  We present alignment problems in current forecasting platforms, such as Good
Judgment Open, CSET-Foretell or Metaculus. We classify those problems as either
reward specification problems or principal-agent problems, and we propose
solutions. For instance, the scoring rule used by Good Judgment Open is not
proper, and Metaculus tournaments disincentivize sharing information and
incentivize distorting one's true probabilities to maximize the chances of
placing in the top few positions which earn a monetary reward. We also point
out some partial similarities between the problem of aligning forecasters and
the problem of aligning artificial intelligence systems.
