There’s also the japanese inventor who would borderline drown himself for ideas.
romeostevensit
Karma: 5,008
This highlights a whole class of questions around education on navigating the realities of modern online job and relationship stuff.
Law of equal and opposite advice: some people are socialized into repressing anger/turning anger inward toward the self which makes it easier for people to take advantage of them. These people need to pass through a phase of recontacting their anger before trying to ‘let go’ of it.
Agreed. Status becomes zero sum when the dimensionality of competition gets reduced to 1 (otherwise known as a hierarchy). In an environment with specialization you wind up with a multi dimensional deference network where people are deferred to in their areas of expertise and everyone benefits from the efficiency of this. A status lattice, otherwise known as prestige.
Selection effects are computationally prohibitive to back out of data. If you have a very large combinatorial space and a sufficiently permissive filter one in a million things are happening constantly.
I investigated this by wielding it with intention as a teenager. I would choose something to notice and treat as meaningful, and then watch the rest of the system pattern match adjacent things a lot (synchronicity).
AFAIK, no one knows how to make a thorium reactor that doesn’t create dirty bomb risk even though their enrichment risk can be made low.
https://en.wikipedia.org/wiki/David_Marr_(neuroscientist)#Levels_of_analysis
It is often characterized as 3 levels but if you read his book the algorithmic level is split into traversal and representation (which is highly useful as a way to think about algorithms in general) As four levels it also corresponds to Aristotle’s 4 whys: final, formal, efficient, and material.
This highlights an, I think, neglected angle of analysis of civilizational problems. I almost want a deity of diffusion of responsibility. One of Moloch’s most faithful servants.
When looking back on an earlier era one has the benefit of conceptual distinctions that didn’t exist at the time. Looking back on our era, I think people will be surprised that we had dim understanding of responsibility and credit taking being able to diverge, and in fact optimized to diverge.
Reasonably you’d probably skip the first few doublings for something that low value, which changes the outcome significantly.
Portfolio construction theory says optimal allocation to gold is generally not zero. Gold you can email seems clearly valuable. As for the heuristic that leads to thinking bitcoin is a good idea in general it was ‘if you see a new mathematical result that enables a new/different kind of payment layer invest some time and money to understand it.’
Great post, I noticed I was confused about this the other day.
couldn’t find anything about any other vaccines working this way (all or nothing).
I think it’s fair for this hypothesis to hang out in the space given that previous vaccines weren’t mRNA based.
Further prior art: Accelerando
I think it’s easy to denigrate (almost exclusive) trackers of social reality. But they are people who experienced conditioning that most of the variance in the outcomes they care about were controlled by social reality inputs. It makes sense that they constantly have to track changes in social reality because social reality is anti-inductive/adversarially optimizing out from under you constantly. Being able to ignore large swaths of social reality and thus bootstrap more permanent wins (since solutions in causal reality often stay wins) is something of a privilege. People mostly tracking causal reality also pay an often invisible cost related to having social reality treat you as a defector.
Agree. I like to split the empirical problems out using levels of abstraction:
Traversal problems: each experiment is expensive or it isn’t clear how to generate a new experiment from old ones because of lack of visibility about controlled variables.
Representation space problems: the search space is too large, our experiments don’t reliably screen off large portions of it. So we can’t expect to converge in any reasonable time.
Intentional problems: we’re not even clear on what we’re trying to do or whether our representation of what we’re trying to do matches the natural categories of the solution space such that we are even testing real things when we design the experiment.
Implementation problems: we can’t build the tooling or control the variable we need to control even if we are pretty sure what it is. Measurement problems means we can’t distinguish between important final or intermediate outcomes (eg error bars).
not impossible per se though you’ll note none of these people do a full range of motion. https://www.youtube.com/watch?v=4DEQhjiaNL4
These are helpful considerations to highlight, thank you.
Notice how your examples are working class. The middle class or Venkat’s aptly named clueless are maximally insulated from causal reality.
One of the major helps for me was thinking in terms of number of potential leverage points for an intervention. If an intervention seems hard to me it is often the case that I am simply trying to lever on a bad spot and am unaware of other spots to place the lever.
Deliberate practice is often about building an intervention model that is more fine grained, which exposes more such points.
I really wish there was a techniques focused history of European philosophy. I suspect anyone capable of a decent shot at such is busy doing more important things.
Is it possible to teach people good heuristics for managing their online presence or does the underlying territory change too fast even for general heuristics? I’ll give a concrete example with serious consequences: several people I have talked to about online job searches didn’t know about the automated resume screening that large platforms use and thus the need to optimize the resume using the appropriate tools/checklist/domain knowledge.