Rebecca Kossnick

Wiki Contributions


Hi there! A few comments

Re: the comparison to good judgement: good point. I added an update in the text and edited the wording since we didn't study relative question difficulty or time horizon.

Re: really fun vs addictive: we hope using Forecast brings people joy, helps them think and write more rationally, and helps improve conversations between people on contentious topics. At our current scale, this is something we mostly measure qualitatively. If/as we scale, we hope to understand how people experience Forecast more rigorously.

Re: scale and data: appreciate the feedback. This is something that is of utmost concern for us if/as we scale.

Thank you for using the app and for all your feedback. This may be hard to believe, but we're actually working on fixes for every issue you mentioned except the long time horizons! In particular, we have the following scoped into our current sprint: 1) improve our in-app economy management (i.e. so there's not so many inflationary points), 2) increasing the max share limit, and 3) updating the leaderboard to be less swing-y.

The reason the leaderboard varies so drastically is that we use current liquidation value (how much you would get if you tried to sell your whole position this minute) rather than #shares X market price to calculate the leaderboard. As a result, if you have a big, market-moving position, you don't get the credit for it until the question closes in your favor. We've been using this value because we thought it would be a more accurate representation of your position in the market. It turns out it just confuses people and penalizes 'value investing'. Whoops!

We don't have a good answer on incentivizing long time horizon questions. We've thought about giving points bonuses or possibly some form of dividend for holding questions for a long time. We're very open to feedback on this one.

Hey Ruby, appreciate your feedback. We hear you on the slider. We were going for broader appeal with the website, which is why we went with words (e.g. 'likely', 'definitely') instead of probabilities, but this definitely sacrifices both precision and accuracy. The app has a more advanced buying flow which shows the probability and the number of shares your purchasing.

In term of how this relates to Facebook overall: prediction markets are indeed a niche interest. There is, however, much broader interest in asking questions about the future, making predictions, and debating what will happen. This is the interest that we hope Forecast can help serve. We think there will ultimately be a relatively small group of people who are highly motivated to make forecasts, write detailed analyses and moderate raw submissions into forecastable questions. But if we can help a larger audience find the work that the smaller group is doing at the right moment (for example, when they are searching for information on an uncertain event), we think that could be quite impactful.

As a micro-example: because users get points when other users support their analyses, there's a strong incentive to break news with reasoned commentary into Forecast (being first to add an update makes you more likely to get the supports*). This is still a low-volume behavior, but as the community scales, we can imagine the this content forming a feed of news** that would be valuable to a much broader audience beyond the community working to make quality forecasts.

*there's some obvious issues with this at scale, but right now no one's exploiting this!

**possibly this could be called a newsfeed :) 

Hi there! We're particularly focused on how prediction markets can improve conversation. We think the overall crowd forecasts themselves are really cool, but for Forecast, they serve primarily as a a frame to guide discussions.

I mentioned this above, but just to expand a bit: with think the combination of the prediction market as a game mechanic + the direct incentive to write quality reasoning + the lack of real money on the line has helped create an environment that is conducive to reasoned discussion. I would guess, without having data, that these factors have also driven that the predictive accuracy in Forecast to be slightly (or significantly?) worse compared with other platforms. Because our goal is better conversation, we're ok with this tradeoff.

It remains to be seen if and how these factors will scale if more people join the platform. As far as I know, we're the only platform exploring precisely this combination of attributes.