We started the series (both in my imagination and in publication) with a story about a ballot initiative outside America. As I reflect on it, it's helped me formalize my guess: sacred values are just secular values we can't amortize. The death of a stranger should be stopped, ya know, in general. We want less of it. But death of our brother or sister, that's worth almost anything we could sacrifice. Assuming you like them, I suppose. [Insert witty comment about, amortizing a cost means that instead of it being instant, it goes on and on, and never dies = a-mort-izing. This is a bit dark and my appetite for wit is spoiled.]
The second one was about economic anxiety (not a code phrase). We can't rely on never making mistakes, something will always go wrong. So perhaps we need a better view into an economy than "aperiodic cycles" – maybe adopt the N-nines system from computers – Can we have an economy growing more than 90% of the time? 99%? 99.9% seems like it's asking a lot.
After, there was the post about an idea I've thought about for a long time – immigrants as a positive force in zero-sum displacement. I think, in general, people don't imagine things very complexly when there is zero- or negative-sum displacement. Lower subgroup risk makes them a shield for higher risk subgroups. It's no surprise that our evaluation of things doesn't consider the totality of their impact, or even attempt to. But I also think, outside finance, it's rare for people to follow an idea and to have it lead to both positive and negative risk assessments. So often our guess defines our analysis, too – it is against our tribal dog-like minds to think a flood of strangers might make us safer. But what's the point in analysis if you don't, at least sometimes, reverse your instincts?
The penultimate piece was more of a gripe than anything – that people continue to view climate change as a sacrifice instead of a risk, which impairs our ability to understand it as the existential threat experts seem to believe it is. Maybe the experts are wrong, but then who compiles the reports with the shockingly low costs attached? An amateur? Surely I'm missing information, and as far as I can tell, it is the most important information. Some bona-fide environmentalists (like the creator of EcoGeek here) say the costs of stopping and reversing climate change are less than just paying the direct costs – but I cannot comprehend how that could possibly be true given these reports of ~0.1% GDP growth cost. But if they won't at least hint as to what the missing piece of the puzzle is, I don't have a lot of other options.
As an aside – in a follow up video, the EcoGeek founder laments the popularity of that clip on Twitter and says he doesn't want to be a professional arguer, he wants to be a professional science communicator. I'd love to do a longer-form text-based interview so all the facts are presented in a way I think we'd both like, but I admit, I'm frustrated enough by my own ignorance that arguing seems like an okay way to have that conversation, even if I wouldn't publish it. It's an important thing and someone should argue about it. Probably a lot of people.
I wanted to end with perhaps the most abstract, but also the most important – what to do about risk. Traditionally, we mitigate it. That means, avoid correlated risks, seek out uncorrelated risks to balance out and help amortize the costs associated with those risks. But then the secondary investments are flooded by people doing the exact same balancing, and begin to be correlated more strongly. This recurses indefinitely until we reach some abstract eigen-risk state where you aren't even buying assets so much as independent asset leverage insurance. Or you could just go one step down the hierarchy and have a more specific market model. Of course, the market statement itself has tremendous risk, but at least it is human-comprehensible – I was on team X, and team X did well/poorly.
In the end I just wanted to bring more examples of risk into discussion. It seems like an important issue, and most of the best analysis works from a group of very different insights mashed together semi-coherently.