Do you know the difference between in-band and out-of-band signaling?

The ad networks are using an automated Turing Test based on statistical models to differentiate between "real" and "fake" requests. Until someone commits real dollars to make a purchase, there is no out-of-band verification of the requester's humanness. When you click the ad, your tamper-proof mouse does not take a tiny blood sample to verify that you are a real person, and communicate that via magical ansible to the ad network servers. Until the check clears on a purchase, the only data the ad networks have come through the HTTP requests, as in-band signals.

In-band signals can always be faked. Ask anyone who has ever blown a modified whistle from a cereal box into a phone handset, or modified a Radio Shack tone-dialer to produce the old payphones' "quarter inserted" tone.

So any script writer that either knows or can guess at the algorithms used to automatically sort "fake" from "real" can produce automated behavior that fools the automated sorter. What's more, those models are brittle. If the real behaviors of real humans change, such as by ad-blocking or running other response-modifying scripts, the models become decreasingly accurate classifiers.

A script that blindly clicks all blocked ads on a page is the tip of the iceberg. You can substitute the "click everything" strategy for a "click like a woman pregnant for the first time" strategy, or a "click like a male gamer, aged 17-25" strategy.

If web traffic ever has a significant number of browsers impersonating the browsing behaviors of other types of people with the help of scripts, ad networks can't trust any of their traffic to know "real" from "fake". That is an intractable problem for them.

You have to be able to verify a statistically significant portion of traffic as real humans before your models will work. And that is what Nielsen does with its consumer tracker devices.