Human Guided Causal Discovery

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Presented by

Tamara Stemberga, Head of Data Science, causaLens

About this talk

Watch our Human-Guided Causal Discovery webinar, where we unveil our unique human-machine approach where domain experts & scientists/engineers collaborate to discover causal graphs. Current AI approaches cannot be trusted for decision-making in the enterprise. They rely on statistical correlations that are often spurious and can’t be explained. The causaLens Causal AI platform delivers unparalleled explainability & trustworthiness and is the only approach that works for AI-powered decision making. Discovering causal diagrams is the first & fundamental step to achieving this. The talk covers: - Why causal graphs are key to building Trustworthy AI - An overview of the existing methods for Causal Discovery and their limitations - A live demo of our Human-Guided Causal Discovery

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causaLens is the pioneer of Causal AI—a giant leap in machine intelligence. Today’s machine learning algorithms extract correlations from data and predict outcomes based on patterns in past data. Correlations are useful for making predictions, but they’re of little use for decisions. Causal AI goes beyond predictions by understanding the actual causes behind an outcome and quantifying the impact of different interventions. It is the only form of machine intelligence that can answer “Why?”. causaLens builds Causal AI-powered products that empower all users to make superior decisions and drive business value. Leading organisations across a wide range of industries trust causaLens with their most important decisions.