Curated blind auction prediction markets and a reputation system as an alternative to editorial review in news publication.

If one were to build an open platform to compete with news media rather than social or blogging media, they would need some sort of accountability/​quality control mechanism to mirror the role of editorial review at prestigious news platforms.

The best tool for aggregating information that we have devised is markets. This is especially the case in open systems. The biggest risk to a well-functioning market is collusion. The second major problem with prediction markets for information is that bettors can become more concerned with predicting what people think the truth is rather than predicting the actual truth. Any mechanism that was designed to employ markets in the place of editorial review would need to guard against these failings. With this in mind I propose this system:

  1. A reporter with information on a climate event in Costa Rica writes an article and publishes it to the platform. They must stake a certain TBD amount of money on this article.

  2. The article is published without editorial review (unlike how news media currently works).

  3. Prospective fact checkers (post editorial reviewers) also stake money and state their specialist topics. Some of those that listed Costa Rican current affairs or climate as a topic are randomly chosen from the available pool of people. They are each given guidelines on how to judge an article and use these guidelines to give the article a trust score without colluding among themselves as they don’t who else’s been asked to fact check. The article and the guidelines together likely represent the only Schelling point the fact checkers can converge on as the position of the market is unknown prior to settlement. Information about any consensus that might exist outside the truth is unknown. A fact checking assignment is like jury duty. Some of your stake is slashed if you renege on giving a score for a given article in your specialty. This requirement along with random selection should minimise any collusion.

  4. The writer’s payout is determined by the score the fact checkers give him/​her. The fact checkers’ payouts are determined by how close they are to the average score from the group. Everyone’s respective rep scores are also updated. Those that drop below a certain trust score will not have their articles listed on the platform or be chosen for post editorial review. Articles from the best performers will be amplified on the platform, minimising the chances of readers being supplied erroneous information.

Would be interested to hear people’s thoughts on this system? One worry I have is that after some time people will be armed with prior probabilty data and will simply strategically pick the high probabilty outcome without doing any fact checking. This could be mitigated by minimising the amount of articles a fact checker gets, leading them to take the utmost care with the ones they are given.

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