If it averages several instances, with enough signal you could decompose a linear combination (e.g. average) of different patterns back out into its constituent parts.

A smarter system won’t just take the mean of the votes from different instances but rather discard outliers as invalid input (flagging repeat offenders to be ignored in the future) and use the median or mode of the remainder. The results should also be quantitized to avoid leaking details about sources or internal algorithms; only the larger trends need to be reported.

Of course you could always just keep the collected data private and only provide it to customers willing to pay $$$ for access, which handily limits instance operators’ ability to reverse-engineer the source of the data. And nothing prevents you from using separate instances for public and private data sets.