OpenBlock Labs STIP Efficacy + Sybil Analysis (2/24)

First, to the work @paulsengh is sharing - well done. As someone with a history of working directly on sybil detection, I can say this is a high quality analysis. I especially appreciate the consideration to how they preference avoiding false positives in a sensitivity vs specificity tradeoff.

Now to the point of “What does this mean?”

I became bearish on proof of individual humanity during my time working on the problem. We look at sybil as in input metric that - if treated - can lead to better outcomes. @bflynn points out that there are specific situations where this is important.

This is almost accurate. imho it does not go far enough.

A sybil-free round is a requirement of running a mathematically optimal quadratic funding round. It is NOT a requirement of that QF round resulting in a better society. Nor is it the only assumption the mechanism must contend with. What we are actually trying to do is optimally allocate capitol to encourage Arbitrum to continue spearheading the evolution of decentralized technology and governance.

I don’t fully agree with the premise of this question. It is not a binary. I agree that sybil accounts paying enough to cover their acquisition is an intriguing concept.

What we don’t have here is the understanding of RETENTION based on a shared understanding of what qualifies as an engaged user at both the protocol and network levels. Luckily, our grants to Open Source Observer and Helika Gaming are just starting to give us insights here. (PSST LTIPP!)

So what does this mean?

@bflynn is taking the approach that we will likely learn and Boost is in a strong position to iteratively improve. The opposite angle would be to argue that the opportunity cost isn’t worth it.

To understand better, imagine the extreme of case: All of Boost was 1 sybil actor (this isn’t close to true - just a thought experiment)

In that case, out of $1 million spent on incentives by the DAO, 1 person was acquired by the network - this person likely wont be an engaged user without further incentives. However, it cost that person about $1 million in transaction fees to do this. We just moved $1 million from the treasury to the treasury.

That example is little facecious, but it shows how important it is to think about the acquisition cost of sybils vs the acquisition of real - potentially engaged - users.

We need the data to understand engagement - It’s been indexed and is now ready to analzye

Maybe we should drop an analysis into the Open Data Community Permisionless suggestion box grants to look into this?