Great post—enjoyable read and connected some concepts I hadn’t considered together before.
The first thing that immediately comes to mind when I think about how to act in such an environment is reputation: trying to determine which actors are adversarial based on my (or other’s) previous interactions with them. I think I would try this before resorting to the other three tactics.
For example, before online ratings became a thing, chain restaurants had one significant advantage over local restaurants: if you were driving through and needed a place to stop and eat, the chain may have an expected quality that is worse than the local restaurant, but at least you knew you weren’t going to be sick because of their reputation. And now that we have Yelp, I can just look there and see which restaurants consistently get 4-5 stars and no complaints of food poisoning, chain or not.
Of course if a restaurant was really trying to deceive you, it could bury negative reviews in thousands of bot ratings (I actually don’t know if this is truly possible given moderation of many rating platforms). And when the environments get more adversarial and the benefits of deceiving you become higher (or the costs of taking the honest route become higher), I imagine a reputation-based filter like this could be easily thwarted. So this feels like an intuitive and lower-cost first line of defense, but not a reason to fully retire the big guns that you talked about in this post.
Great post—enjoyable read and connected some concepts I hadn’t considered together before.
The first thing that immediately comes to mind when I think about how to act in such an environment is reputation: trying to determine which actors are adversarial based on my (or other’s) previous interactions with them. I think I would try this before resorting to the other three tactics.
For example, before online ratings became a thing, chain restaurants had one significant advantage over local restaurants: if you were driving through and needed a place to stop and eat, the chain may have an expected quality that is worse than the local restaurant, but at least you knew you weren’t going to be sick because of their reputation.
And now that we have Yelp, I can just look there and see which restaurants consistently get 4-5 stars and no complaints of food poisoning, chain or not.
Of course if a restaurant was really trying to deceive you, it could bury negative reviews in thousands of bot ratings (I actually don’t know if this is truly possible given moderation of many rating platforms). And when the environments get more adversarial and the benefits of deceiving you become higher (or the costs of taking the honest route become higher), I imagine a reputation-based filter like this could be easily thwarted. So this feels like an intuitive and lower-cost first line of defense, but not a reason to fully retire the big guns that you talked about in this post.