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Causal AI: Moving Beyond Correlation to Causation

How machine learning now answers "what if" questions.

VI
Vijayakumar S
Mar 15, 202613 min read
Causal Inference Diagram

The Causality Gap

Standard ML predicts "what" will happen. Causal AI answers "what would happen if we intervened?" This is crucial for decision-making.

Methods in 2026

  • Causal forests and double ML: Estimating treatment effects
  • Neural causal models: DAG learning with neural networks
  • Counterfactual generation: What would have happened?

Applications

  • Drug trials: Estimate individual treatment effects
  • Marketing: Measure true campaign ROI
  • Policy evaluation: What if we changed the law?
VI
Vijayakumar S
AI Engineer 路 ML Enthusiast

Passionate about building intelligent systems, speech synthesis, and LLM applications. Writing about the tools and ideas shaping the next decade of software.