I've been thinking about potential solutions to the very likely case of what I previously referred to as Shadow Topics, the idea that other systems will layer on their own ML to build Topic prediction and lookalike models and instead of selling Topics instead sell what is essentially an alternative layer of what looks like Topics but is not.

I don't think that this is a problem exactly. If handled properly then buyers can make decisions against such models and take their chances around less accurately set terms. However, we know that fraud is particular rampant in the ad tech system and it seems very likely that Topics, if mainstreamed, will immediately be accompanied by middlemen adding Topics fraudulently to the ecosystem or using modeling to generate Shadow Topics and treat them similarly to Topics and causing significant confusion and loss of trust in the Topics system.

If buyers have no clear way to understand if a Topics value they are bidding on was generated at the level of the browser or the middleman the ecosystem could act unpredictably. Topics (as I've previously discussed) is likely to be highly trusted by buyers, their presence will be of high value. Topics could then be shared among site and ad tech system. But if the ad tech systems are incentivized to create fraudulent or lookalike Topics then the incentive to keep Topics to themselves as a real or fantasy secret sauce code product is increased. The market for Topics could blow up and then fall apart as declining trust in Topics zeros out value.

Is there a way we could better secure Topics as verifiable by buy-side systems? Some way that a buy-side system could verify that the Topics they are seeing is indeed a Topic generated by the browser? Or, if a Topic is shared with a publisher that the publisher could run that verification?