Pseudonymous accounts, commonly found on prediction platforms and forums, provide individuals with the opportunity to share their forecasts and predictions without revealing their true identity. While this anonymity can protect the privacy and security of users, it also creates an environment ripe for manipulation. Pseudonymous accounts can present an inconsistent track record by making predictions that support opposing outcomes on different platforms or even within the same community.
One tactic employed by pseudonymous accounts to deceive followers is uncorrelated betting strategies - to place bets or predictions that cover multiple outcomes in an uncorrelated manner. By doing so, these accounts increase the probability of being correct on at least one prediction. For example, if an account predicts a AI will takeoff fast and slow on different platforms, they are essentially hedging their bets, ensuring that they can claim accuracy regardless of the actual outcome. This strategy allows them to maintain an illusion of expertise while minimizing the risk of being proven wrong. Even financial costs to betting can be compensated for given the grant and employment opportunities offered to successfull forecasters.
Another deceptive practice seen with pseudonymous accounts is selective disclosure. This means that individuals only reveal their identity when their predictions have been accurate or appear to be favorably aligned with the actual outcome. By withholding information about incorrect forecasts, these accounts create an inflated perception of their success rate and erode the reliability of their overall track record. Such selective disclosure can mislead followers into believing that the account possesses a higher level of accuracy than it genuinely does.
Relying on the track records of pseudonymous accounts can have significant consequences. Strategists and funders may make decisions based on inaccurate information, leading to impaired impact. Individuals seeking guidance on effective charities might be misled into making donation that are doomed to fail.
While pseudonymous accounts can provide a platform for diverse opinions and insights, it is crucial to approach any purported track records with skepticism. The ability to bet both ways, over multiple bets in uncorrelated ways, and selectively disclose favorable outcomes can create a distorted perception of accuracy.
I don't think the forecaster needs 2^10 accounts if they pick a set of problems with mutually correlated outcomes. For example, you can make two accounts for AI forecasting, and have one bet consistently more AI skeptical than the average and the other more AI doomy than the average. You could do more than 2, too, like very skeptical, skeptical, average, doomy, very doomy. One of them could end up with a good track record in AI forecasting.
If doing well across domains is rewarded much more than similar performance within a domain, it would be harder to get away with this (assuming problems across domains have relatively uncorrelated outcomes, but you could probably find sources of correlation across some domains, like government competence). But then someone could look only for easy questions across domains to build their track record. So, maybe there's a balance to strike. Also, rather than absolute performance across possibly different questions like the Brier score, you should measure performance relative to peers on each question and average that. Maybe something like relative returns on investment in prediction markets, with a large number of bets and across a large number of domains.