Both parts are about the hazards of trusting results from computer simulations. Putting the two parts together shows the connection between divergent series and tail risk. When a series inside the computation changes from convergent to divergent, you then have tail risk, and the simulation's trustworthiness degrades suddenly, yet in a way that may be difficult to notice.

If you are a rational agent, you work with averages, because you want to maximize expected utility. In the kinds of simulations I mentioned, it's especially important to look at the average rather than the mean, because most of the harm in the real world (from economic busts, wars, climate change, earthquakes, superintelligences) comes from the outliers. In some cases, the median behavior is negligible. The average is a well-defined way of getting at that, while "probability of a catastrophically large change" is not capable of being defined.