Hypothesis
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Platform Limitations
The limitations of Hypothesis are not necessarily technological in nature, but instead arise from the extent to which the platform can successfully make inroads toward solving the variety of problems facing digital media in the 2021 and beyond, and whether adequate attention is being focused on the correct problems, or if the underlying assumptions behind assigning value to said problems are missing the mark. Due to the relative novelty of Hypothesis’ combined feature set, it is difficult to discern whether any single feature is being implemented in such a way that it truly works toward the larger goals of the platform. Should more attention be spent on building a new revenue stream for content creators, like platforms such as Substack and Twitch have so far been successful in implementing? What about the heretofore inadequate job that social media platforms have done at managing the proliferation of fake news and hate speech? Does a critical mass of internet users truly care enough about where they get their information such that they are willing to take a chance on an unproven—and more intellectually-demanding—application? What defines a "Critical mass" for Hypothesis?
On their own, the incentives incorporated into Hypothesis may be valid, but it is in their interweaving that they become fundamentally transformed in their cumulative potential efficacy. Whether such a transformation leads to an overall strengthening or weakening of that efficacy remains to be seen. The limited input that Hypothesis has been constructed to receive—questions, resolution choices, Context, comments and likes—may not be enough to accurately represent the accountability, Usefulness and intuition of its stakeholders. Conversely, while we intend for Hypothesis’ formulas to be grounded in truth, the scientific answer to whether or not they actually are may not matter, insofar that it is ultimately up to users whether or not they trust that those formulas adequately represent the things they are meant to. Whether Hypothesis is structured in a way that it leads to such trust can only be proven by its stakeholders.
More specifically regarding content creators, we are faced with the question of whether currently-popular digital publishing business models will interfere with Hypothesis’ efforts to implement an equitable system of accountability and Usefulness. Those publications that restrict access to their content using paywalls may be negatively impacted by Hypothesis rating formulas due to the possibility that users will avoid interacting with paywalled content in favor of information that is freely accessible. Despite Usefulness being calculated roughly based on proportional engagement as opposed to aggregate engagement (meaning, it should not matter how many correctly-predicting users engaged with your content, rather the proportion of correctly-predicting users who engaged with your content), paywallers may still experience Usefulness growth that is disproportionately correlated with whether users are paying customers instead of whether users perceive their content as useful. One could argue that access to a publisher’s content should factor into their overall Usefulness, but nevertheless, this stance may lead to friction between Hypothesis and the increasing number of publishers who rely on subscriptions to earn revenue.
This problem also raises the question of the extent to which Hypothesis should foster content-creation incentive mechanisms such as in-app paywalling, per-creator subscriptions and revenue-sharing. Will institutional stakeholders see value in such a system? Would these new incentives help or hurt Hypothesis’ efforts toward achieving its larger goal of an information economy built on truth and accountability? These are all considerations that must be assessed while building both short and long-term roadmaps for Hypothesis.
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