# What imagination is Imagination is [understanding](understanding.md) something enough that we can [rebuild](creations.md) a [decent copy](image.md) of it in our minds. Imagination comes from two facts: 1. We can capture a somewhat reliable [image](image.md) of [reality](reality.md). 2. We can manipulate and tweak that image. While imagination can broadly be defined when we stop recollecting our [memory](mind-memory.md) and change or insert information, we *technically* start imagining when we take a step away from perceiving [reality](reality.md). Once we've disconnected from sensory experiences (e.g., closing our eyes), we unlink our attachment from the world around us and can more easily [work with](mind-creativity.md) the thoughts in our minds. Then, when we engage our senses again, we can snap back instantly. By removing and adding various elements, we can form a remarkable variety of [stories](stories.md). Literally, all knowable possibilities of what is, was, and can happen sits inside the mind as an imagined thing. If we focus on it enough we can [feel](mind-feelings.md) as if it's [reality](reality.md) itself. Most of what we [perceive](image.md) as "[reality](reality.md)" is simply our imagination, proportional to our [creative ability](mind-creativity.md). We incessantly play with our memories to create horrific [mental illnesses](mind-feelings-fear.md), but absolutely any [willfully created](creations.md) thing has to be imagined first as well. APPLICATION: The things you dwell on in your mind define what you [produce](creations.md) and how [effectively](results.md). While you don't *directly* create reality with your thoughts, your focus on something *will* increase and decrease the likelihood of events happening that ripple out from that imagined circumstance. Anything that isn't real is the domain of [fictional stories](stories.md). But often, we constrain that imagining into only [likely](understanding-certainty.md) things. The non-fiction version of imagination, usually regarding the future, is called "predictions" or "expectations". ## Predictions and expectations Predictions are stories we have [reason](logic.md) to [believe](understanding-certainty.md) will happen. By the time we're adults, we tend to subconsciously say "no" to all the impossible or unlikely things and localize our thoughts to the possibilities that exist within [reality](reality.md) alone. When we're children, we make sweeping generalizations with very little accuracy. [Adults](maturity.md) tend to predict things with more case-by-case focus (barring [trauma](hardship-ptsd.md)), but slowing down thoughts to consider [bias](mind-bias.md) still takes tremendous [discipline](morality.md). APPLICATION: Imagination is a form of [understanding](understanding.md) that isn't constrained by reality. In that sense, [children](maturity.md) typically have the strongest ability to understand (even if they're unskilled at it) and we typically lose that ability as we [gain experience](maturity.md). ## Purpose We only feel a sense of [meaning](meaning.md) to imagine when our predictions are at least partly useful for our [decisions](people-decisions.md), which is why experience sabotages imagination. If we consistently fail too many of our predictions, we tend to risk an [existential crisis](hardship-depression.md). APPLICATION: Imagination is unfettered by nothing and nobody but our mental limits, but the practical effects of [science](science.md) and [culture](people-culture.md) can impede our attempts to [build](results.md) whatever we imagine. If we become too [conceited](morality-evil.md), we lose the ability to conform our thoughts to [reality](reality.md), which makes our imagination and [feelings](mind-feelings.md) about them effectively [useless](purpose.md). We must predict the future because it dictates what we presently [create](creations.md) and [consider](purpose.md). If you knew you'd probably die tomorrow, you'd live today differently than if you knew you had forty years left to live. Since we must act, we make a [calculated wager](people-decisions.md) on the most likely thing, then give the rest up to whatever we [trust](trust.md). APPLICATION: Blame is a waste of effort. Outside the need for [forgiving](mind-feelings-happiness-stress.md) or [power games](power-influence.md), we don't need to know what caused an issue, but instead what to do about it now to create desirable [results](results.md) in the future. ## Predicting across time Time itself doesn't exist the way we think it does. We perceive "now", but the past doesn't technically exist. The past version of "now" is only in our minds as [memory](mind-memory.md) (former versions of "now") and our connections of cause-and-effect to craft a [story](stories.md) that ends in "now". Since we can cross-reference the past against [reality](reality.md), we have good [reasons](logic.md) to [trust](trust.md) it for our perspective of the future. The future is our [predictions](imagination.md) about what will happen in future instances of "now", but doesn't exist beyond our minds. Our predictions have varying degrees of accuracy, and *any* precision in our expectation of the future gives us reason to [trust](trust.md) it as reliable. Since we tend to [feel](mind-feelings.md) our predictions as if they were occurring presently, the experience in our minds is the phenomenological equivalent of [reality](reality.md) proportional to our ability to imagine. APPLICATION: We tend to obsess about odd, unlikely circumstances. This gets us into trouble because we assume that the unlikely things are likely, which can make us superstitious or anxious, depending on how we imagine its [results](results.md). FURTHER APPLICATION: When something happens, it typically means one thing: it happened. If it was unlikely, it's just as unlikely to happen again. Sometimes people get lucky, but it's better to trust an unlikely thing happening from an [unnoticed](unknown.md) place than where everyone is currently looking. The perceptions of "past" and "future" makes us [feel](mind-feelings.md) our existence is a continuum, and automatically registers in our mind as a series of connected events, even though they are functionally nothing more than memory, now, and imagination. With very, very few exceptions, we tend to find more [uncertainty](unknown.md) the farther out we go into the future or past. We [trust](trust.md) our next or previous breath as existing implicitly, but will consider next month's events with in-depth [analysis](logic.md) to find the same [certainty](understanding-certainty.md), and treat five years from now as a [complete mystery](unknown.md) or [hope](trust.md). Technically, our predictions never look *only* into the future. If that were the case, we'd always predict fantastic silliness. Instead, we use the framework of the past and present we [know](understanding.md), as well any unproven [impressions](mind-feelings.md) about them, to build a reliable-enough model to [understand](understanding.md) everything we need to make sensible [decisions](people-decisions.md) that create [results](results.md) we want. Some predictions go *backward* from the present. By assembling likely past circumstances, we can often infer what caused a situation that presently exists (i.e., "blame"). We give plenty of value to it because we assume it's necessary for [fair retribution](morality-justice.md) for [hardship](hardship-ptsd.md). However, blame isn't very [useful](purpose.md) because it rarely provides legitimate answers to present [decisions](people-decisions.md) (which are inherently about the future). ## Predicting people We tend to underestimate how we'll [change](people-changes.md) from our environment (e.g., [feelings](mind-feelings.md) a day from now) and overestimate how much our environment itself will [change](results.md). This is because we have *much* more direct experience with our minds than our environment, so we're more likely to assume our minds are fixed while the environment is malleable. We tend to suppose other people will say or do things, and usually create [habits](habits.md) around those beliefs, which is the basis for [cultural](people-culture.md) rituals and [social standards](people-rules.md). We're perpetually making and breaking predictions, and it gives us tremendous [power](power.md) to [decide](people-decisions.md) and [create](creations.md). ## Predicting the unknown For whatever reason, some things are simply [unknowable](unknown.md). As a [purpose](purpose.md) grows larger, there are more variables and places where unknowable things can exist. We tend to expect the unknown more than the known because we focus on it. Therefore, unknown things seem to stand out for us more, even while mundane things constitute more of our time and [purposes](purpose.md). However, vast [power](power.md) is at stake for massive [decisions](people-decisions.md), so people pursue many ways to capture and subdue [uncertainties](understanding-certainty.md), which typically includes [analysis](logic.md) and [religion](religion.md), and can expand into [numerical](math.md) assessment. The constant [uncertainties](trust.md) of seemingly mundane things, all the way down to the subatomic level and how we form thoughts in the first place, make predictions difficult. However, the more we [understand](understanding.md) something, the more reliably our [intuitions](mind-feelings.md) can follow [trends](trends.md) before they emerge, and it can create the [illusion](image.md) that we understand when we really don't. ## Expecting chaos Beyond predicting chaos, we can still [direct](purpose.md) it even if we don't quite [understand](understanding.md) how it works. [Parents](parenting-children.md), demolition crews, nuclear engineers, social media experts, and [politicians](groups-large.md) all share that "chaos prediction" in common. Some people, especially [some large-scale leaders](groups-large.md) and [entrepreneurs](socialrisk.md), can sharpen their [intuition](mind-feelings.md) well enough to trace [patterns](trends.md) inside chaos with *astonishing* accuracy. A [trend](trends.md) is the aggregate behavior of everyone's involved [feelings](mind-feelings.md), so the secret to successfully tracking [trends](trends.md) requires understanding which key details to focus on. However, this is very difficult, since it requires *both* [empathy](mind-feelings.md) of the relevant demographics alongside a consistent [analysis](logic.md) of those collective sentiments over time. We only need a few key details to funnel chaos because of how [values](values.md) connect with each other: 1. Our [purposes](purpose.md) often operate as a chain or sequence of elements, often derived from environmentally-triggered [habits](habits.md). 2. Any shift in that chain affects the rest. 3. If we can see the weakest link in that chain, we know where a break will likely come. 4. 80% of the results come from 20% of the actions ([Pareto Principle](lawsaxioms.md)), so specific small things can create a domino effect for *gigantic* things. We need experience to see the correct details because our values tend to oversimplify [results](results.md): 1. The difference between passing and failing can be as little as 1%. 2. There's only a subtle difference between 89% and 90%. 3. However, in a given situation 89% versus 90% may define "pass" or "fail". 4. Therefore, most of the ingredients for something changing are already present in an 89% condition, even if they [appear](image.md) to be as bad as a 1% condition. Further, the Pareto Principle compounds for each effect inside an abstraction: 1. 20% in one action creates 80% of the [results](results.md). 2. 20% of *that* 20% is 4%. 3. 20% of that 4% is 0.8%, and so on. 4. If we observe the effects of this: - 4% will define 64% of the event (80% of the 80%) - 0.8% defines 48.8% (80% of the 64%) - 0.16% defines ~40% (80% of the 48.8%). The implications of these ripples can be stunning: - The type of breakfast a CEO has on a specific day can dictate the fate of 10,000 jobs. - Cracking a whip or pulling a gun's trigger is a relatively light effort that creates a precise, powerful mark that could literally change the world at the right time and place. - [For want of a nail, the kingdom was lost](https://en.wikipedia.org/wiki/For_Want_of_a_Nail). APPLICATION: Often, the most "likely" [trends](trends.md) are the ones that were fringe ideas: - Investing in airplanes in 1900 was a crackpot idea for only crazy people. - Cars were once a "dying trend" before they applied assembly line [technology](technology.md) to it. - Before the microchip, the "[personal computer](computers.md)" was also a dying trend. - Economists once predicted that New York City wouldn't be sustainable because it'd be covered in pony poop. - [Too many others to count](imagination-badpredictions.md)! ## Reliability Estimating future likelihood is mostly a well-designed illusion, so it's *relatively* reliable. We're good at performing most things we're familiar with, but we tend to assume things are more [certain](understanding-certainty.md) than they really are. However, since everything we work with in our minds is essentially a [story](stories.md), we tend to fixate on the end of the experience and forget the details. This means we're constantly integrating new sensations in with old experiences and rebuilding our [perspective](image.md) to converge new information we [understand](understanding.md) and what we have historically [believed](trust.md). APPLICATION: Our minds have a tendency to drift. You don't remember *anything* as well as you think you do, so nobody and nothing can quite measure to how you've reframed it in your mind. This becomes a major problem if you're [grieving a loved one's death](legacy.md). We tend to overestimate our predictions, and often believe we know more than we really do. We also frequently tend to [presume](trust.md) that becoming certain about unknown things guarantees we can do something about them. APPLICATION: We imagine we [understand](understanding.md) the world around us, but most of our beliefs are simply prejudices we've acquired through experience, without much consideration for the idiosyncrasies of reality. Abstractions are valuable as theoretical concepts, but theories *always* take more work to become reality (when they *do* work). Further, we're pretty good at guessing what has happened, but are typically awful at predicting what *will* happen, for several reasons: 1. We're bad at predicting [trends](trends.md) we haven't seen and things we can't know. 2. We tend not to comprehend the [effects](results.md) of [technology](technology.md) or changes in collective [understanding](understanding.md), which dramatically changes the effects of various factors. 3. We tend to overstate what we [feel](mind-feelings.md), even when we're experiencing a distinctly unlikely situation. 4. We don't like [uncertainty](understanding-certainty.md) in the face of [unknown](unknown.md) things (typically from [conceit](morality-evil.md) or [fear](mind-feelings-fear.md)), so we assign broad [values](values.md) and mental models to highly sophisticated things (like mechanisms and [groups](groups-member.md)). This means technical realities and constraints are lost in our pursuit for [certainty](understanding-certainty.md). Even with [statistics](math.md), capturing [information](image.md) for [analysis](logic.md) doesn't make our predictions more reliable: 1. [Technology](technology.md) can't currently capture all the variables necessary to reliably predict [reality](reality.md) and account for [random chaos](unknown.md), especially when dealing with [social behaviors](trends.md). 2. Capturing information is a secondary [image](image.md) to reality, which can make models difficult to represent reality itself, even with reliable data. 3. All events are statistical likelihoods stacked on statistical likelihoods, so finding legitimate chances with averages requires assigning it to multiple statistics, which become layers of abstraction removed even further away from reality. Eventually, [feelings](mind-feelings.md) grounded in [experience](understanding.md) are often more reliable. 4. [Statistics](math.md) will find remarkably accurate correlations, but only [logic](logic.md) in the scope of an individual's [understanding](understanding.md) can build causation, which is necessary for predictions. 5. Sometimes, people who make or [sell](marketing.md) statistics are [lying](image-distortion.md) about where they got their information, and are simply working off an [educated](understanding.md) [hunch](mind-feelings.md). ## Predicting many people Proportional to our desire for [certainty](understanding-certainty.md) and opportunity to [gain power](power.md), we will track large-scale [social trends](trends.md). We can frequently feel them out from our shared [human universals](humanity-universals.md), but too many unknown variables make us unable to precisely track what other people are likely to do, even with [technological assistance](technology.md). Predicting a trend is trying to [understand](understanding.md) a [story](stories.md) you're in the middle of. We can easily see how trends can cycle across history, but many people are often [unaware](understanding.md) of *other* trends that swung the opposite way. In effect, we're making a gamble on the reasonable [effect](results.md) of a cause based on what we know. In fact, most of the people who *make* gigantic trends are blissfully unaware of what their impact will be. If someone [who has died](legacy.md) is presently famous, there's a good chance they never would have thought that they'd be as famous as they became. APPLICATION: Staying unaware of the consequences of decisions that may have a terrible consequence can often expose us to tremendous advantages we otherwise wouldn't have had. If we can humanly survive the likely risks, it's always worth taking an [unsafe](safety.md) decision for the advantages from the [change](people-changes.md).