Unboxing the Concepts in Newcomb’s Paradox: Causation, Prediction, Decision in Causal Knowledge Patterns

In Nozick’s rendition of the decision situation given in Newcomb’s Paradox dominance and the principle of maximum expected utility recommend different strategies. While evidential decision theory (EDT) seems to be split over which principle to apply and how to interpret the principles in the first place, causal decision theory (CDT) seems to go for the solution recommended by dominance (“two-boxing”). As a reply to the CDT proposal by Wolfgang Spohn (2012), who opts for “one-boxing” by employing reflexive decision graphs, I will draw on the framework of causal knowledge patterns, i.e., Bayes net causal models (cf. e.g. Pearl 2009), augmented by non-causal knowledge (epistemic contours), to finally arrive at “one-boxing” – more intuitively and more closely to what actually is in Nozick’s story. This proposal allows the careful re-examination of all relevant concepts in the original story – it prompts a re-evaluation of how prediction may be analyzed, philosophically and formally, and what the decision-maker’s conceptualization of the situation might look like