Taking a blind guess here because I have never worked at Google, but I would assume there is one organization that has the data, and another organization that can block IPs from clicking on the ads and consuming the spend. There is a byzantine process preventing that second org from getting the data along with a lack of motivation because it would decrease ad-spend, which is one of their key metrics. Org2 which deals with people clicking the ads is a bad place to work and no one who is actually good sticks around long enough to navigate the process and implement this, so the can gets perpetually kicked down the road.
Tends to be how it goes once you reach a certain size.
Google's AdSpam/fraud/bot-prevention team was, when I worked there, world class and fairly well funded, took their job seriously, and had access to all the data. It's an existential threat to the ad business, because if Google gets a reputation for being full of bots/spam, then the advertisers will bid lower per click/conversion to compensate, which means that legitimate website publishers will get paid less and go to other networks, which is a feedback loop that leads to the entire market collapsing (see also: https://en.wikipedia.org/wiki/The_Market_for_Lemons). It's absolutely worth refunding/zero-rating huge amounts of advertiser spend to avoid that situation, and they do.
It's not that they're not trying, it's just a very hard problem.
Problem 1: Buyers cannot tell if a product is good or bad, so they offer less money and good sellers may leave.
Suppose 50% of used laptops are good and worth $1,000, while 50% are bad and worth $400. Since you cannot tell which one you are buying, the average value is 0.5x1000 + 0.5x400 = $700, so you will not want to pay more than about $700.
But owners of good laptops may refuse to sell for $700, so more good laptops leave the market and the chance of buying a bad one increases. And the only guy selling for $700 is the lemons.
Problem 2: The theory assumes buyers already know how many bad products are in the market, but in real life they often do not.
Your "point 1" is literally the argument of the paper. If that scenario arises, the market collapses and no further sales can be made. That's the whole problem. As someone who takes a percentage of every sale, you want to keep the lemon-sellers out even though in the short run they make you extra money.
Your "point 2", if it's meant to be a rebuttal, isn't much of one. Buyers don't need to accurately know exactly what fraction of sellers are fraudulent; if they believe that it's 50-50, the same thing happens, even if the true rate is 80-20 in favor of good sellers. Conversely, if buyers are overly optimistic about quality, the market can persist despite a level of fraud that's higher than should be tolerated. But in any case, things like reviews and external reporting should eventually give them good information.
Cynicism is fine. They don't have to believe in any sort of ideal to do this. They just have to be thinking more than a couple months ahead to realize the math favors quality.
Just to be clear, this is different to the problem of Google ads that link to malware and fake banking websites and promotion of cryptocurrency scams isn't it?
Related in that some of the same organized groups tend to be carrying out every kind of attack at once, but operationally a different thing.
In the ad marketplace there are four participants: the advertiser, the user, the network (Google), and the publisher (also Google for AdWords, other websites for AdSense and so on, and effectively the channel owner for YouTube).
In the click spam or botnet case, the bad actor is the user, who is usually associated with a publisher trying to get extra money (although not always - there's reasons like auction manipulation where some advertisers run click bots too). In the bad-ads case, the bad actor is the advertiser.
At Google, each of those problems has their own well funded team, but they do also share some data to help catch rings of bad guys.
it's also just flat-out unsexy from a product/MBA-brained perspective to push for something that will negatively impact metrics for your users. I ran into this when I was advocating for onboarding a third-party provider that would filter out automated/spambot email clicks thus decreasing the north star metrics our users had for engagement (even though it was truthier and would provide more accurate targeting and some of our most senior people had been advocating for for years)
the only reason I got the go-ahead for the effort was because one of our upstart competitors who was handily eating our lunch had implemented this years ago, started advertising based on it, literally pointed to the fact that we didn't do this yet, and then this was followed quickly by all of our other competitors implementing this, too. at this point we were well inducted into the illustrious halls of companies who stopped giving a shit about their core product with leadership blaming everyone but themselves for the fact that we were churning faster than we were net-new-ing
and even then it was a half-assed, resource-starved implementation that got dumped on regularly. have left the org since and couldn't be happier
also observe that Musk did the opposite, counting any attention whatsoever on a tweet as a view, such as a 1 pixel sliver appearing at the bottom of the viewport as you scroll, boosting numbers and all the Twitter posting addicts praised him for it when he did it
Alphabet has claimed to be fighting ad fraud for many many years.
That is not how an organization fighting ad fraud would structure itself.
Alphabet does not have an abundance of technical incompetence. But it does have the strongest of incentives to ensure ad budgets get spent quickly and no meaningful disincentives.
I mean what’s the OP going to do, go to Google’s competition?
I mean if you could show Google know they're charging people for ads they're knowingly showing to robots then a few €Billion of fines for fraud should be following.
Tends to be how it goes once you reach a certain size.