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RE: Steemit Update: HF21 Testnet, SPS, EIP, Rewards API, SMTs!
This is all just narative. Simulate it with some old data and see how the incentives pan out. The only real incentives the EIP creates favor the bid bot economy. It could be easily fixed I feel by making down votes hit curation harder than the author.
That sort of simulation is entirely worthless because it doesn't account for changing behavior, which is the entire point of it.
Downvotes absolutely should hit the author (as well as the other curators, but not to the extent of favoring the author). The fundamental goal of both upvotes and downvotes is to pay authors in accordance with a stake-weighted consensus of value contributed. Downvoters are contributing their opinion into that consensus process that the payout to the author is too high.
That method shows us exactly what behaviour will be first to be incentified to be changed, and you can start reasoning from that. People don't change behaviour because of eloquent narrative about incentives meant to change their behaviour, they change behaviour because of actual stimuli acting on their existing behaviour.
That same method could have warned us about the disaster that was HF20. I feel it quite worrying, especially after our HF20 that anyone still could consider real-data simulations "useless". They aren't just usefull, they are essential to preventing what is perfectly predictable.
At best it is of minimal value in these situations.
Take downvotes for example. A number I saw recently was 0.008% of votes being downvotes, essentially zero. Running a simulation over that data will tell you nothing about downvotes because (for practical purposes) no one uses them. Only after the cost structure attached to downvotes changes will, possibly, the usage of downvotes change, and nothing in the historical data will tell us how it will change or how much.
HF20 is a very different type of situation. Very little of HF20 was intended to or could reasonably be expected to change behavior via incentives on a widespread scale. What it did do is block certain actions (spamming mostly) which meant that it wouldn't even be possible to simulate in that way, because many of the previous recorded actions in the history would be blocked, resulting in a chain state from that point forward deviating from the historical state. Many subsequent actions in history would then become invalid, leading to further rejections and deviation.
One must use the right sorts of tools in any situation. Historical replay as you suggest is the right tool for some problems and the wrong one for others.