Interweaving Incentives With Foresight and Usefulness
Perhaps the most complex puzzle in crafting a new and untested social platform is building balanced, attractive and inherently valuable incentives for each stakeholder. Not only must the incentives sustain growth and drive adoption, they must function within the system in ways that contribute to the system’s fundamental purpose. In the case of Hypothesis, those incentives must drive users to make predictions and interact with content. By extension, they must also drive publishers to shift the way they approach creating content toward more constructive, truth-oriented ends.
For a user, the core incentive is expressed through a new, proprietary rating metric called Foresight. Foresight tracks prediction performance, with its evaluation taking into account both a user’s correctness and the correctness of their peers on a given prediction, as well as the usefulness of the content they created, shared and interacted with. Inspired by a modified version of the Elo rating system, over time this number will grow and shrink, eventually giving users meaningful insight into their own informedness and intuition. This rating-based incentive can be strengthened through its adoption by third parties as a metric by which an individual’s reputation is quantified. For example, a user might incorporate their score into their Linkedin profile to attract prospective job opportunities, or into their Tinder profile to efficiently communicate a difficult-to-define characteristic.
Content creators and publishers also have a rating metric, called Usefulness. Usefulness ratings are evaluated based on the prediction performance of the users who interact with their content, and are not influenced directly by the ratings of competing providers. Over time, this rating will also grow and shrink, and could serve as an indicator of the quality of information that providers publish. While we cannot go as far to say that a low rating will always be correlated with a low quality of information (or vice-versa), Usefulness will nevertheless prove valuable in better understanding the effect media has on shaping our worldviews. Ideally, it will motivate publishers to produce information with higher standards of objectivity.
This interweaving of incentives, where users have a vested interest in interacting meaningfully with the most useful information, defines the inherent value of Hypothesis. The system’s design depends on its stakeholders’ dedication to constructive interaction, and so itself is incentivized to be highly transparent and provide an exceptional user experience.
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