2021 HPCC Systems Community Virtual Summit: The Causality Analytics Toolkit for HPCC Systems

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The Causality Analytics Toolkit for HPCC Systems, Roger Dev, LexisNexis Risk Solutions Group

Causal Reasoning is at the heart of most human thought and action, yet has only recently been formalized as a mathematical and scientific field of study. It is hard to conceive of achieving a true AI without such a capability. Although the science of Causality has not advanced to the threshold of AI, it can unlock capabilities that are beyond the realm of statistical observation. Current Machine Learning methods assess observational patterns, and learn to replicate the results of patterns previously detected. They make no effort to disentangle true causal effects from observed correlation. They lack the ability to respond to changes in the scenarios that generated the data, or to predict the effect of new actions on the outcome. Causal Science provides a path toward a deeper understanding of our data. It defines mechanisms that can separate causal influences from spurious correlation and infer causal effects from observational data. As these techniques evolve, they stand to
revolutionize our understanding and uses of data. Causality 2021 is an HPCC Systems research and development program. The goal is to increase our understanding of the latest causal algorithms, assess and challenge the current state-of-the art, and develop a Causality Toolkit for HPCC Systems Platform. This project encompasses all three levels of the "Ladder of Causality": “Seeing”, “Doing”, and “Imagining”, as well as Causal Model Validation, and Causal Discovery.

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