We study policy advice by several experts with
information and biased preferences. We
highlight a trade-off between the truthfulness of the information
each expert and the number of signals from different experts that can
to reduce noise. Contrary to models with
perfectly informed experts, because of this trade-off, full revelation
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
asymmetric information as we increase the precision the experts'
signals. Second, the inefficiency in
also converges to zero as the number of experts increases, even when
residual noise in the experts' private signals is large and all the
have significant and similar (but not necessarily identical) biases.