Curation by Prediction Market Proposal

This is a proposal for a change in how Steem allocates curation rewards. Instead of rewarding voting, we propose to reward accurate predictions of future payouts.

The problem

Curation is a difficult job, but someone has to do it. The problem we face with the existing curation reward system is that there is a feedback loop whereby upvoting rewards the upvoter. This feedback loop is made worse by bandwagon effect and ultimately leads to people taking actions to earn rewards that do not produce quality curation as a side effect.

An upvote is an action that is currently rewarded to some degree no matter what. It is something that can be done without thought and even simplistic automation can return a modest profit. The existing algorithm rewards "speed" over "quality" of curation. It rewards "large voters" more than "small voters". In other words, paying people for upvoting is not really paying people for the information we want.

You get what you pay for

Since we get what we pay for, then we must make sure we pay for what we want. In this case what we want to know is the value of a post. A value of a post is a function of the number and quality of the individuals who eventually up or down vote a post.

Rather than rewarding those who upvote, we should reward those who accurately predict the outcome of voting. Armed with this prediction, websites such as steemit.com can filter the low quality submissions from the high quality submissions as early as possible.

We want people to tell us what posts are valuable to the community. Then we want the community to confirm the prediction with their votes.

Prediction Market

Under the proposed system we have two classes of people, paid curators and voters. The job of curation would be entirely separate and independent from the act of voting. Voting will no longer be rewarded. The only people who will qualify for curation rewards will be those who make the best predictions on the future payout.

When a curator sees a quality post they can press a button that will open the curation dialog. This dialog will allow them to quickly enter and submit the future payout value. It may optionally show a chart with existing predictions.

When a post receives its payout, all curators who predicted a value between 90% and 100% of the the final payout qualify for a weighted share in the curation reward. This creates a price-is-right rule that discourages people from over-predicting.

The weighting algorithm used to divide the curation rewards needs to factor in the following information:

• Steem Power of individual making the prediction (prevent sybil attacks)
• Existing Predictions (copying someone else's prediction should not be rewarded)
• Time of Prediction (late predictions are no prediction at all)
• Reputation of Predictor

Proposed Weighting Algorithm

let SP = Steem Power of Predictor 
let P  = Prediction of Predictor 
let EP = Closest Existing Prediction
let CP = Closeness Penalty
let N  = the number of predictions made by predictor + 1
let R  = the number of times predictor was within 10%  
let RP = Reputation Penalty = (R/N)^3
CP = (1 - abs(EP-P) / EP)^2

let Weight  =  RP * SP * CP 

Once the weight of each successful predictor has been calculated, the predictor would receive a pro-rata share in the curation rewards for that post.

Justification for Math

All predictions must be entered within 30 minutes of posting. This encourages timely behavior with minimal ability to profit from knowledge of existing votes. I would suggest preventing voting during the curation period, but that would discourage readers from voting in the moment.

The closeness penalty heavily biases rewards toward the first person to stake out a position on the reward scale. This means that voting the same as someone before you will get you no reward. Voting 90% the same will get you just 1% of your potential reward.

The reputation penalty is designed to filter out sybil attacks where by small accounts vote in increments of 10% to ensure they win and force everyone else to suffer a closeness penalty. Ballot stuffing will result in a much lower predictive reputation than someone who uses human intuition to vote.

The Steem Power factor is designed to discourage sybil attacks and encourage predictions by whales. This also encourages predictors to acquire more Steem Power to maximize their earning potential. A side effect is that they are risking more so they can earn more. A whale that sets up a prediction bot will likely have very low prediction reputation.

Predicted Outcome

I predict that this algorithm will result in more opportunities for smaller players to earn larger curation rewards. The value that the blockchain will extract from the curators will be much greater than what can be extracted from a single upvote. By improving the quality of information and curation we improve the value Steem can bring to readers and voters.

This system will also gamify curation in a way that will become addictive and maximize the number of people reading all new content submitted to the network. This in turn should maximize the reach each submission receives.

Those who make a prediction also have financial incentive to see the prediction come true. If you see a great article and predict it will receive a high payout, then it is in your interest to make sure that many people see and vote on the article. This means sharing it via your social media.

There is much less incentive to make predictions on low-value content. The highest rewards go to the first person to identify high value content and accurately predict its value. This should give Steem the most benefit possible from the rewards being distributed.