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” but pinning down causal effects rigorously is challenging. It’s not an accident that most heuristics about causality are negative—it’s easier to disprove causality than to prove it. As data science, statistics,
“Let us define plot. We have defined a story as a narrative of events arranged in their time-sequence. A plot is also a narrative of events, the emphasis falling on causality. ‘The king died and then the queen died,’ is a story. ‘The king died, and then the queen died of grie...
A Teasingly Suggestive "Parable"Speculations I: MinskyParticle InteractionsSpeculations II: ZuseSpeculations III: FredkinDigital MechanicsDM ProcessesCausalityPutting DM to the TestReversible ComputersQuantum Mechanical ComputersComputability and PhysicsTuring's Halting TheoremComputational IrreducibilityNoncomputability...
fullest sense of the word unique, they teach no lessons and lead to no conclusions.Distinguishing causes involves interpretation, and therefore value judgement:Interpretation in history is, as we saw in the last lecture, always bound up with value judgments, and causality is bound up with ...
The SARS outbreak was a prime example of the importance of contextualizing epidemiologically notable human behaviors in social, economic and cultural systems in order to decipher causality of an EID. Pandemic diseases in wild animals (epizootics) can also result in devastating impacts to a country’...
Another company that was deploying artificial intelligence followed the “respect every individual” principle by choosing models that were interpretable, so that the individual operators could understand the causality links between all of the recommendations from the models—and so...
Participants were further instructed to avoid any snacking and/or physical activity during that time window (see “Methods”). This ensured a null or low impact of potential confounders (snacks, physical activity) of morning alertness, as well as a high temporal causality between the predictors of...
A framework to infer causality on binary data using techniques in frequent pattern mining and estimation statistics. Given a set of individual vectors S={x} where x(i) is a realization value of binary variable i, the framework infers empirical causal rel
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