1. Which part(s) of the discussion do you expect would be most illuminating for non-quantitatively-inclined readers?
I really like how the article suggests we put uncertain events into four "buckets" - high-risk high-uncertainty (Apollo 11), high-risk low-uncertainty (Russian roulette), low-risk high-uncertainty (getting COVID-19), and low-risk low-uncertainty (driving). While this approach applies "stereotypes" to uncertain events, it's often much easier for humans to think about things when using categories as compared to the raw numbers.
2. Suggest another framing of the issues discussed that would be more effective.
One method I love for evaluating risk of death is the micromort along with confidence intervals. In keeping with conventions for metric units, one micromort is a 1/1,000,000 (one in a million) chance of death. For example, skydiving comes with a risk of 8 micromorts per jump (8 in a million chance of death), while traveling 230 miles by car comes with a risk of 1 micromort. This unit lets us convert risk from a hard-to-understand fraction into a nice, low, round number, which is much easier to comprehend.
Additionally, micromorts let us use error bars that make sense on our numbers. For example, skydiving has a risk of 8.4 micromorts per jump, with a 95% confidence interval between 7.7 micromorts and 9.3 micromorts - a low-risk low-uncertainty activity. But going to space, by contrast, we now know has risk of 32,000 micromorts (not taking into account modern advances in spaceflight technology), with a 95% confidence interval between 21,000 and 49,000 micromorts - far less certain than skydiving.