ZIYAO LIN
How Not To Be Invisible
How Not To Be Invisible is an interactive installation that examines how contemporary systems of scoring shape visibility, access and social value.
Across education, employment, welfare allocation and digital platforms, individuals are continuously evaluated, ranked and filtered. These scoring mechanisms do not merely measure performance. They structure access to space, opportunity and recognition. Visibility itself becomes a conditional outcome of evaluation.
The installation translates this structural logic into an experiential environment. Participants enter a space populated by symbolic objects representing different forms of capital. They are informed that their “visibility score” will be calculated based on what they collect. Without clear guidance, hierarchy or explanation, participants must decide which objects are worth accumulating. Their score determines which spatial outcome they are permitted to access.
The result is binary. A score above a defined threshold leads to a celebratory and amplified environment. A score below the threshold leads to a muted and diminished space. The mechanism mirrors real-world systems in which complex lives are reduced to numerical thresholds, and acceptance or exclusion becomes automated.
In doing so, the project contributes to ongoing debates about algorithmic governance, institutional evaluation and the politics of recognition. It proposes artistic practice as a method for making abstract mechanisms perceptible and contestable.
2026.02.
Theoretical Framework
This project draws upon Pierre Bourdieu’s theory of capital as a structural framework for understanding how visibility is distributed.
Bourdieu identifies three primary forms of capital:
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Economic capital, referring to financial resources and material assets that are directly convertible into money.
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Cultural capital, referring to education, knowledge, taste and institutional qualifications.
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Social capital, referring to networks, connections and access to power through relationships.
Symbolic capital emerges when these forms are recognised and legitimised within a social field. It appears as honour or prestige, but functions as authorised power.
Within the installation, these forms of capital are represented through recognisable objects. For example, Economic capital appears through the US dollar and Bitcoin, signalling both traditional and digital forms of monetary value. Cultural capital is materialised through the diploma, a socially recognised credential that institutionalises knowledge and qualification. Social capital is expressed through the recommendation letter, which serves as a material proof of valuable relationships and allows them to be exchanged for opportunity. It also appears in the form of a VIP pass, symbolising access to exclusive networks, and through quantified digital approval such as the thumbs-up icon, which operates as a unit of online social recognition.
Reference to Documented Cases & Public Reports
The logic of scoring and capital accumulation often reinforces what is commonly described as the Matthew Effect, in which those who already possess advantage are further strengthened, while those in vulnerable positions become increasingly marginalised.
In the United States college admissions scandal, a billionaire family paid 6.5 million US dollars to secure their daughter’s admission to Stanford University. The case revealed how financial capital can be directly converted into educational opportunity. In the same investigation, admissions consultant Rick Singer was found to have misrepresented white clients as ethnic minorities in order to benefit from affirmative action policies. These incidents demonstrate how economic and social capital can be mobilised to manipulate institutional evaluation systems.
Media commentary has also noted that recommendation letters are frequently issued by elite institutions, thereby reinforcing educational inequality. In higher education applications, candidates with access to influential networks are more likely to obtain strong endorsements. Students from marginalised backgrounds, even when equally qualified, often lack access to such support. The process sustains a logic of relational privilege, in which opportunity circulates through existing networks of recognition.
University rankings further illustrate this dynamic. Quacquarelli Symonds operates as a for-profit organisation that not only publishes rankings but also offers data analysis and consultancy services to universities. Some studies have suggested that institutions purchasing consultancy services have subsequently experienced noticeable rises in ranking positions. For many international students, QS rankings function as a status symbol, operating as a contemporary halo effect attached to institutional prestige.
At the same time, scoring systems may intensify vulnerability among those already disadvantaged.
In 2021, lawsuits in the United States challenged the use of artificial intelligence systems that allegedly discriminated against low-income applicants who were eligible for assistance. For years, automated systems had been used to support major decisions affecting residents’ access to welfare. As one affected applicant stated, everything was reduced to numbers, and there was no possibility of human empathy. The system itself appeared insurmountable.
In the Netherlands child benefits scandal of 2022, tens of thousands of families, often with lower incomes or minority backgrounds, were falsely accused of fraud and forced into severe financial hardship. Some victims took their own lives, and over a thousand children were placed into foster care. The case revealed how automated fraud risk scoring could operate with insufficient oversight and devastating consequences.
In France, the welfare agency CNAF analysed the personal data of more than thirty million individuals, including applicants for government support and their household members. The algorithm assigned each individual a score between zero and one based on the estimated likelihood of receiving payments to which they were not entitled, whether through fraud or administrative error. These scores informed monitoring and enforcement procedures, often without meaningful transparency.
Together, these cases demonstrate how systems of evaluation and scoring do not merely reflect inequality. They can actively consolidate advantage and deepen precarity within existing social structures.
Spatial Setting
The installation is set in a space filled with scattered objects. These objects represent different forms of capital and systems of evaluation. Participants move through this environment and must search for items that may increase their chances of remaining visible within the system.
Visibility in the installation is directly linked to what participants choose to collect. The objects they gather determine how their presence is evaluated.
Game Mechanics
When entering the installation, participants are told that their “visibility score” will be calculated based on the symbolic value of the objects they collect.
More than fifty objects are placed throughout the space. Some increase the score, others decrease it. There are no labels, no instructions and no clear hierarchy. Participants must rely on their own judgement and experience to decide which objects might be valuable.
The experience follows a gradual rhythm. At first, participants are confronted with many objects and little guidance. Through exploration and clicking, they receive fragments of information. They begin to collect items strategically. As objects accumulate, their visibility score changes.
Once the collection phase is complete, the system calculates a final result. The participant’s visible identity is reconstructed according to their score.
The outcome is binary. Participants who score above fifty enter a bright and celebratory space with congratulatory sounds and visual rewards. Those who score fifty or below are guided into a quiet and minimal space, accompanied by negative voice-over messages.This mechanism reflects the structure of many real-world systems. In recommendation engines, visa applications, funding assessments, recruitment platforms and welfare allocation, outcomes are often reduced to a simple distinction between acceptance and rejection. Complex lives are translated into a numerical threshold.
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