  We formulate a new variant of the private information retrieval (PIR) problem
where the user is pliable, i.e., interested in any message from a desired
subset of the available dataset, denoted as pliable private information
retrieval (PPIR). We consider a setup where a dataset consisting of $f$
messages is replicated in $n$ noncolluding databases and classified into
$\Gamma$ classes. For this setup, the user wishes to retrieve any $\lambda\geq
1$ messages from multiple desired classes, i.e., $\eta\geq 1$, while revealing
no information about the identity of the desired classes to the databases. We
term this problem multi-message PPIR (M-PPIR) and introduce the single-message
PPIR (PPIR) problem as an elementary special case of M-PPIR. We first derive
converse bounds on the M-PPIR rate, which is defined as the ratio of the
desired amount of information and the total amount of downloaded information,
followed by the corresponding achievable schemes. As a result, we show that the
PPIR capacity, i.e., the maximum achievable PPIR rate, for $n$ noncolluding
databases matches the capacity of PIR with $n$ databases and $\Gamma$ messages.
Thus, enabling flexibility, i.e., pliability, where privacy is only guaranteed
for classes, but not for messages as in classical PIR, allows to trade-off
privacy versus download rate. A similar insight is shown to hold for the
general case of M-PPIR.
