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.