What Is Right with ‘Bayes Net Methods’ and What Is Wrong with ‘Hunting Causes and Using Them’?

Nancy Cartwright's recent criticisms of efforts and methods to obtain causal information from sample data using automated search are considered. In addition to reviewing that effort, this paper argues that almost all of her criticisms are false and rest on misreading, overgeneralization, or neglect of the relevant literature. – 1. Introduction; – 2. Cartwright's Claims, and Their Errors; – 3. Problems of Causal Inference; – 4. Context; – 5. Graphical Causal Models and Markov Properties; – 6. Interventions, Experiments, and Randomization; – 7. Search for Causal Explanations; 7.1 The PC algorithm; 7.2 The Fast Causal Inference algorithm; 7.3 ION and iMAGES; 7.4 Build pure clusters and MimBuild; 7.5 Measurement error and mixed methods; 7.6 Time series; 7.7 LiNGAM; 8. Cartwright's Objections Again; 9. Conclusion. M.-M. V.