The streetlight effect got its name from the following anecdote: *A policeman sees a drunk looking for his keys under a lamp post, starts looking with him. After a while he stops, asking the man whether he's sure this is where he lost them. Turning around, the drunk says he has no idea, but this is the only place he can see anything.* This original story is attributed to Nasreddin, an Islamic cultural figure: *One day, Nasreddin lost his ring in the living room. After looking for a while, he goes outside looking for it. Questioned by his wife about this, he answers the room is too dark for him to find anything, when there is so much light outside.* Both stories illustrate our tendency to overfocus on what comes easy at the expense of what makes sense; on the information we have, rather than the information that is hidden from us; on why we're right, instead of why we're wrong. It is consequential because it affects how we manage risk and allocate resources. ## Distracting Wounds A good example of the streetlight effect in action is distracting wounds. I learned about the concept through [[Can't Hurt Me by David Goggins]]. When rescuing people, it's easy to get distracted by the most obvious or spectacular injuries, like an open leg fracture, which is rarely mortal. Addressing that first in the rush of the action without assessing the rest might make you miss the broken rib that perforated the lungs of the victim. Many people die from distracting wounds every year, despite the fact paramedics are specifically taught not to let themselves lead astray by them. This seemingly goes agains the conventional wisdom of doing the most simple task so that you can move forward. The trick is to recognize some situations call for one type of prioritization — because all tasks at hand are straightforward — while others need you to [[fieldnotes/Notions/Tackle the Monkey First|differentiate between the monkey and the pedestal]], between critical wounds and distracting wounds. What good is patching a scary wound if the victim is going to die from another? ## Distracting Information >“It ain’t what you don’t know that gets you into trouble. It’s what you know for sure that just ain’t so. “ *— Mark Twain* Another example comes from an experiment described in [[Thinking Fast and Slow by Daniel Kahneman]]. You're given the following description of an individual by his neighbor: *"Steve is very shy and withdrawn, invariably helpful but with very little interest in people or in the world of reality. A meek and tidy soul, he has a need for order and structure, and a passion for detail"*. Is Steve more likely to be a librarian or a farmer? When asked that question, almost every single person answers he's more likely to be a librarian, failing to consider the distribution of librarians and farmers in society. Because some information has been brought to our attention, we tend to consider the question exclusively in the light of it, *replacing* our current knowledge instead of updating it.[^1] We tend to overrely on information, recipes and technics that are readily available or easily accessible, often neglecting crucial insights or edges. ## Distracting Models >"The problems with models is that the assumptions that are necessary to simplify the model eventually come back to bite you." >*— Rory Sutherland* Building up on the previous example, we tend to overrely on *given* information. Most given information, however, comes from the past. This means we have a tendency to think of the future as something slightly different from the past, when it tends to be vastly different from our expectations because of... unexpected events. This tendency we have to address the future in terms of the past leads to overfitting: We create solutions that would have worked in the past but fail when confronted with reality. Models that are derived from past events tend to create the disastrous blind spots N.N. Taleb calls [[Black Swan Events|black swan events]]. Such events owe their name to a deceptively simple idea. People tend to think black swans are impossible, because all the swans they've ever seen were white; and with every white swan they see, their confidence in the impossibility of a black swan grows bigger. But a single black swan is enough to wipe out everything that was based on the assumption that all swans are white. This analogy illustrates the philosophical problem of induction: Can we make predictions about what we did not observe based on what was observed? We've seen it happen during the 2008 subprime mortgage crisis[^2], which was deemed impossible by many. Industry-standard models made the mortgage market look rock solid, when it was on the verge of collapse. Only a handful of outliers were able to see happening, no thanks to any model. Taken from N.N. Taleb's [[The Bed of Procrustes - Nassim Nicholas Taleb|The Bed of Procrustes]], *"you can expect blowups and explosive errors in fields where there is a penalty for simplicity"*. Overrelying on models makes one blind to the moving boundary between relevant and irrelevant information, between signal and noise. The issue is, of course, that we can't predict what will be relevant in the future, or what will change. We can only know that such explosive errors and events will happen. >"There are known knowns. These are things we know that we know. There are known unknowns. That is to say, there are things that we know we don't know. But there are also unknown unknowns. There are things we don't know we don't know." >*— Donald Rumsfeld, former United States Secretary of Defense* The way we address *unknown unknowns* is often by arbitrarily stretching or amputating the part of reality that doesn't fit the expectations and models we've come to build, rather than revisiting those. > "All models are wrong, some are useful." *— George Box* ## Asking Questions A crucial component of the anecdote we started with is the policeman asking "why are we looking here anyway?" Having the people and space to ask hard questions is a requirement if we want to avoid blindspots. Don't fool yourself and don't be a quack[^3]. ## Variations >"It is tempting, if the only tool you have is a hammer, to treat everything as if it were a nail." >*— Abraham Maslow* >"The first rule of fishing is fish where the fish are." >*— Charlie Munger* [^1]: To learn more about Bayes theorem, [check out this video by 3Blue1Brown](https://www.youtube.com/watch?v=HZGCoVF3YvM) [^2]: An excellent investigation on the topic: [Money, Power and Wall Street by Frontline](https://www.pbs.org/wgbh/frontline/documentary/money-power-wall-street/?) [^3]: UK equivalent of a snake oil salesman, a charlatan