We study policy advice by several experts with noisy private information and biased preferences. We highlight a trade-off between the truthfulness of the information revealed by each expert and the number of signals from different experts that can be aggregated to reduce noise. Contrary to models with perfectly informed experts, because of this trade-off, full revelation of information is never possible. However, almost fully efficient information extraction can be obtained in two cases. First, there is an equilibrium in which the outcome converges to the first best benchmark with no asymmetric information as we increase the precision the experts’ signals. Second, the inefficiency in communication also converges to zero as the number of experts increases, even when the residual noise in the experts’ private signals is large and all the experts have significant and similar (but not necessarily identical) biases.