Causality
| Criteria | 📈 Causal Inference | 🤖 Causal AI |
|---|---|---|
| 🎯 Core Goal | Estimate treatment or policy effects from data | Enable AI to reason, simulate, and plan with causality |
| 🌍 Scope | Focused on statistical estimation from real-world data | Broad, includes CI + causal reasoning in intelligent agents |
| 🛠️ Methods | Matching, IVs, DiD, DAGs, do-calculus | SCMs, causal discovery, RL, counterfactuals, representation learning |
| 🗂️ Data | EHRs, trials, economic panels — structured/tabular | Images, text, sensor logs, simulations — multimodal |
| 🧰 Tools | DoWhy, EconML, Stata, Stan, CausalML |
Pyro, CausalBench, Causal Transformers, RL libraries |
| 🧠 Theory | Pearl’s SCMs, Rubin’s Potential Outcomes | Extends CI with planning, control theory, generative modeling |
| 🧪 Use Cases | Drug effects, A/B testing, public health impact | Clinical AI agents, counterfactual explainers, planning under uncertainty |
| 🚀 Trends | Automated causal discovery, scalable estimation | Causal LLMs, structure-aware agents, causal generalization in foundation models |
| 👥 Audience | Statisticians, epidemiologists, applied economists | ML/AI engineers, decision scientists, generative modeling researchers |
| 🧭 Philosophy | “Understand causes to intervene wisely” | “Use causality to empower robust, generalizable, explainable intelligence” |
| 📚 References | Elements of Causal Inference: Foundations and Learning Algorithms Jonas Peters, Dominik Janzing, and Bernhard Schölkopf (2017) | Causal AI Robert Osazuwa Ness (2025) |
🏥 Healthcare-Focused Examples #
| Scenario | Causal Inference Approach | Causal AI Application |
|---|---|---|
| Does a drug reduce mortality? | Use propensity score matching on EHRs to estimate treatment effect | Simulate outcomes, explain counterfactuals, and adapt AI decision policy |
| Which patients benefit from a treatment? | Estimate HTEs using stratification or causal forests | Personalized planning agent using causal graphs and reinforcement learning |
| What if surgery is delayed? | Model counterfactuals using SCM or time-series IVs | Temporal causal simulation to guide optimal intervention timing |