Originally Published - September 18, 2020.
Upshot One is a question & answer protocol built on Ethereum. It leverages a field of mechanism design called peer prediction to incentivize honest answers to questions.
The Problem
When we ask a question, we naturally expect a “correct” answer in return. For general queries on the Internet, and especially on blockchains, this has obviously proven to be a presumptuous expectation.
A number of services have arisen to make this expectation realistic, but they have their pitfalls. They tend to require trust (e.g. major journalism outlets, whitelisted authorities), have no guarantees on the quality of gathered information (e.g. most crowdsourced mediums such as Twitter polls or Amazon reviews), or are complex and economically expensive (e.g. dispute bonds and voting). To our knowledge, few popular approaches even define what a “quality answer” is in a way that most people would agree with.
The question remains: “How can we incentivize people to answer questions honestly?”
Peer Prediction
In previous approaches to answering questions, the quality of answers is assessed according to an ambiguous notion of credibility or expensive mechanisms. Peer prediction takes a ground-up approach to this question-answer dilemma by examining the structure of answers.
Peer prediction is a nascent field of mechanism design that finds new ways of eliciting quality answers, and peer prediction mechanisms are distinguished from one another by how they assess quality. Put simply, peer prediction mechanisms assess quality using a measure of mutual information — (a generalization of correlation) — the more honest answers are, the more mutual information they admit. In these settings, participants are compensated for answering questions. The mutual information between participants’ answers determines how well they’re compensated — participants who submit answers that admit high mutual information get paid more. This creates a clear incentive to answer questions and to answer them honestly.
Upshot One
Peer prediction is a means of identifying high-quality answers. With it, we can build a protocol that efficiently matches high-quality answers to questions: a question & answer protocol. We call that protocol Upshot One. This is how Upshot One works.
To efficiently identify participants who are most likely to have quality answers to questions, we randomly select participants using stake-weighted sortition. Then, committed answers are revealed and funneled into a new peer prediction mechanism called the Determinant-based Mutual Information Mechanism (DMI-Mechanism). Under weak assumptions, DMI-Mechanism is guaranteed to reward participants who submit informed and honest answers more than those that try to “cheat the system.”
Upshot One can even be used to answer subjective questions with no inherent notion of ground truth (e.g. “Do you like jazz?”). Disagreements on elicited answers to these or other questions can often be justified — even those with a notion of ground truth can be called into question (e.g. the temperature of a room can be questioned if the thermometer is not trusted, if the measurer didn’t effectively consider the variation of temperature throughout the room, etc.). This is why Upshot One implements subjectivocracy — histories of question-answer pairs can be forked into new histories (e.g. fork A could say the temperature is cold and fork B could say the temperature is warm). With subjectivocracy, multiple, equally valid realities can simultaneously exist, which is beneficial for some applications (e.g. content curation). Furthermore, subjectivocracy serves as a final line of defense against an attack — realities that have been successfully manipulated can simply be forked away.
Upshot One is built as a set of smart contracts on the Ethereum blockchain. Anyone can ask questions, anyone can supply answers and be rewarded for them, and anyone can subscribe to the ensuing feed of matched questions and answers.
Applications
Get Involved
There will be much more coming out in the coming weeks and months. Reach out if you’d like to get involved in the community! In the meantime, check out our website, read the whitepaper and follow us on Twitter.
Acknowledgements to my co-founder Kenny Peluso for collaboration on this post and the whitepaper.