Early experiences inside any complex system rarely feel neutral. They feel adversarial—personal, intentional, and unfair. Beginners across domains describe the same emotional pattern: the rules seem opaque, outcomes feel skewed, and losses arrive with a speed that makes the system appear designed to exploit newcomers.
This common early misunderstanding is closely related to how people overestimate their influence on outcomes they don’t truly control. You can explore this idea in more depth in why early losses feel personal, which looks at how early feedback can distort judgment and create emotional biases.
This perception is so common that many people mistake it for evidence. If it feels rigged, they assume it must be rigged. This is one of the most predictable early-stage misinterpretations in any system governed by uncertainty. More details: https://seoulmonthly.com/잘-기능하는-시장이-왜-공정하게-느껴지지-않도록-설/
The conclusion is understandable. But it is usually wrong. What beginners encounter is not deception—it is exposure. The system reveals its structure asymmetrically. It punishes before it explains. It delivers outcomes long before it delivers context. And because humans are wired to infer intention from pain, early losses are interpreted not as signals of complexity but as signs of bias.
The Illusion of Control in Early Experience
A well-known cognitive bias that helps explain this pattern is the illusion of control, where people believe they have more influence over outcomes than they actually do. Even when outcomes are random or governed by chance, beginners often feel that their actions should directly determine immediate results, and when reality doesn’t match this expectation, the system feels hostile or rigged. Research on this bias shows it occurs because humans are naturally inclined to seek causal relationships as a way to make sense of uncertainty. This can lead to overconfidence, misattribution of outcomes, and emotional reactions when things don’t go as hoped.
For a concise explanation of this phenomenon from a psychological perspective, see the overview of the illusion of control, which describes why people overestimate their ability to influence events and how that affects interpretation of random outcomes.
The Three Things Beginners Always Lack
When someone enters a system for the first time, they lack three things simultaneously:
Past reference points
Understanding of distributions
Emotional calibration
Any one of these gaps is manageable. Together, they create the perfect storm in which normal outcomes feel abnormal and neutral processes feel hostile.
1. The Absence of Reference Points
Beginners experience outcomes as isolated events, not as points on a long curve. With no memory of past volatility, every result feels decisive. A single loss is not “one of many”—it is the loss. When outcomes are interpreted individually rather than statistically, randomness feels targeted.
2. No Understanding of Distributions
Most systems operate on uneven distributions. Losses cluster, wins are sparse, streaks are normal, and plateaus are expected. Early participation exposes people to the widest amplitude of volatility because they have no experiential filter. Experienced participants expect turbulence; beginners experience the same turbulence as betrayal. If the system didn’t warn them, they assume it must be hiding something.
3. No Emotional Regulation
New participants have not yet adjusted their expectations to the system’s feedback speed or intensity. Early feedback arrives too quickly and too bluntly. Without an internal volume dial, losses feel louder than they are. Over time, experienced participants learn how much weight each outcome deserves. Beginners treat every signal as urgent, every result as diagnostic, every setback as meaningful.
Why Neutral Outcomes Feel Like Targeted Punishment
This is where the idea of rigging takes root. The system reveals information before the user has the tools to interpret it. Pain arrives first; explanation arrives later—or not at all. Another source of the “rigged” feeling is beginners’ confusion between symmetry and fairness. People often expect balanced outcomes over short intervals and assume that effort should produce reward. When this fails to happen, misunderstanding turns into accusation. But fairness in complex systems is not about immediate balance; it is about long-term consistency. Systems are fair to distributions, not to moments—and beginners often aren’t yet tuned to that reality.
Why Experience Changes the Story
This is why experienced participants rarely describe the system as rigged even when they acknowledge that outcomes are harsh and uneven. They understand where the boundaries are, know which outcomes are noise and which are signal, and learn to separate emotional discomfort from structural reality. The early stage feels rigged because it is where misunderstanding is punished most efficiently. The system does not greet people gently; it exposes them. The discomfort is not a trap—it is a filter. Those who misinterpret it as malice leave early. Those who stay long enough to understand it stop calling it unfair.
In this sense, the feeling of rigging is not a warning about the system. It is a diagnostic signal about the user’s current level of understanding.
