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Grinding in video games and real life

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What is grind in video games?

Grind is a process of slowly getting valuable resources (be it experience points or loot) by repetitive and often simple tasks in video games. Usually, the goal is to make the future gameplay easier. In games that are centered around grind, it is usually the only way to progress. It has been present from the beginning of gaming but has become more widespread with the popularization of online RPG games because of their leveling systems and competitive elements. 

It is highly criticized by gamers around the world for making games boring and work-like, yet many people specifically choose to play grind-heavy games. The reason might be because they find simple repetitive tasks relaxing and distracting from real-life problems, as a form of escapism.

Everyone will likely have to grind at some point to prevent gameplay from getting too difficult, which quickly becomes an inescapable habit. Later, gamers might apply grinding even to games that do not require it. Interestingly enough, grinding early on can also make the late-game boring because it can become too easy, which can diminish the fun of playing the game.

So grind is not always a necessary process and can be either minimized or avoided entirely: sometimes, the need for it exists only in our mind. But is it just a question of habit, game design, or is there any other reason for us to grind?

Why do we do it?

Let’s outline the three reasons we have mentioned above: relaxation, habit, and risk minimization (where risk is a combination of the likelihood of failure and consequences of failure). Using these reasons, grind can also be classified into three categories: distractive grind, automatic grind (habitual or natural grind), and risk-minimization grind.

We have already mentioned that distractive grind is done to escape from everyday problems. Although it looks like the other types of grind on the surface (killing monsters, looking for loot, gathering resources), it has a different goal: a regular video game grind is done as a preparation for another task, while distractive grind is independent of any other tasks and is done to change focus from real life to some simple repetitive task. In fact, it perfectly fits the criteria of escapism -- a distraction from unpleasant reality, especially by seeking entertainment or engaging in fantasy -- both in its goals and approaches. A process of distracting from stressful situations is not problematic in and of itself because it can either be a mechanism of coping with stress or a method of procrastination. A coping mechanism is generally not a bad thing and a method of procrastination is only a symptom of a problem, not its source. Hence it is ultimately a different process that simply shares similarities with the other types. It is closer to video games themselves because of them also being a form of escapism which might be why some video games are built entirely around grind. However, analyzing its effects would be equivalent to analyzing the effects of video games, which is outside of the scope of this post so we will mostly ignore distractive grind later. 

Automatic grind has the same goals as the risk-minimizing grind. The only difference is that automatic grind is an unconscious reaction. Recent studies support the notion that intuition and habits can help someone make rational decisions based on prior experience but much faster than using logic. It means our automatic responses (habits) are simply logical conclusions made by our unconscious and automated for more effective use. Hence its reason (risk-minimization) and effects (decreased efficiency at the beginning of the task and decreased risk at the end of the task) are the same because they share the same goal and process. For example, one might have learned to excessively grind in Diablo and did it out of habit in Subnautica. Thus, both risk-minimizing and automatic grind are essentially the same thing so we will not distinguish between them later on.

Grind as a risk minimization technique is quite logical in high-risk situations such as the final boss in video games mentioned above or in rogue-like games where failure means losing all progress. However, it can make the entire task extremely boring if applied excessively, especially when risks are overestimated like in the Subnautica example. People apply this kind of grind even in games and situations not designed for it and so it is important to find out why. It can either be an evolutionary mechanism, a personality trait, a habit from prior experience, or a combination of them all.

As an evolutionary mechanism, allocating more time to prepare for solving most problems (similar to grinding before facing the final boss to get stronger) made sense before humans lived in a safe society because the risks for most actions were high and failure could easily result in death. Following the same logic, our fear of the unknown could trigger grind as a defensive mechanism whenever we are in a new context and feel lost; for example, when we are trying to acquire a new skill.

It is likely that our modern culture, especially academical, is influencing people to adopt perfectionist and atychiphobic tendencies, both of which force people to overestimate risks. It could explain why many gamers choose to grind even without prior experience with grind in video games.

Grind Classification

Type of grind by its reason / Type of grind by its effects

Distractive

Risk-minimizing

Normal

Conscious coping with stress

The actual risk is high

Problematic

Procrastination

The actual risk is low

How does it affect our day-to-day life?

Games have always been an exaggerated parody of real-life so it’s not surprising that we tend to grind outside of gaming. But real life does not have any loot to find or monsters to hunt, so let’s generalize the definition of risk-minimizing grind first to help us apply it to real life: it’s a process of postponing the task to take time to prepare for it. For example, we might postpone fighting a boss to earn enough experience or gear. In real life, we can postpone taking an exam to prepare for it. In both situations, grind is a logical solution.

However, it is often misused either out of habit or because we got into an unknown field where we cannot analyze how hard the tasks are. In such cases, our fear of the unknown kicks in, forcing us to overestimate risks and grind. That is the reason people know not to grind in fields they are confident in but resort to grinding whenever they get into a new field. For example, when one knows that excess preparation is not necessary to start working out, he still might not apply the same strategy to learning programming. As a result, he can start grinding and make the entire process ineffective and boring, which can lead to hundreds of hours procrastinated and even anxiety disorders developed in the worst case. 

Of course, perfectionists are more vulnerable to grinding as we have mentioned above but no one is truly safe from it because of the fear of the unknown, for which grinding is the most natural solution. Even though unnecessarily grinding once is not a problem, constantly relying on it will easily drain the energy from the most motivated people out there. Let’s take a look at some examples.

Situations with excessive grind

Trying to learn all of the material before attempting to do homework on it. While it’s logical if learning beforehand is a part of a lecture, we can work more efficiently by learning during practice without risk because homeworks can be attempted and errors fixed until all necessary knowledge is gained.

When behind on a few of the classes at a school/university, postponing doing assignments to go over all missed content. It sounds like a logical solution but without getting results for the work (results being the actual task being worked on and parts of it finished), it can quickly tire the person out and force him to procrastinate, which can greatly extend the grinding period and make the learning process a lot less effective.

When one wants to learn programming for the first time and buys a textbook on it. He might spend weeks reading it but never actually getting to work. In the case of programming, it is quite rare to work like this. Understanding programming without tons of practice is impossible, which is why most online programming courses (Codecademy, udemy, etc) are centered around practice.

A similar effect can be reached if a programmer tries to begin working with new technology by reading most (or all) of the documentation. All interest will be lost in the process, and procrastination will kick in very quickly. Especially with calendars

When one is learning a new language and tries to begin by memorizing theory or excessive vocabulary. The more effective way would be learning only the most necessary basics and focusing on in-context practice or something as close as possible to it (for example, italki, online games, or something similar when one can speak with real people)

When one has never worked out and tries to start: one might try to learn as much as he possibly can about exercises and weights before getting to practice, which can result in him completely abandoning the original task due to the sheer amount and complexity of knowledge he tries to learn.

What can we do to prevent it?

First, it is important to say that risk-minimizing grind is not the same thing as procrastination. It can be a source of procrastination but never the result of it. Also, not every simple repetitive process is necessarily the problematic risk-minimization grind and not every risk-minimizing grind is a simple process. Some simple repetitive processes are the escapist grind, and others can hardly be compared to video game grind at all.

There is a lot of advice on productivity floating around: start small, split the problem into subproblems, allocate a certain amount of time to solving the problem, etc. All of these methods are essentially aimed at minimizing a task at hand, getting us results quicker, and lowering our risk estimates as a result. However, it does not necessarily eliminate grind. We can still spend most of our time preparing to solve the task if we follow these methods. In my personal experience, I split my grind into subtasks and used pomodoro to manage work & rest time. Even though this strategy can be useful in the beginning, grind will eventually lead to procrastination and boredom. So eliminating unnecessary grind is not about starting small or dividing the problem -- grind is not about the amount of work but the order we do it in.

In programming, we have a concept called lazy evaluation. In simple terms, it is a process in which a program does not do all of the work at once and only does what is required of it at the moment, postponing any unnecessary calculations for later. For example, when we open youtube’s home page, it shows us some recommendations. Then we scroll and it shows us more. Youtube does not load all recommendations at once. It only loads a small number at first and loads more when the user scrolls down. This way, the program postpones its work until more recommendations are absolutely necessary. If Youtube did not do this, loading its home page would either be extremely hard or entirely impossible. If we apply the same strategy to working out, the only things we need to grind are safety protocols and the most basic exercises. The learning of other, more specialized facts and procedures, can be postponed until they become indispensable. The same applies to schoolwork: only learn the topics absolutely required to complete the current task and only learn them as you are working on the task, even if you still lack the prerequisites at the moment. The general approach is to assess the risks of making a mistake during the task, and if they are low -- immediately begin working on the task, postponing all preparation until it is necessary. In simple terms, high risk requires postponing work until you are ready, and low risk requires postponing preparation until you need to learn something to complete a part of the work.

It can be tricky at first, but most of the time only some specific pieces of prior knowledge are required to solve new problems. Programmers do that all the time: they do not learn everything about websites before creating one. As mentioned before, they start with the simplest prototype using their prior knowledge and only google things they need at the moment to implement the next small piece of functionality. This strategy prioritizes practice which is a proven most effective way to learn. It allows us to get results early; And constantly earning small rewards is an essential part of staying motivated for work, which is exactly why video games can be so fun -- they keep rewarding us for our effort, making us as addicted to the gameplay as mice in the Skinner box

This strategy has also proved to be effective in education. For example, why do we learn physics three to four times from the beginning of school until the end of our bachelor's degree? We might start learning it in middle school with simple factual laws and minimalistic formulas. In high school physics, we apply all we know from elementary algebra and trigonometry. Then we apply calculus to understand the same concepts but at a much deeper level. And finally, if we pursue a technical degree, we might take physics again but with applications of various forms of mathematical analysis and abstract algebra. This general path is applied all over the world to teach physics for a reason: it is one of the most effective ways to keep students at least moderately interested and help them understand concepts that seem too complex if tackled for the first time. So if there is any general strategy for learning anything without giving up early -- it’s lazy evaluation!

Of course, this process is not perfect. It creates the so-called knowledge debt -- a knowledge we would have gotten if we have learned the entire topic. It can be necessary later on but we sacrifice it for early rewards. However, we must still consider the knowledge debt every time we apply lazy evaluation because otherwise, we will end up with a large number of small pieces of unstructured knowledge that we will not be able to apply effectively. Yet addressing the knowledge debt is much easier after we have already studied some of the topic and its applications because we know exactly why we need the topic (gives motivation) and we already understand some of it (decreases difficulty). For example, if the topic is the prerequisite for a concept we were trying to learn, then this concept is the application of that topic.

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