[jfalcon]

> I can see this kind of survival-bias stories distorting the reality.

That was my take with the entire report which I think lends to an inherent bias within the data and stories. You have the entrepreneurial stories, then you have the ones where people are both impacted and receiving benefits.

The infographics and charts even call out how countries that are "first-world" with fewer safety nets are more likely to be in "survival" mode compared to countries with them.

The bit from George Carlin standup routine regarding how the poor are there just to scare the hell out of the middle class rings true in this reflection. Poorer countries accept their current realities and the feedback reflects the hustle. Richer countries with safety nets reflect the existential issues with previous industrial revolutions. Richer countries without safety nets reflect the fear that their efforts will be made "replaceable" by AI.

As for the rest - massive testing creating false positives - that is an issue of implementation and the errors introduced by humans, not data itself. If the process were in large part made more automated, it could screen for a larger panel of issues for less cost.

From my experience working deep in data and human factors - the issue in quantifying the root cause isn't reality, we live a shared experience in general. The issue is the data isn't good enough. What bugs us about it is the psychology that our perceptions are different enough to the degree that we will fight to prove an unknown.