper is to demonstrate that one still has good skeptical grounds for resisting any conclusions in favour of the automation of causal reasoning. If by causal reasoning is meant the entirety of the process through which we discover causal relationships and make use of this knowledge in prediction, explanation, decision-making, and reasoning in terms of counterfactuals, then one relies besides on tacit knowledge, as might be constituted by or derived from the epistemic faculty virtues and abilities of the causal reasoner, the value systems and character traits of the causal reasoner, the implicit knowledge base available to the causal reasoner, and the habits that sustain our causal reasoning practices. While certain aspects of causal reasoning may be axiomatized and formalized and algorithms may be implemented to approximate causal reasoning, one has to remain skeptical about whether causal reasoning may be fully automated. This demonstration will involve an engagement with Meno’s Paradox.
Highlights
Are we in a position to fully automate causal reasoning? Given recent groundbreaking advances in causal epistemology, one might be tempted to reply in the affirmative
Before we commence our critical examination of the automation question, an acknowledgment of the state-of-the-art in causal epistemology will first be in order
Suppose further that we have in place a sufficiently advanced computational method that is guided by the state-of-the-art in philosophical theory and will allow us to infer causal relationships relative to this set of problem-free data
Summary
Given recent groundbreaking advances in causal epistemology, one might be tempted to reply in the affirmative. Are we in a position to fully automate causal reasoning? In this paper, it will be demonstrated how, notwithstanding a number of significant philosophical and computational developments, one still has good skeptical grounds for resisting any conclusions in favour of the automation of causal reasoning. Our critical examination of the central opening question (hereafter: the automation question) will rely on a delineation of these philosophical and computational advances in causal epistemology, a careful articulation of the automation question, Meno’s Paradox and Polanyi’s treatment of it, and
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