Philosophy Compass 13 (1):e12470 (2018)

David Danks
Carnegie Mellon University
Daniel Malinsky
Carnegie Mellon University
Many investigations into the world, including philosophical ones, aim to discover causal knowledge, and many experimental methods have been developed to assist in causal discovery. More recently, algorithms have emerged that can also learn causal structure from purely or mostly observational data, as well as experimental data. These methods have started to be applied in various philosophical contexts, such as debates about our concepts of free will and determinism. This paper provides a “user's guide” to these methods, though not in the sense of specifying exact button presses in a software package. Instead, we explain the larger “pipeline” within which these methods are used and discuss key steps in moving from initial research idea to validated causal structure.
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DOI 10.1111/phc3.12470
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References found in this work BETA

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