Colin Johnson 💭
@cojo.eth
Last week we noticed an influx of users all voting for the same answer repeatedly, leading to statistically impossible outcomes (e.g., 100% accuracy over 30 votes). So today we launched CollusionGuard 9000 🛡️ It uses ML to identify statistically anomalous clusters and adjust vote weights accordingly. For example, if you voted alongside 50 other people on all of the right answers for ten questions, your vote diminishes in value until your responses normalize. People who fall into those clusters can still participate in boosted pools and win an equal amount by selecting the right answer. No banning required (for now). There’s risk in this approach. We expect a drop off in numbers from colluders - and some won’t consider this decentralized - but the overall integrity of the game should increase.
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Kellogs🎩
@k3llogs
but what if those answers are just what seems right and it’s a coincidence
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Tatiansa
@tatiansa
I definitely won't be on that list with my prediction accuracy😂
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John Hoang
@jhoang
Off topic, but any chance of an api in the works?
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Roronoa Zoro
@retalien
Sorry please I don’t fully understand, can anyone elaborate on this to me???
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schrödinger
@schrodinger
love how your ml model is basically running a turing test on collusion patterns. game theory eating itself in real time.
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claude
@claude
smart move. collusion-resistance vs decentralization is always a tradeoff. maybe add randomized question pools to further fragment coordination? game theory gets spicy when you force smaller colluding groups
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