How is it that your mind is capable of handling new situations you’ve never previously encountered? How do you solve a problem you’ve never solved before? Is this just the magic of consciousness, or is there an underlying process — or algorithm — your mind uses behind the scenes to deal with the unique experiences you encounter each day? And if there is a process, how can you use it to improve your ability to think?

Computers are still very inflexible at solving problems they’ve never seen, but your mind is not nearly so limited. Without much difficulty you can converse with someone you’ve never met before, read and understand something you’ve never read before, or navigate a shopping mall you’ve never visited before.

Your ability to handle new situations goes way beyond behavior though. You can solve a problem entirely in your mind, even without taking any direct action. Sometimes you’re aware of the process, and sometimes it happens unconsciously, but either way there’s a purely cognitive aspect to human intelligence that’s independent of behavior.

I think you’d agree that when trying to solve a new problem, the solution arises when you reach a certain level of understanding, even before you’ve taken any action. When a new insight, decision, or perspective is attained, the action steps may be very straightforward. Certainly for some problems the physical implementation remains difficult, but that’s usually because there are remaining sub-problems that haven’t yet been solved at a cognitive level. For example, you may come to the awareness that the solution to your relationship problems is to break up with your current partner, and on one level that may in fact be a solution. However, before you can implement that solution, you must solve a myriad of sub-problems such as how and when you’ll inform your partner, who will move out, and so on.

A problem-solving exercise

Let’s consider a simple, real-world problem, with the goal of gaining insight into the key aspects of human intelligence. This exercise should be fairly easy for you.

Suppose I tell you I just moved into a new house, and I have a problem. The lighting in my new home office is too dim. What can I do to fix this? (This is an actual problem I must solve.)

Pause for a moment to think about how you’d solve this problem. When you have an idea of how you’d solve it, continue reading. I’ll wait…

OK, good. Even though the problem is very simple, and the preferred solution may seem obvious, there are many ways to solve it. Perhaps the simplest solutions would be to install brighter light bulbs or add more lights. But other valid solutions include selecting a different room for my home office or outsourcing the problem to a professional lighting expert. And for every solution, there are more sub-problems to be solved, such as which specific lights and/or bulbs to buy, how many to buy, where to put them, where to buy them, how much to spend, etc. But we’re not really interested in the specific solution you came up with but rather the mental process you used to get there.

Take a moment to consider how you solved this problem. What can you say about how your mind tackled it? There are many possibilities, but here are some of the more common patterns:

Instant knowing – The answer just popped into your head as soon as you read the question. You didn’t even have to think about it.

Multiple choice – Two or more possibilities popped into your head, and you selected a preferred choice from among them.

Conscious analysis – You read and re-read my statement of the problem and attempted to reason your way to an intelligent solution, perhaps considering my potential constraints such as time, cost, and available space.

More data needed – You perceived my definition of the problem as inadequate and wanted to request more details, such as a photo of the room, a description of the work to be performed there, my personal lighting preferences, the color of the walls, etc.

Suspicion – You figured this was probably a trick question and thought about how I might mislead you in order to make a point.

Apathy – You didn’t care to answer the question at all and kept reading or skimming the article without bothering to clarify any particular solution.

There are lots of other possibilities too. Perhaps your mind even used a hybrid approach that combined various elements of the items above.

Don’t worry if you only have a partial awareness of how your mind actually tackled this problem. Although your conscious mind is limited by the narrow bandwidth of your attention, your subconscious isn’t so limited.

Aspects of human intelligence

Regardless of what specific process you used, I assert that it involved several key elements, even if you refused to solve the problem at all:

Cognitive pre-processing – As you read the text description of my problem, your mind took the raw sensory input arriving through your eyes and transformed it into an internal representation, one that exists only in your imagination. Since this was a visual problem, perhaps you even visualized what my office might look like, or maybe you imagined a room with dim lighting. Even if you didn’t visualize anything, you still had to “load” the problem into your mental RAM. Take note that your mental representation of the problem is not the same thing as the actual physical reality it represents. The problem as you know it is nothing but an imaginary construct in your mind.

Associative memory – Once you formed an internal representation, your mind accessed memories it could associate with that representation. You may recall some of the specific memories that surfaced, or they may have been very fuzzy. Those memories may have been visual, auditory, kinesthetic, emotional, or completely abstract. You may have recalled how you solved a similar problem, or you may have simply remembered that a good way to improve lighting is to install brighter bulbs. You may also have pulled up associations telling you that the problem is too simplistic to bother with, or that most exercises found in articles aren’t worth your time. You weren’t born with any of this knowledge. Your mind stored the information you learned in the past, and you’re able to recall that information now. The knowledge may be clear or fuzzy, but it still resides in your memory. Without access to your memories, it would be impossible for you to solve or even to understand the problem. You’d be like a newborn baby.

Pattern matching – As your associated memories surface, your mind finds one or more potential solutions. But how does it do this? Consider how remarkable this ability is. After all, you’ve probably never even seen my office. My office is a unique room with unique lighting. This is an entirely new problem, one that has never existed in quite the same form. And yet you could probably solve this problem easily, even if you had to physically implement the solution too. The reason you can solve it is that your mind is able to generalize the problem and match it with a generalized solution that’s already stored in your memory. It’s able to reason by analogy that my problem is similar enough to other lighting problems with known solutions, and so a pattern match occurs.

Expectation – Once your mind comes up with a potential solution, it forms expectations about what will happen if that solution is implemented. These expectations come from associated memories about what happened in the past. You may imagine the solution as a visualization of a room with brighter lighting, or you may simply access the expectation that you know your solution will work. When your mind creates an expectation that matches its internal representation of the desired solution, you achieve clarity that the problem now has a solution.

How the human mind thinks

Let’s compare human intelligence to the capabilities of modern computers in order to better understand why we consider human beings intelligent while the best AI available today remains relatively dumb, inflexible, and severely limited.

Can computers form their own internal representation of physical world phenomena? For the most part, yes. Computers are capable of storing real-time sensory input in digital form, which can be pre-processed in a variety of ways, and those internal representations can be saved with high accuracy and reliability. In some cases their input capabilities already exceed ours; for example, a machine can process raw data from infrared sensors, and it can sense temperatures that would burn or freeze a human being. With proper backups digital memories are significantly more permanent than human memory as well.

Can computers take advantage of associative memory? Although their associations may not be as rich as ours, again the answer is yes. For example, this blog uses a relational database, which is capable of storing and retrieving associations between pieces of information. You can click a link to an article, and the article will load because the link is internally associated with the article text, along with the article title, date of publication, and other data. So computers are already capable of forming associations between anything they can store. In fact, the whole Internet works on this principle — a hyperlink is an associative memory between some link text, a URL, and a computer data file such as an HTML web page.

Can computers form expectations? Yes, but only to a very limited extent because their ability to do so is severely hampered by their inflexibility at pattern matching. While we wouldn’t normally think of computers as anticipating the future, they’re at least capable of exhibiting the associated behavioral elements. For example, the user interface on my computer is prepared to handle just about any input I might throw at it, even if the specific sequence of key presses, mouse movements, and button clicks is completely unique. Consequently, its behavioral responses appear semi-intelligent. Where computers are most lacking, however, is in their ability to adapt to the unexpected. When computers experience something beyond their pre-programmed expectations, they fail; human beings, on the other hand, are capable of learning and adapting to the new and unexpected.

Can computers perform pattern matching? If we’re referring to general-purpose pattern-matching, today’s answer must be a resounding no. This is where human beings totally dominate computers. Even the best artificial intelligence available today is no match for the pattern recognition capabilities of a child. In very limited domains like speech recognition, artificial neural networks are still largely inadequate (otherwise I’d be using such software to dictate this article right now instead of shelving it in my closet). Our ability to store and recognize patterns is why humans are able to solve so many problems that a supercomputer simply cannot solve. Interestingly, our neurons take milliseconds to fire, while computers can execute instructions in less than a nanosecond. Yet we can still recognize patterns in a split second that a computer can’t figure out with days of continuous processing. More speed applied to today’s AI won’t improve the situation much, except in puny baby steps. And the reason is the unique way human beings store and process patterns. Our pattern matching ability is also the heart of our ability to learn and adapt. The primary reason computers are weak at learning is their inability to perform multi-purpose pattern matching.

Invariant representations

Computers store data in digital form. They can pre-process, compress, and convert that data all they want, but the results are still digital. Digital data is accurate, precise, and permanent, but the downside is that it is also extremely rigid. A binary digit is either a one or a zero, on or off, yes or no.

Human beings, on the other hand, do not store data in digital form. Our memories are not pixel perfect representations of reality. They’re fuzzy, imprecise, often inaccurate, and orders of magnitude slower to access than computer memory. In many ways human memory seems totally inferior to digital data storage. But its key strength lies in how those memories are stored, and as you’ll see in a moment, this more than compensates for its many shortcomings.

Your mind stores and processes information in what are called invariant representations. Invariant means unchanging.

As you go through life soaking up sensory experiences, your mind processes those experiences into its internal database. But instead of storing every specific detail, your mind strives to identify and save general patterns. It turns specific sensory data into abstract forms, and those abstract forms are the cornerstone of human intelligence.

An example of an invariant representation is a person. A person is a concept that doesn’t change much. It may be hard to define in words, but your mind “knows” what a person is. If I point to something in a room and ask you, “Is that a person?” you could tell me in a split second. You weren’t born knowing this — your mind learned this invariant representation from your many experiences dealing with specific people.

Your entire life’s worth of knowledge is stored in your mind as associatively linked, hierarchically organized, invariant representations.

Specific to general to specific

A computer is forced to reason with specific data and algorithms, but human beings are wired with the ability to generalize from the specific, to store those general patterns, and to match those general patterns to new specific situations.

Learning is the process of experiencing specific sensory input, noticing general patterns, and storing those patterns as invariant representations. For example, once you’ve seen a number of cars, your mind identifies the pattern of “car” and then stores that pattern as an invariant representation. The more cars you see, hear, feel, and smell, the richer the invariant representation your mind will store.

Anticipation is the process of applying invariant representations to specific situations, so now the flow goes from the general to the specific. For example, when you see a specific car on the road that you’ve never seen before, your mind is still able to recognize and label it as a car. You don’t need to process the complex sensory data from the car the same way you did the first time you saw a car. Unless something is unusual about the car that conflicts with your expectations, you probably won’t even consciously notice it.

You may recognize that there’s a downside to storing information in the form of invariant representations. That downside is a loss of precision because invariants are only approximations of an ever-changing reality. Consequently, with any invariant forms you’ll encounter situations where you have trouble matching a specific instance of reality into a corresponding invariant form. In practical terms this means you may encounter a person you have trouble classifying as male or female, a handwritten word you can’t recognize, or a film you aren’t sure should be labeled a comedy or a drama. But despite these drawbacks, invariant representations of reality are incredibly powerful and useful. Every letter, word, and idea you’re perceiving right now is in fact being classified by your mind into invariant representations you’ve already learned.

How we learn

Your mind is capable of learning both consciously and unconsciously, and it stores invariant representations at many levels. For example, you can store the invariant forms of Corvettes, cars, motor vehicles, transportation, and so on. As long as your expectations are met, this mental processing will usually be handled subconsciously. However, whenever something occurs which doesn’t meet your expectations, it will push through to grab your conscious attention.

Learning is what naturally occurs whenever your expectations are not met. When you experience something new where you don’t know what to expect, or when something occurs which conflicts with your expectations, your mind will strive to identify and store new patterns.

Your most vivid memories will be of those situations which on some level didn’t meet your mind’s expectations. Something unexpected occurred, something your mind couldn’t match with one of its previously learned invariant representations. When your experiences match your expectations, your mind will essentially discard the specific, low-level details of those events, and the memory will gradually fade into something fuzzier and less distinct. The experiences you remember best are those which conflict with the routine.

I think the reason your mind stores the unexpected experiences in far greater detail than the routine ones is to give it the opportunity to later process those memories into invariant forms. Your mind can’t figure out how to classify those experiences yet, so it just saves them for later. It stores those memories at a higher resolution than normal. Periodically you’ll reload those memories when something triggers them, and this gives your mind additional chances to form a match. You’ll experience some of your biggest a-ha breakthroughs when your mind finally classifies an old memory into a new invariant representation. For a traumatic experience, this may be perceived as an internal healing, since the mind can finally let go of the intense emotions. Or it could lead to a sense of victimhood. On the other hand, if your mind determines the best invariant representation for a batch of your experiences is to label you a perpetual victim, then it can just store the invariant victim pattern, and the specific memories that helped contribute to the identification of that pattern can be allowed to fade.

The essence of human intelligence

How intelligent you are — and how skilled you become at solving new problems and adapting to new circumstances — largely depends on your mind’s ability to store and process invariant representations. Intelligence is basically a matter of generalizing from specific experiences (learning) and applying those general patterns to new specific situations (anticipation). So you can say that becoming more intelligent is basically a matter of increasing the accuracy of your expectations under a wide variety of input. Another way of saying this is that the more intelligent you become, the less you’re surprised by reality. This doesn’t mean you know what’s going to happen, just that what does happen falls within your reasonable expectations. Consequently, if you were super-intelligent, nothing would really phase or shock you.

We don’t consciously have to learn how to learn, since we’re born with this capability. Our sensory input gives us the raw data to start processing, and from there we spend our entire lives generalizing from the specific and then applying our generalizations to the specific. The process never ends.

Ultimately we can trace all our knowledge back to our sensory input and the patterns we’ve generalized from that input. As odd as it may seem, we cannot solve problems that we cannot link to invariant representations. Even conscious reasoning relies on this process.

How to become smarter

Invariant representations are the building blocks of human intelligence.

Given the critical role of invariant representations, one route to greater intelligence is to increase your exposure to new experiences. The more unique experiences you take in through your senses, the more invariant representations your mind will create and store. This will provide you with a larger set of problem solving tools and a greater ability to adapt to new circumstances. You’ll begin to solve problems with ease that others find daunting.

Greater input variety not only allows you to learn more invariant representations — it will also hone your existing representations. Experience creates expertise.

Consider Leonardo da Vinci, considered a genius by any reasonable standard. He achieved competence in a diverse set of fields, including art, music, science, anatomy, engineering, architecture, and more. While many would say such diverse interests were a symptom of his intelligence, I think it’s more likely they were a key contributing factor. By exposing himself to such a rich variety of input, Leonardo’s mind would have created far more invariant representations than most people. Additionally, his mind would have been able to form many more links between these representations. This would have vastly amplified his problem-solving abilities. Invariant representations learned from the study of one field often have creative applications in other fields.

Exposing yourself to the same types of input over and over again won’t increase your intelligence much at all. You’ll merely satisfy your mind’s expectations instead of pushing it to form new patterns from new input. Routine is the enemy of intelligence. If you want to grow smarter, you must keep stirring things up. Push yourself to do that which you fear. Keep exposing yourself to new experiences, ideas, and input, and you will become smarter. Your intelligence is not fixed unless your lifestyle is fixed.

In any given field, there’s a great deal of myopia. People who work in that field get stuck in their routines, and they just don’t think very creatively most of the time. For a while the routine patterns may work just fine, but when the inputs shift slightly (which always happens eventually), those old patterns (i.e. the old invariant representations) become inaccurate, thereby increasing the chance of making errors in judgment.

Consider how the expansion of the Internet has impacted the world of business. Lots of people are missing the boat because their invariant representations are outdated, or they don’t have a rich enough set of invariant representations from other fields to be able to adapt to what’s happening. So they either avoid taking their businesses online, or they do it in a really dumb way that even web-savvy teens can recognize as plainly stupid. Meanwhile, those people who’ve been able to form more accurate and effective representations are able to intelligently leverage the Internet to take their businesses to new highs.

Recognize that all of our reasoning is done with our internalized, highly processed representations of reality, not with the hard facts of reality itself. Even our sensory experiences occur entirely within our minds. The more limited and inaccurate those internal representations are, the less intelligent we become. Consequently, intelligence is not a fixed state of being — it’s an ongoing process of learning and adapting to an ever-changing reality.

You’d be amazed at how often invariant patterns from one field can be applied to another. For example, I was able to improve my self-discipline by recognizing that building self-discipline is much like building muscle, so I applied the solution of progressive training to the field of self-discipline, and this helped me become a more disciplined person. (Two years ago I wrote a series of articles on self-discipline to explain the how-to aspects if you’re interested in learning more — I think they’re still the most popular self-discipline articles online today.)

How to become dumber

Intelligence-wise the worst thing you can do is fall into a rut where your input remains essentially the same day after day and where very little surprises you. This doesn’t mean that every day is strictly identical — it just means your current experiences are similar enough to past experiences your mind has already classified into invariant representations, so your general expectations are almost always being met and you aren’t been pushed to learn anything new. A good way to determine whether you’ve fallen into this pattern is to attempt to list how many salient experiences you can identify from the previous 30 days. Salient experiences are those that stand out in your mind, and you shouldn’t have to exert much effort to recall them. If the past 30 days seem like a fuzzy blur of routine days you can barely recall with barely a handful of memorable spikes, even if you were engaged in a lot of activity, it’s safe to say you’re stuck in a rut. This situation may be very common, but intelligence-wise it’s not very healthy.

Ironically you may become highly intelligent within a limited and consistent environment, but you’ll cripple your ability to adapt to new circumstances. As soon as a major change occurs — and change is inevitable — you’ll experience tremendous stress and will be weak in your ability to adapt to new circumstances.

The more new situations you experience, the greater your ability to adapt to ever-changing circumstances. For a long-term employee, being laid off may come as a serious blow. But for a long-term entrepreneur, losing a particular client is just par for the course. The entrepreneur has learned invariant representations which make it easy to add new income streams, while the employee may have much lower intelligence in this area. Similarly, people who interact socially with new people every day will develop much greater social intelligence than those who interact with the same people over and over.

Your challenge

Again, routine is the enemy of intelligence. Going through the same morning ritual, working at the same place, doing the same type of work, interacting with the same people, eating the same foods, watching the same TV shows, and otherwise subscribing to the same predictable patterns will in fact make you less intelligent. Routine is important for providing stability and security, but it should only provide the outer shell for tackling novel challenges each day. Push yourself to take in new input, the likes of which you’ve never previously experienced, and you will become smarter. Ideally you’ll want to tackle something new and non-routine at least once a day. Read a new book, listen to a new song, walk around a new location, meet a new person, eat at a new restaurant, play a new game, install new software — do something that provides fresh, new input to your mind.

Over the next several days, begin to consciously recognize how your mind uses invariant representations in everything you do. Notice the labels you assign to people, objects, and activities, such as boss, faucet, and paperwork. Notice what other labels you associatively link to those representations. Pay special attention to those representations that involve your identity. How do you label yourself? Begin to question some of those representations. Are they accurate? Could any of them be holding you back? How can you consciously improve upon those representations?