Play involves taking resources that are normally useful and wasting them for fun. This might seem pointless, but it is only a waste if you believe the activity has no value. A more useful definition of playfulness is the ability to move lightly between different worlds. We all inhabit various worlds, like the business world focused on profit or the family world focused on connection. One can choose to stay in one world forever, or move between them with ease.

To be playful is to inhabit the world lightly and creatively. There's two different things really good at role shifting versus being willing to completely transform yourself and get yourself stuck in a role forever.

Thi notes that being playful means you do not get stuck in your roles. The world often rewards those who commit themselves entirely to a single, simplified role. However, true playfulness requires the flexibility to shift and transform rather than becoming trapped in a permanent identity.

Attention and value are deeply connected. What a person values is exactly what they will pay attention to. In games, the scoring system serves as the primary guide for this attention. It dictates what players should want and what they should care about during play.

The most important thing in my game design toolbox is the scoring system. It tells the players what to care about and what to want in the game.

Games are the art of agency. They operate within the medium of how we act and make choices. While some games provide vast freedom, others are effective because they strictly limit agency. Soccer is a primary example of this concept because it creates a unique challenge by taking away the use of hands.

The English language often connects the words play and games, but they are not the same thing. It is possible to be playful without a game, such as when you experiment with new ways to cook or approach your daily work. Conversely, you can play a game without being playful. A professional poker player might treat the game as a job they dislike, meaning they are playing a game but not engaging in play.

You can be at your job and starting to make up new stuff. You can be fucking around with new ways to approach your daily life or cooking. And you can also play a game, but it's not really play, it's work.

C. Thi explains that being playful means redirecting useful resources to activities that are valuable in themselves. These are known as autotelic activities. This involves using skills for the sheer pleasure of the action rather than for a specific goal. For example, a person might use their logical mind to solve a puzzle instead of using it to win an argument. This shift often looks like wasting time or resources for fun.

Normally I use this logical capacity to fix things or to argue with people or get something. But then sometimes I do a puzzle, and that's just exercising the logical capacity just for the sheer pleasure of doing it, often uselessly.

While society often views play as a waste of resources, the definition of waste depends on one's perspective. If life is only about creating goods and accumulating resources, then play appears useless. However, C. Thi suggests that the real waste is spending a life on production and ending up unhappy. Fulfilling lives are built on activities that an individual finds intrinsically valuable.

Playfulness is the ability to move lightly between different worlds. These normative worlds have their own rules and landscapes, such as the profit-focused business world or the expressive artist world. Many people get stuck in a single world and stay there permanently. However, a playful person realizes they can shift between these spaces and not remain trapped in one perspective.

Thi describes playfulness as inhabiting a world creatively. This includes the freedom to mentally change the rules of the environment you are in. It is about a certain kind of movement and flexibility. Rather than being stuck in a rigid way of thinking, a playful person can inhabit their world lightly.

To be playful is to inhabit the world lightly and creatively. To both be able to move between them and also be able to screw with them and in your mind, change the rules of the world that your soul is inhabiting.

Jackson notes that this description captures the essence of a playful person. It suggests a sense of dancing through different environments rather than being weighed down by them. This movement allows for a deeper sense of freedom within various social and professional structures.

Thi explains that creativity and playfulness do not always go hand in hand. Using the ideas of philosopher Bernard Suits, Thi illustrates how some activities focus on perfecting a specific skill rather than inventing something new. In sports like rock climbing, the goal is often to find the exact movement required for a task. This process is about refining a physical action for the pure enjoyment of it rather than seeking a creative breakthrough.

You are trying to perfect a movement and get exactly this movement exactly right. Get your body all in a line and you might know exactly what you are supposed to do. In a sense, that version isn't very creative, but it is like refining my movement and taking actions for the sheer pleasure of it.

In these moments, playfulness exists because the action is done for its own sake. However, it separates from creativity because the path is already known. The challenge lies in the execution and the refinement of the body, not in the creation of a new idea.

Scoring systems are all around us and they fundamentally shape what we want. There is a paradox in the modern world. Life is more gamified than ever, yet people are becoming less playful. In a game, the scoring system and the challenges provide a sense of freedom. However, in the real world, these same systems tend to constrain us and limit our choices.

Scoring systems tell us what to desire. I think the challenges in games, they give us freedom. In the real world, they constrain us.

Jackson defines agency through the lens of philosopher Carol Rovane, who describes an agent as an entity that considers reasons and acts upon them. While the technology world often views agency simply as the ability to do things, C. Thi approaches it as a medium for exploration. He treats games as the art of agency because they allow us to inhabit different ways of valuing and acting.

Many critics try to validate games as art by comparing them to movies or literature. They focus on scripts and characters but often ignore the elements of play and choice. C. Thi argues that games are like art governments or rule systems designed for fun. By choosing to play a game, we willingly opt into a specific structure of reasons and goals. A scoring system is one of the most powerful tools in game design because it dictates what a player should care about.

The heart of games wasn't that they told stories. The heart of games was they shaped your action so that actions, decisions and stories came out of you. Games work in the medium of agency.

Agency in games is not just about total freedom. Some of the best games are interesting because they strictly limit what a player can do. Soccer is defined by the restriction of not using hands, and games like Tetris or limit poker are compelling because they force players to make significant moves within a very small space of possible actions.

Agency doesn't just mean activity and freedom. Some games are really good because they hyper constrict your agency. Soccer is interesting because it takes away your hands. Tetris is interesting because you're trying to do so much with such a tiny action space.

This shifting of reasons is not limited to games. In professional roles like being a legal agent or serving on a hiring committee, individuals act based on the needs and values of a group rather than their own personal preferences. C. Thi explains that this ability to adopt a new reasoning structure is a fundamental part of how we function in various social and creative contexts.

When we enter a specific role, we often cancel out our normal reasons for acting. This process occurs in both games and professional life. For example, a teacher might have to set aside their personal liking for a student who shares their sense of humor or politics to remain fair. Thi notes that being fully authentic in a professional role can sometimes be detrimental. In a government office, you would prefer to be treated according to the rules of the role rather than the personal feelings of the official.

In games we're doing it for play and these conducts, we're doing it for duty or obligation. But John Dewey says that in a lot of the arts we take something we do in normal life and we concentrate it and crystallize it for beauty or interest for its own sake.

Games take this common human behavior of role shifting and make it visible. Most people inhabit different forms of agency throughout their day without thinking about it. They act differently at work than they do at home, but they do not always realize they are switching between different sets of reasons. Thi suggests that games help us see the water we are swimming in. Jackson points out that successful people are often very good at this shifting. However, a danger exists in becoming stuck in one hyper simplified role instead of moving through them playfully.

Games provide two distinct layers of agency. On one level, a specific game narrows focus, turning a person into a being dedicated solely to one skill like balance or calculation. On a broader level, the sheer variety of games allows for exploration. Thi explains that the enclosed nature of games and the clarity of their rules make it easy to shift between these different ways of acting. This freedom to choose between different types of play is a form of agency that is often missing from professional life.

In a lot of my work life, I don't have this choice. But for my break, I can choose. Am I going to play with yo yos? Am I going to run around the block? Each of these is a completely different kind of action and a completely different feel of action.

This clarity leads to a deeper discussion about the difference between incentives and values. Values are the core motivators that drive every action and choice. Incentives are external resources the world offers, such as money or an audience. While it is necessary to engage with incentives to gather resources, the danger lies in value collapse. This happens when the external score becomes the ultimate goal.

One frame of mind is to make enough money to do what you actually want. And the other frame of mind is just to be like, well, here's what I do. Here's the scoring system. I'm just going to max out on making money and not thinking about the thing it's for.

Maintaining a firewall between true values and external incentives is essential. Without it, individuals risk forgetting what their efforts were meant to achieve in the first place. This requires keeping the external world at arm's length so that the reasons for gathering resources always stem from actual values.

Willpower is often viewed as a form of grittiness, the ability to push through difficult tasks because of a long-term payoff. Jackson suggests that relying on willpower might indicate a lack of harmony between personal values and external demands. He compares this to the extreme discipline shown by figures like David Goggins, who wakes up at 4 a.m. to perform grueling physical challenges.

I think willpower is this sort of grittiness, despite maybe even clear incentives that says, I'm going to do something hard because in the long run, it's going to pay off. The people who require willpower are the ones who haven't found a way to harmonize their real values and what the world wants.

Thi offers a more practical view. While the idea of total alignment is romantic, everyday life still requires willpower for less exciting responsibilities. Even a philosopher who loves their work must find the internal strength to grade a stack of student papers at the end of a long night.

Thi introduces value capture as a core concept where rich, subtle, and developing personal values are replaced by simplified, institutionalized metrics. This shift happens when the incentives of an environment collapse into a single number. For example, a student may enter school with a genuine interest in learning but eventually refocuses solely on their GPA. Similarly, someone might join a social network to connect with others but finds themselves obsessed with likes or subscriber counts.

Value capture is what happens when you go to school out of an interest in learning, and you get focused on GPA. It is what happens when you go on social media to connect to people and you get focused on likes, or you start a podcast to get ideas, and then you become focused just on subscriber count.

The most concerning aspect of value capture is not that people are forced into it. Instead, individuals often enthusiastically and freely choose to be value captured because it is easier. The world provides a quick, easy tracker that everyone else understands, which makes it tempting to lose the plot of one's original goals. Jackson emphasizes that these oversimplified values eventually interfere with the fundamental goal of living a meaningful and flourishing life.

A central idea in economics and social policy is that well-being consists of satisfying an individual's expressed desires. This perspective aims to be non-paternalistic by respecting personal autonomy. However, this model overlooks the phenomenon of adaptive preferences. When opportunities are systemically limited, people often lower their expectations and adapt their desires to fit their restricted circumstances. This creates a risk where systems can reorient a person's will toward simplified, flattened values that actually diminish their potential.

The view is something like, well, we can't be intrusive. We have to let people be autonomous. We have to listen to what they want. This is sort of like the neoliberal late stage capitalism. But if I start to limit your opportunities, your preferences will adapt to the opportunities that are available to you.

This raises the difficult question of whether it is possible to have the wrong values. Rather than there being a single set of correct values dictated from the top down, C. Thi suggests that values must be tailored to a person's specific context and psychological profile. Values serve as a form of fitness for an environment. For instance, the value of friendliness is essential in a rural setting, but in a crowded city like New York, valuing privacy and respecting personal space becomes more appropriate for the environment.

You don't calculate the right values for you from the top down by thinking about some abstract conception of the good and then deducing it. You have to try them out and see if they work for you. Some values are suited for some context and some values are suited for others.

Values should not be seen as something simply picked out of thin air or handed down from an authority like the church or the state. While there is a common belief that we must choose our own values to find meaning, it is more accurate to say that values must be tailored to a specific person and their environment. This process requires a sensitive detection of one's own emotional signals. Jackson notes that while we have moved away from top down values, there is still a tension in how to find ones that are actually good.

You can have better and worse values. You can get the wrong values. But whatever the right ones are, they are deeply tailored to what you are. So it is less about choice and more about sensitive detection. It is a mixture of both invention and listening.

Thi explains that when someone relies purely on willpower to push through a situation, they might be ignoring important internal data. For instance, being miserable in graduate school is a signal that the pursued value is not leading to flourishing. Boredom and misery are forms of detection that reveal when a value is a poor fit for an individual.

The idea that authentic values come only from within, or that values from the outside are always alienating, is a limited view. Some frameworks treat values as too rigid and heavy, while others treat them as too thin and based on pure choice. Effective value formation involves soaking up ideas from the world while remaining responsive to how they actually feel in practice. It is not about sitting in a cave and making something up. It is about finding a fit between yourself and the world.

Learning to value things often happens through the guidance of others who help us see hidden layers of an activity. A person might start rock climbing simply for the physical workout. However, a more experienced climber might suggest focusing on sensitivity in the feet rather than brute force. This advice can reveal a new form of beauty, such as the delicate poetry found in one's own movement. This shows that we do not just invent our values from scratch.

A lot of the way we learn to value things is by learning from other people who guide us through activities. You suddenly learn that actually so much of the beauty on offer and so much of the value in this activity is something you never realized before, which is there could be delicate poetry in your own movement.

Thi explains that there is a middle ground between two extremes of value formation. One extreme is a top down approach where the world dictates your values. The other is a bottom up approach where you create values out of nothing, which is almost like an immaculate conception. The real process involves learning and negotiation. When values are not strictly imposed, we can take candidates for value from the world and then balance or reinterpret them for ourselves.

Pure top down is the world tells you your values and you take them on. Pure bottom up is make it up, immaculate conception almost. In between is something about learning and negotiation.

Taste is often viewed as a simple act of judgment. However, true taste is built on a massive amount of input and exposure. It is like eating a lot of different foods before deciding what is good. When developing taste in something like jazz, you cannot find your way entirely alone. You also cannot simply accept what an authority tells you. You need intense exposure and careful attention to many examples to eventually find your own way.

When you learn about something like jazz you listen, you learn, you let people point things and then you slowly start to also find your own way and refine your own tastes. You do it through this intense exposure and careful attention to lots and lots of examples.

Thi argues that the metrified world is stripping away the nuance of human values. Values like honor, courage, or loyalty are powerful because they are open ended. They do not have precise borders. This lack of precision allows for freedom of interpretation. In contrast, a metric like a subscriber count is unidimensional. It leaves no room for free play or personal meaning. Precise values often embody a closed minded spirit about what actually matters.

Metaphors serve a similar purpose by pointing at truths without strictly defining them. A metaphor might suggest that a soul is like the ocean without explaining exactly how. This meaningful inarticulateness is necessary when the world itself is fuzzy or when we are uncertain. Modern slang terms like vibe and aura reflect this same need. These words allow people to acknowledge something real that cannot yet be put into words. They represent a collective desire to sit with uncertainty rather than forcing a false precision.

Games allow for agential fluidity, which is the capacity to shift our focus and agency. This process begins with attention because value and attention are deeply linked. Whatever we value becomes the primary focus of our awareness. In games, the scoring system acts as a guide, helping the designer sculpt where a player directs their attention. Jackson notes that this training is not just about a technical skill but creates a whole new outlook and attentional focus.

The scoring system is a way for a game designer to sculpt your attention. Rock climbing is a great example. The goal is to go up, the rules are don't use any rope, and suddenly your attention has to be on tiny details of the rock and the way you balance. If you are inattentive to your balance on the rock, you will fall. That game is not only telling you what to pay attention to, but refining your attention by slapping you over and over again.

This dynamic appears in other disciplines as well. Difficult yoga poses serve as a tool for meditation because they amplify a wandering focus. While a person might not notice their mind drifting during seated meditation, they will immediately wobble and feel it if their focus wanders during a hard pose. Similarly, different game genres focus attention on different modalities. Deception games might force a player to stare at a face to read a person, or they might restrict talking entirely so that players must signal intent through board moves alone.

Thi warns that while these scoring systems are beautiful in games, they can be destructive when applied to institutions. This creates a lock-in effect. If a university only measures graduation rates, the entire institutional attention becomes hyper-focused on that single metric. This focus comes at the expense of things that are harder to measure, such as student happiness, wisdom, or ethical growth.

Scoring systems can give you the most beautiful part of lock-in and the most soul-deadening society-destroying parts of lock-in.

Recognition and perception are different ways of processing the world. Recognition involves applying a category to something and then stopping. It serves as the end of thought. Once you label someone as a business person or a coder, you assume you have all the information you need. Perception is different. With perception, you apply a category but then use it as a starting point to look closer at peculiarities and differences. It is the ability to keep looking further and further even after you have a name for something.

The difference between recognition and perception is that in recognition you apply a category and then you stop looking at the thing. The category is the end of thought. And with perception you apply the category and that helps you look at it and you keep looking further and further.

This explains why scoring systems feel fun in games but soul deadening in institutions. In games, players often maintain a playful and exploratory attitude. However, metrics in large institutions tend to promote a closed vision. They categorize things quickly and stop looking at the nuances. When we use fuzzy terms like interesting or rich, we are forced to deliberate and interpret. When we use mechanistic metrics like screen time, the process becomes automatic and loses its depth. Screen time is a poor category because it treats a child coding in Minecraft the same as a child watching low quality videos.

There is a fundamental tension between practical vision and aesthetic vision. Practical vision is driven by goals. It filters the world and ignores features that are not immediately related to a specific purpose. This is a survivalist way of seeing. Aesthetic vision requires stepping back from those goals to let the object lead. It allows attention to rove freely and discover new values that were not pre specified.

What aesthetic vision is, is you let the object take the lead and show you what there is to love about it instead of having your own goal. The more hyper clear the goal and the focus ahead of time, the more your vision seems to be closed and dismissive and non exploratory.

In games, the relationship between goals and the experience of playing is unique. Usually, people work hard to achieve a goal they care about deeply. In games, however, the value of the outcome is tied directly to the value of the process itself. This concept is known as striving play.

In normal life we struggle in order to attain some goal that we really want. In striving play we adopt a goal to get the struggle we really want.

Thi explains that in striving play, we do not necessarily care about the goal for its own sake. Instead, we adopt a goal specifically because it creates the kind of struggle we want to experience. This mindset can extend to other areas of life, such as exercise. Someone might start exercising with a narrow idea of the benefits, only to discover much more value in the process than they initially expected.

Modern frames of thinking often devalue the processes people follow. There is a common tendency to dismiss the importance of how things are done in favor of final results. This perspective makes it difficult to explore the connection between process and values. Thi notes that even the way we frame questions about these concepts can be influenced by a modern bias that looks down on procedural steps.

I'm worried that already adopts a modern frame that has crapped on processes too much.

A game is the voluntary attempt to overcome unnecessary obstacles. In normal life, people care about outcomes. If a person needs to get across town, they take the fastest route possible. However, in a marathon, the goal is to reach the finish line using only specific, prescribed means. Taking a taxi would defeat the purpose because the struggle is an intrinsic part of the goal.

To play a game is to voluntarily take on unnecessary obstacles to create the possibility of striving to overcome them. In practical life what we care about is the outcome in and of itself. If I am playing a game, if I am running a marathon, I have to get there by prescribed means. It only counts as crossing the finish line if I did it a particular way.

There are two distinct ways to approach a game: achievement play and striving play. Achievement players value the win itself. They do not cheat because cheating would disqualify the achievement they value. Striving players value the process of the struggle. For them, winning is a necessary constraint that makes the process meaningful.

Thi explains that he avoids reading strategy guides for board games even if they would help him win. Reading a guide would make the game boring by removing the challenge. This reveals a unique form of agency. A player can adopt a win oriented mindset during a game without actually caring about the win in a broader sense. They try their hardest to win simply to experience the pleasure of an interesting struggle.

I am adopting a win oriented kind of agency to have the pleasure of an interesting struggle.

Value in human life comes from the rich exercise of our physical and intellectual capacities. This idea stems from Aristotle and the game scholar Bernard Suits. Outcomes, tools, and resources are only useful because they allow us to exercise these abilities. While we often aim for a specific result, the real value lies in the activity and the process itself. Modern life often tries to persuade us that only countable outcomes matter. We focus on the money we make or measurements of our skills instead of the actual experience.

The process of skill refinement, even if I end up at most mediocre, the process of refining the skill is valuable in and of itself. How did we get to think that you had to look in piles of things that you made for the value?

Thi highlights the difference between a recipe and a dish. A recipe is a dead thing that records how someone once made something. A dish is a live thing that exists as an idea in a cook's head and changes every time it is made. Jackson notes that following a recipe is a trade off. It is easier to let someone else make the decisions to ensure a good outcome. However, real cooking requires tasting and adjusting based on the ingredients available that day. Following a fixed set of instructions simplifies life but removes the creative process.

The recipe is not the real thing. It has been engineered so you don't have to make decisions. You do often get a good outcome, but it is a very fixed outcome.

Following a mechanical recipe offers ease and reliability. It requires no experience and guarantees a predictable result as long as the ingredients are standardized. Jackson points out that people often prefer recipes because they are afraid to waste food or time. But this efficiency comes with a trade-off. When you follow a recipe precisely, you act as a robot rather than a cook. You lose the opportunity to engage your senses and make personal choices.

We have persuaded ourselves to turn into the restaurant mindset where we've turned ourselves into our own menial laborers. We follow the rest of it precisely in order to have a guaranteed good outcome, where instead we could invite our friend into the kitchen, make decisions together, taste together, and the outcome might not have been perfect, but we lived.

Thi suggests that true cooking is about developing the capacity to see a decision space. It involves learning how to adapt when ingredients change, such as adjusting for tomatoes that are too sour. Instead of being a laborer for a guaranteed outcome, you become present in the moment. Cooking becomes an act of living and connecting with others rather than just a task to be completed.

In games, beauty is found in the player rather than the object. Game designers shape the general path of action instead of every detail. This is known as process beauty. This type of beauty is often undervalued because it is difficult to measure with objective metrics. Aesthetic value is naturally subtle and varies between people.

Thi suggests that aesthetic value is really about the value of perception. Perception is a slow process. If a person wants to be efficient and hit a specific target, they should focus on recognition instead. A recognizer moves quickly by ignoring everything that seems irrelevant to their goal. This allows for fast optimization, but it only works if the ignored details have no value.

If you want to be really efficient at hitting some simple top target, you should be a recognizer and not a perceiver, because you will move quickly, you will ignore everything that is irrelevant, and then you will be able to optimize for your target. And that is great, as long as there is nothing of value in what you threw away.

When we prioritize efficiency, we become recognizers who move fast and ignore the world. Aesthetics require us to be perceivers. This means slowing down to see the details that metrics often miss. We lose something important when we only focus on what is easy to count.

The concept of autotelic living involves doing things for their own sake. It is a compelling philosophy for how to live and find passion. However, the idea of living a purely playful life can feel unrealistic. The philosopher Bernard Suits wrote about a future utopia where abundance allows for constant play. While the modern world is somewhat abundant, it is not a perfect utopia yet.

Great things are clearly not always playful. You do all kinds of things that suck and are hard to get to, either whether it be the aesthetic process you want or outcomes that are important.

Jackson notes that many important goals require hard work that is not always fun. Most people hope to move closer to autotelic activities in their careers. They want to find internal motivation while still managing messy external realities. The challenge is to see if a life driven by joy is incrementally more possible over time.

Every profession involves a grind. The challenge is whether an individual devotes themselves entirely to that grind or makes space for something else. Thi admits that his research on value capture grew out of his own experience falling into a career trap. He entered philosophy because he loved it, but graduate school introduced metrics that shifted his focus. In academia, success is often measured by status rankings and the number of articles published in top-tier journals. To succeed, one must often hyper-specialize and write technical articles within a very narrow domain.

I went in the course of my professionalization from someone who was deeply excited about philosophy to somebody who, by the time I left grad school, was grimly doing philosophy. I had to have a dark moment of the soul. I was saved by my impatience and my intolerance of boredom where I was just like, I cannot do this anymore. I have to do something else.

While a significant portion of academic life involves administrative tasks, teaching, and policy changes, Thi emphasizes the importance of carving out space for genuine interests. Even if that space only accounts for a quarter of his time, it allows him to treat his work as pure play. Having the freedom to explore strange ideas is a privilege that keeps the work from becoming purely mechanical. A previous version of himself would have thrown his entire life into the grind. Now, he recognizes that being one of the luckiest people in the world means getting to roam weird ideas for a small part of his life.

Metrics function as a technology that standardizes attention. While they provide clarity and portability across large groups, they often force people to justify their actions through what is easily understood by everyone else. This process can kill intuition and opacity. Scoring systems do not just discover a pre-existing agreement. They actually produce a convergence where everyone begins to value the same specific numbers.

Metrics are technology that standardize attention. Data is engineered information and metrics are engineered values. Public metrics get rid of intuition. They force us to justify ourselves in the cold light of general comprehensibility. They kill opacity.

A significant danger arises from how humans react to the presence of a metric. Even when a number is intended to be a simple or limited proxy, people tend to hyper-orient toward it. This creates a suction effect where the quantified measurement becomes the primary focus, and the original qualitative values are pushed aside. This happens even when the metric is known to be flawed or narrow in scope.

The history of the Body Mass Index serves as a clear example of this shift. BMI was originally designed as a rough epidemiological tool to look at nutrition shifts across entire national populations. It was never meant to be a precise health indicator for individuals. However, because it is a clear and accessible number, it has been transformed into a personal health scoreboard. People often forget its status as a rough proxy and begin to treat the number as the ultimate goal of their well-being.

When you put a metric in a space, everyone starts to care about it and hyper orient to it. It becomes a personal scoreboard and its proxiness is lost. People forget about the fact that it's this just really rough population level measure.

Thi argues that metrics are not inherently bad, but they are limited by their very nature. They are designed to measure things that are easy to count and recognize universally. For example, it is simple to track graduation rates or lifespans because the data points are clear and consistent for everyone. This clarity allows large scale data systems to produce significant results in specific areas.

The worry is that the basic intrinsic nature of metrics is very conducive to targeting some things and does it really well. It is no accident that large scale data collection systems have given us miracles like antibiotics because antibiotics lead to a highly measurable result.

However, metrics struggle with complex human values like wisdom, beauty, and friendship. These qualities are harder to quantify. In institutional efforts like diversity, it is much easier to count the number of people hired from specific groups than it is to measure a diversity of intellectual styles or backgrounds. This leads to a focus on the countable over the meaningful. Jackson notes that even health is often reduced to simplified proxies. When we have a rich concept like flourishing, we often replace it with a measurable substitute like heart attack rates or life expectancy. This creates a trade-off where easy-to-count data points drown out the quieter and more variable aspects of human life.

Thi explains that institutional metrics are designed to capture a specific type of knowledge. He distinguishes between qualitative and quantitative knowing. Qualitative knowing is rich and context sensitive. It is dynamic and meaningful but travels poorly between different groups. To understand a qualitative assessment, you need a shared background. Institutional quantification works differently. It identifies a context invariant kernel. This nugget of information remains the same regardless of the situation. By removing high context details, bureaucracies create something portable. This allows people from very different backgrounds to understand and aggregate information.

The fact that we fix the meaning of A, B, C, D in the letter grade and we hold it the same is what makes that information travel well and what permits automatic aggregation. Institutional quantification is socially powerful by design. The way it has been designed is that nuanced context and sensitivity have been stripped out of it. It is an artificially created easy communication mechanism.

Thi notes that this insensitivity to context is the source of its power. Values that require deep experience or context to understand are systematically removed. This trade-off is the defining feature of how large organizations function. The very thing that makes a metric socially powerful is the same thing that makes it blind to nuance.

Thi explains Lorraine Daston's research into the history and nature of rules. Daston identifies different types of rules that govern how people evaluate and count things. The first type is a principle. This is an abstract generalization that allows for exceptions. Following a principle requires discernment and judgment to know when the rule applies and when it does not. In creative writing, the rule to show rather than tell is a principle. Authors follow it generally, but they must also know when it is appropriate to break it. Wisdom in this context is knowing how to navigate these exceptions.

A principle is an abstract generalization that admits of exceptions and requires discernment and judgment to apply because you need to know when you might be in an exception case. The point isn't to throw out the rule. The point is that the rule should hold until it doesn't.

The second type of rule is a model, which functions like a role model. An example is the Rule of Saint Benedict, where one follows the example of a specific person. Like principles, models require expertise and judgment to apply. They do not work automatically. These types of rules often thrive in apprenticeship cultures where a student learns from a master over time. They are difficult to scale because they require teaching someone how to apply a rule within a specific context.

The third type of rule is a mechanical or algorithmic rule. These are designed to be applied unthinkingly and automatically with no exceptions. While many people believe these rules started with computers, they actually began about 150 years ago. Their purpose was to make labor fungible. By making rules explicit and removing the need for expert judgment, companies could hire and fire anyone regardless of their location or specific expertise. This system works best when inputs are standardized, such as the ingredients used in a global fast food chain. Thi notes that even mathematics requires non-mechanical judgment to decide which formula or procedure is right for a specific problem.

People thought that mechanical rules and algorithmic rules arose with computing machines, but they didn't. They arose about 150 years earlier in an attempt to cheapen labor so you didn't have to hire experts who had judgment. They make labor fungible. They make it so you can hire anybody and fire anybody because the rule has been made explicit.

Even a simple task like splitting a pie reveals the hidden complexity of our choices. There are many ways to define what is fair or equal. One might split a pie by weight to track nutrition or by angle to ensure it looks right. Another method is to let one person cut and the other person choose, which focuses on the feeling of equity between two people. Each of these procedures represents a different value system.

Half by angle is different from half by weight is different from half by deliciousness or appealingness. There is a complex choice of procedure. But if you mechanize it, then you lose those details.

Thi points out that the real world is lumpy and full of variation. Mathematical perfection works for a perfect circle, but real pies are irregular. Jackson observes that if everything were identical and lacked complex, overlapping details, there would be no problem with mechanization. However, because the world is full of nuance, applying a single mechanical rule often ignores the unique qualities of the things or people involved.

Metrics often rely on mechanical rules because they are easy for everyone to recognize. These rules tend to ignore subtle distinctions that require high levels of discernment. For example, the legal age to vote is set at 18. This number is a mechanical rule that does not actually track intellectual or emotional maturity. Instead, it is a compromise. We use a sharp line because the cost of individual bias would be too high if we tried to judge maturity on a case by case basis.

Thi explains that choosing between discerning judgment and mechanical judgment is really just trading one kind of arbitrariness for another. With discerning judgment, we risk letting in individual bias. With mechanical lines, we remove that bias but create sharp boundaries where life is actually fuzzy and complicated.

When you're switching between discerning judgment and mechanical judgment, you're actually trading off between two kinds of arbitrariness. With discerning judgment, you let in the individual bias. With mechanical lines, you shut that out. But you introduce instead the bias of arbitrarily sharp lines where things are fuzzy and complicated and gray.

The core of this issue is the trade-off of accessibility. When a procedure is made more accessible so that everyone can follow it, the system inevitably cuts off expertise and sensitivity. While this is sometimes a worthy compromise, we often fall into the trap of thinking mechanical metrics are purely objective rather than just a different set of trade-offs.

Our world is vast and science is incredibly complicated. This complexity makes it hard to distinguish between visionaries and posers from the outside. People often turn to conspiracy theories because they simplify the world into a version that is easier to understand and fit into their own heads. Because the real world is so complex, everyone is forced to specialize in narrow fields.

Transparency is frequently used to manage this complexity, but it essentially functions as a form of surveillance. It creates a leash for both bad and good people. While transparency prevents incompetent individuals from causing harm, it also prevents highly competent individuals from doing their best work. Everyone is forced to operate only within the limits of what the public can understand.

We limit the harm that bad and incompetent people can do, but we also limit what good and competent people can do. Transparency leashes both kinds of people, forcing them all to operate within the public's comprehension.

Expertise involves more than just running machinery. It requires seeing deeply into goals and grasping subtle values. The reason we visit a doctor is that they understand things we do not. However, we live in a metrics world that struggles with this depth. Thi observes that institutional trust is at an all-time low. Metrics are often used to scale trust, but they come with heavy costs.

Thi references historians Theodore Porter and Lorraine Daston. Porter teaches that large-scale metrics remove high context. Daston argues they remove expertise. These metrics emphasize only what everyone can see and recognize consistently. This leaves no room for context.

Thi shares a personal example from his university. The philosophy department faced budget cuts because it was labeled unproductive. The metric for productivity was research grants and expenditures. Since philosophers do not need labs or large grants to work, they look unproductive under that specific lens. The metric cannot make the contextual shift to recognize their value.

The reason I'm worried about this is because this is the answer for why metrics can't capture values. Because values are context sensitive, highly expert, and metrics by their nature target what is portable, consistent and accessible. What is legible.

Charity Navigator is another example of this problem. It was designed to identify which charities are wasteful. While transparency aims to root out fakers, it often harms people targeting important, non-quantifiable goals. Fakers often learn to game the system anyway. The result is a system that values what is legible over what is truly valuable.

The gap represents the distance between what is easy to measure and what actually matters. Metrics like Charity Navigator's throughput ratings illustrate this problem. For years, people used efficiency ratios to decide where to donate money. This system compares how much a nonprofit receives against how much it spends on its programs. This metric seems logical at first, but it creates a perverse incentive. It suggests that a nonprofit should not hire talented people or invest in internal research.

The gap is the gap between what is easy to measure and what actually matters. It assumes that a nonprofit is just there to redistribute resources and not to hire experts, not to make decisions.

Judging the actual efficacy of a charity is difficult. It requires a deep understanding of specific domains like housing or nutrition. Every field has unique complexities. However, accounting is the same for every organization. Throughput ratings are popular because they provide an objective and fast way to compare different groups. This approach highlights mechanical similarities like accounting while ignoring the important, variable work that actually solves problems.

Jackson asks how we can scale trust and points to Charity Navigator as a potential model. He sees it as an attempt to get around the problem of trust by finding a systematic solution. However, Thi clarifies that such examples are not about scaling trust at all.

It was an attempt to eliminate trust. That's what I was saying. Which is very different, by the way, trustless systems.

These models create trustless systems. They are designed to remove the need for trust rather than expanding it. This represents a fundamental shift in how we interact with organizations and information.

Transparency metrics often act as trust eliminators. Instead of relying on an expert to explain what is important within their domain, institutions use public ways of counting goods to ensure accountability. This shift forces organizations to stop using their expertise and instead focus on simple, easily accountable targets. For example, when the National Endowment of the Arts was put under oversight, success began to be measured by box office receipts rather than artistic merit. This turns complex value into something mechanically countable like page views or engagement hours.

The paradox of transparency and accountability is the whole reason we want experts and specialists is because we don't understand them. And then we're like, then you can only attempt to find the things that we can understand. That's not possible.

Thi points to two major ideas that define the modern world. The first is that data is essentially information engineered to travel and be understood by distant strangers. The second is that true trust begins in vulnerability and dependence, yet we try to replace that vulnerability with social contracts. While contracts allow for transactions between strangers at scale, they are a social technology designed to secure expectations rather than foster genuine trust.

Jackson asks how we can scale trust or defer to other specialists. Thi explains that the central challenge, which dates back to Socrates, is how a non-expert recognizes a true expert. Most people are experts in a tiny fraction of the world and non-experts in everything else. This creates an existential dilemma: we are surrounded by both true experts and fakers, but the ability to tell the difference requires the very expertise we lack. In response, we reach for hyper accessible metrics that imagine away complexity because we want the security of objectivity.

The problem is how does a non-expert recognize an expert? ... We're constantly having to overextend ourselves and become vulnerable and then we try to secure it with hyper accessible metrics which imagine away the complexity.

Trust is often invisible because it is so pervasive. It functions like water to a fish, something we swim in constantly without noticing. When people claim they do not trust anyone, they usually overlook the thousands of car mechanics and fellow drivers they trust with their lives every time they get on a highway. Identifying every person we depend on in a single moment can cause a sense of vertigo. It reveals that the dream of absolute intellectual autonomy, where one only believes things they have verified personally, is a fantasy.

Trust is so intense and deep that we forget how much we are trusting. Because trust to us is like water to a fish. We just swim in it all the time, so it becomes invisible to us.

The pursuit of science has actually made individual intellectual autonomy impossible. While the Enlightenment began with the idea of thinking for oneself, it created such a vast amount of specialized knowledge that no single person can verify it all. Instead of pure autonomy, we rely on a high error metabolism, which is the ability for reasonable people to verify and correct ideas over time. This requires accepting that objectivity is not a perfect shield against failure.

Modern objectivity is often defined as perspectival objectivity. This means a fact is considered objective if it can be recognized by anyone, regardless of who they are. However, objectivity and truth are not the same thing. Objectivity favors things that are easily countable and consistent across different viewpoints. Many important truths are subtle and require specific context or sensitivity to detect. When we prioritize metrics over these subtle values, we often do so to avoid the weight of personal judgment.

The reason that bureaucrats and politicians reach for numbers is to avoid responsibility. It is so good not having to make a judgment or exercise their discretion. They take themselves out of the apparent stream of judgment and say, it is not me, it is just the numbers.

This reliance on metrics offers a false sense of security. By narrowing decisions down to mechanical rules and easily countable numbers, people feel they can avoid the risks of trusting others. The cost of this security is a loss of sensitivity. If you only reason using what can be measured by a metric, you lose the ability to see the complex values that actually matter.

Technologies are often seen as neutral tools, but they actually encode value judgments and shape society in specific directions. Jackson points out that even though standardization can save lives, it also requires us to outsource some of our values. This challenges the common belief that engineers simply build tools and leave the choices to the users. Instead, the design of a tool often dictates how it is used and who can access it.

Technologies actually shape and push society into certain directions, often irrespective of what their designers and users hope for.

One classic example involves Robert Moses and the construction of bridges in New York. Moses designed overpasses to be lower than the height of a standard bus. This choice effectively kept lower-income people who relied on public transit out of certain areas. While a bridge seems like a neutral piece of infrastructure, its physical dimensions were used to enforce a specific social bias. Similarly, the printing press shifted power away from decentralized oral communication. Because it required significant capital, it centralized communicative authority in the hands of those who could afford the equipment.

Metrics are often viewed as neutral and objective, but they are built on specific systems of classification. To count something, you first have to categorize it. These categories are never truly neutral because they require humans to decide what is worth tracking and what is not. This process reduces the complexity of the world into manageable data points. However, the decisions about where to reduce that granularity are based on specific interests.

Every category involves decisions about where to reduce granularity. The U.S. Census is very interested in the difference between Asian and Latino categories, but it is uninterested in the difference between South Asian and East Asian. This has changed how people think about these groups in real life.

Thi points out that these biases even appear in medical record keeping. The classification manual for mortality statistics is highly detailed when it comes to urban accidents. It has separate codes for falling from a balcony, a commode, or an escalator. In contrast, rural accidents are grouped into just two categories: falling from a cliff or "other." This discrepancy reveals exactly what the system designers cared about most. We often forget these value judgments once the data is collected and turned into a metric.

Cost-benefit analyses also rely on these arbitrary starting points. To calculate the value of a national park, an analyst must assign a dollar amount to a single day of recreation. In the early 20th century, this was set at 14 cents per visitor. While the final report looks like a piece of objective science, the initial input was essentially made up to reflect a specific sense of valuation.

You run the analysis and it looks objective at the other end. But one of the inputs is just something we made up. It expresses our sense of valuation.

In cost benefit analysis, the discount rate is a critical number that determines the relative value of the future compared to the present. If this rate is set to zero, the present essentially loses all value because any small change today can be justified by massive effects in the future through compound interest. There is no objectively correct number for a discount rate. It is a value choice about how much the future matters compared to today. When this subjective choice is hidden at the bottom of a calculation, it makes the entire result look like an objective fact. Thi refers to this process as objectivity laundering.

Objectivity laundering is like money laundering. You take a subjective choice and then you pile on calculations. You take a subjective choice and then you pile on calculations until it looks objective.

This desire for clear numbers often stems from a longing for the simplicity found in games. Games are attractive because they provide a single scale for success, like a victory point system, where values do not conflict. It is tempting to export this model to the real world to avoid messy ethical questions. If a person convinces themselves that their metrics capture everything that matters, they can optimize for those metrics much more efficiently. This efficiency is only possible because they have removed the drag of worrying about all the other important factors they chose to ignore.

Ethics is about treating people well. Doing this properly requires deep attention to specific contexts and the sensitivity to understand what matters in a given situation. Thi draws on Aristotle to explain that practical wisdom is a form of perception rather than simple recognition. It involves being soaked in the moral complexity of a situation rather than just applying abstract rules.

If we expect ethics to be a mechanistic procedure that resolves debates, we will naturally focus only on features that are easy to count. This causes us to ignore more important factors that are harder to measure. When we rely on simple procedures, we lose the sensitivity required for true ethical judgment.

If you actually expect a decision procedure that will resolve ethical debates and you expect it to be mechanistic, then you will start to concentrate on those moral features that are easily countable and you will ignore the others.

Technology often relies on a ladder of abstraction, which can be seen in how maps are designed. A map might include elevation data because of historical military needs but omit sound quality or other sensory details. These tools are value laden. The solution is not to stop using maps, but to use them with an awareness of their inherent biases.

Technologists who build the structures of our world should avoid forcing a single map on everyone. Instead, they can focus on creating a variety of maps or building tools that allow people to construct the maps they actually need for their specific lives.

We have to use maps. But what we should hope to do is be aware that different maps reflect different values and choose our maps with care and sometimes make our own.

Many people in the technology sector want to solve political polarization by optimizing for agreement. They create algorithms that boost content accepted by people on both sides of a divide. They often believe this approach is value neutral. However, this method explicitly favors politically centrist views and ignores the complexity of moral progress.

Imagine you went back to 1830 America where half the population still believes in slavery and then you had your bridging content moderation algorithm that boosted the things that everyone both sides agreed with. That is a very value laden, very choicey.

There is a recurring fantasy in the tech world that it is possible to improve the world without making difficult moral or political decisions. Thi points out that some developers hope to change society for the better while avoiding complicated thoughts about what better actually means. This perspective fails to recognize how deeply values are woven into every technical choice. Jackson notes that while some AI labs now discuss ethics, the broader challenge is to be more thoughtful about where values are hidden. Any action taken to change the world will inevitably alter the value landscape in a significant way. Truly making the world better requires being careful and making explicit political choices rather than hiding behind a facade of neutrality.

Coordinated communication requires groups to make collective decisions about what information to ignore and what to track. This process involves weighing the advantages and disadvantages of shared concepts and data points. It is a fundamental question of how we coordinate together.

There is a significant need for more belief in the concept of play. Play and humility are deeply connected. When people optimize for a metric, they operate under the assumption that they already know exactly what is important. This mindset leaves no room for discovery or for realizing what might have been missed.

The attitude of optimizing for a metric encodes behind it the attitude that we know what's important and we just need to max out for it. There is no process by which we might wander the world figuring out what we've missed.

The spirit of play represents a form of humility. It encourages trying new things, even if they appear strange or silly. By embracing play, individuals remain open to being surprised by the world rather than just maximizing for a pre-defined goal.

Professional success can lead to a dangerous level of overconfidence. When people start listening to you and treating you as a senior figure, it becomes easy to trust yourself too much. Thi counters this by intentionally engaging in activities where he is a beginner. He brings strange toys like yo-yos and spinning tops to play with other people. This practice reminds him that everyone is just a clumsy and playful human being.

I can start to trust myself too much. I can start to become overconfident. The way I remind myself of the fact that we are all just clumsy, playful, idiotic mud things these days is I bring really weird toys. I have got these really silly spinning tops and I play them with people and fail.

Doing something difficult and seemingly pointless with others creates a unique sense of humility. It helps to be soaked in the oddity of an activity where you do not know exactly what it is for. This process of exploration with others serves as a constant reminder that no one knows everything about anything.

There is something really weird about doing something dumb and hard that you are bad at with other human beings. Being a beginner and being soaked in the oddity of it reminds me that I don't know much about anything.