Could there be a confirmation bias to this observation?<p>You distinctly remember the times you had an outlier belief which you ignored to your detriment, but tend to forget all the foolish-seeming ideas you had which were indeed very much foolish when taking stock of the past.<p>I think the opposite advice might be even more useful for many, many people: be more scared of overconfidence, because you know less than you think. Research on cognitive biases and the underperformance of "experts" in many fields tends to support this view.
Outliers happen all the time. The sort of "overconfidence" described in this article is really about outlier detection and being willing to take a risk on something being an outlier. I have some thoughts on outlier detection.<p>* Avoid groupthink. If everyone thinks it's an outlier then it probably isn't. I won't touch anything more than two people tell me to look at.<p>* Sometimes you do know something the market doesn't. Sometimes you can maintain a position longer than the market can remain irrational. This is something that happens every day.<p>* Ask why it's different. Outliers have distinguishing characteristics from their peers.<p>* Look as the population the potential outlier belongs to (businesses, athletes, commodity futures, etc). Understand key statistics such as variance, confidence intervals, range, mean, and mode. This helps answer basic questions like "To be successful will this need to be in the top 20% or top 0.002%", "If this fails completely, what will it cost me" and "What is the range of the 95% most likely outcomes." A lot of people will avoid something that feels more risky than it actually is.
Reasoning based on fear has taken over far too great a mindshare. We continually convince ourselves of our rightness righteousness and betterness by down-putting the hopeful, the ambitious, the would-tries. There's a new church of doubt in our fellow man & willing against the try. This post sets a nice positive message I long to hear, about trying, trying hard, about swinging for great.
Meh. Maybe not so many people should be trying to be outliers. Maybe society would be better off if we stepped back from the always-on, up-or-out culture and accepted that most people are average and (rightly!) value consistency more than upside. (Is it unfair to immediately wonder if the article was written by someone with an upper-class upbringing, who's always had access to a safety net that most people don't?)
Related: "Heuristics That Almost Always Work":
<a href="https://astralcodexten.substack.com/p/heuristics-that-almost-always-work" rel="nofollow">https://astralcodexten.substack.com/p/heuristics-that-almost...</a>
Put another way, don't extrapolate based on unspecific information. Context matters a lot, and the average case is rarely useful for making a decision.<p>Ben mentions his writing on outliers [1] and how <i>"low-info heuristics tell you that outliers can’t exist"</i>, which is completely true but I want to add another perspective to that.<p>As mentioned in the outliers piece, you want to rule things <i>in</i> not out. The average case is good for ruling things out, but terrible for ruling things in. Specifics to your scenario will always be the reason to rule in on things that look bad in the average case.<p>[1] <a href="https://www.benkuhn.net/outliers/" rel="nofollow">https://www.benkuhn.net/outliers/</a>
To distill: popularity of an idea != quality of thought. Just because many people believe something, doesn't mean it's likely to happen. In fact, it doesn't even mean the people believe their idea is very probable (e.g. VCs betting on startups knowing that most of them will fail).<p>In turn, it can be useful to adjust the very one-sided public estimates based your own nuanced reasoning. This could change the status-quo probability from 99% to, say, 60%.
VC firms expect the vast majority of their portfolio companies to fail. Being skeptical of a startup’s prospects does not in any way represent a break from the VC’s expert opinions. They are playing the whole field. You’re going all in on one company, a completely different thing.
> The founders of Wave seem much smarter, more relentlessly resourceful, and more trustworthy.<p>I appreciate the casual trashing of Theorem's trustworthiness as someone who has been on the receiving end of the lack of it.
> (...) early-stage startups (...)<p>> (...) efficient market hypothesis (...)<p>Classic case of "just read a new idea and I'll apply it everywhere".<p>In addition of everything else wrong with this post: No, you can't reach reliable conclusions about startups by reaching to efficient market hypothesis.