Bayesian Nets and Causality

Bayesian nets are widely used in artificial intelligence as a calculus for casual reasoning, enabling machines to make predictions, perform diagnoses, take decisions and even to discover casual relationships. But many philosophers have criticized and ultimately rejected the central assumption on which such work is based-the causal Markov Condition. So should Bayesian nets be abandoned? What explains their success in artificial intelligence?