📋Quality assurance
Before giving more explanations about quality assurance, it is necessary to explain what is "quality data". Good quality data is data that meets the criteria set by the company and approved by a sufficient subset of the community. In our system, we consider that a data is valid if it meets the Schelling point. For example, if all checkers listening to an audio recording agree without consulting each other that there is background noise, we simply consider that there is background noise in the recording. If the company wanted such noise, the data is considered valid (it matches the company expectations), otherwise it is invalid.
Now that we have clarified the concepts of quality and validity, let's see how users are incentivized to produce good quality data. Each time a user performs an action (production or vote) he locks in a deposit (a small amount of tokens).
When a producer's data is validated by the checkers, he earns some tokens. In the opposite case, he earns nothing and loses his deposit. The deposit is a structural incentive system for producers and checkers we found to ensure that people will do a good job, even if it is insignificant compared to the gains. This set-up has deep roots in DeFi and blockchain protocols in general and is proven to work.
For the checkers, the mechanism is slightly more complex and relies on a consensus calculation between the voters. Basically, the checkers who voted against the majority are slashed. For example: four checkers indicate hearing an elderly person in an audio recording and only one checker indicates hearing a child's voice. In such a configuration, the four checkers are paid while the last one is slashed. The page Consensus calculation gives more detail about this.
On Ta-da, companies only pay for valid data that meets their criteria. So how do we do it? Thanks to the slashing system described above. A producer's deposit is big enough to pay the checkers. This way, when a data is invalidated by the checkers, they are paid only by the producer's deposit rather than by the company's money. Thus, an invalidated data doesn’t cost anything to the company.
When the checkers validate the produced data, the producer and the checkers are paid with the company money.
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