Algorithmic Culture is a new cultural phenomenon that has emerged in contemporary digital society due to the widespread application of algorithmic technology. By sorting, classifying, evaluating, and predicting people, information, objects, and behaviors, it profoundly influences decision-making processes, social structures, interpersonal interactions, and the creation and dissemination of cultural content.
 

I. The Essence and Definition of Algorithmic Culture

Algorithmic Culture refers to the cultural phenomena, social practices, and value systems formed by the widespread application of algorithms in society. Its core characteristic lies in the use of algorithms to rank, classify, and categorize people, information, objects, and ideas. This cultural form does not simply view algorithms as technical tools, but rather as a social entity that is both influenced by and, in turn, shapes social Culture.

From a historical perspective, algorithmic Culture is the product of the integrated development of "a new form of human civilization" and "digital civilization," and is the inevitable outcome of digital civilization’s evolution into the intelligent stage. It transcends the traditional notion of viewing algorithmic "code" and human "craft" as opposites, embodying the synergistic development and interdependence between algorithms and human society.
 

II. Core Characteristics of Algorithmic Culture

1. Dominance of Computational Rationality

At the core of algorithmic Culture lies the mindset that “everything—including humans—is computable.” It transforms various relationships, behaviors, and values within human society into computable data, which is then processed and optimized through algorithms. This computational rationality has not only impacted the economic sphere but has also profoundly altered the ways in which Culture is produced, disseminated, and consumed.
 

2. Information Reorganization and Knowledge Reconstruction

Through a chain of processes—from data capture and cognitive modeling to behavioral regulation—algorithms have reconstructed the logic of subjectivity formation in the digital age. They have not only altered the distribution of information but also reshaped the mechanisms of knowledge production, evolving the acquisition of knowledge from the traditional model of “people seeking information” to the intelligent model of “information seeking people.”
 

3. Cultural Convergence and Diversification Coexist

On the one hand, algorithms make cultural experiences more “tailored to the individual” through personalized recommendations; on the other hand, they lead to cultural convergence. As Kyle Chayka notes in *Filterworld*, algorithm-driven recommendation systems make our Cultures more alike, and our tastes and desires increasingly “do not belong to us.” The flip side of this “hyper-personalization” is “hyper-isolation,” creating what is known as the “information bubble.”
 

4. Value Embedding and Power Shift

Algorithms are not value-neutral technologies, but rather decision-making systems embedded with specific value judgments. By setting standards, allocating resources, and evaluating individuals through code, they have gradually evolved into a new form of power, possessing de facto regulatory authority. This shift in power has made algorithms the foundational operating rules and core productive tools of digital society.
 

III. Dimensions of the Impact of Algorithm Culture

1. Individual Level

• Algorithmic Self: Algorithmic technologies such as personalized recommendations help users construct an "algorithmic self." TikTok’s "For You" page uses user data to build an algorithmic identity, turning the platform into a space where users collectively discuss autism diagnoses and refine their sense of self.
 

• Cognitive Shift: Through frequent, targeted content delivery, algorithms shape users’ decision-making frameworks. By exploiting human weaknesses—such as the desire for instant gratification—they erode self-discipline, causing users to unconsciously lose control over their information choices.
 

2. Societal Level

• Crisis of Cultural Diversity: The algorithmic recommendation system’s extreme pursuit of a single optimization goal reduces the diversity of information users encounter, leading to a crisis of increasing entropy in cultural diversity.
 

• Exacerbated Social Polarization: Through seemingly neutral logic, algorithms selectively present the world, thereby reshaping people’s attention and trust mechanisms, which may amplify social inequality.
 

3. Cultural Dimension

• Transformation of Cultural Production: Generative AI reshapes content production models, facilitating a shift from assisted creation to autonomous generation.

• Transformation of Cultural Consumption: AI-driven virtual reality, augmented reality, and interactive technologies have fundamentally transformed the experience of cultural consumption. Readers can “step into” the scenes of a novel and interact with the protagonist; audiences can “touch” artifacts with their own hands in virtual museums.
 

IV. Challenges and Responses to Algorithm Culture

1. Key Challenges

• Information Silos: To maximize user retention, algorithms tend to continuously feed users content they “like,” effectively trapping them in “silos” composed of homogeneous information.

• Algorithmic Discrimination: By learning from historical data, algorithms often perpetuate or even amplify existing social injustices. In scenarios such as credit approvals and recruitment screening, they may implicitly discriminate based on characteristics like race or gender.

• Cultural Sovereignty Risks: If the values of the Chinese-speaking world are primarily disseminated through algorithms defined by multinational tech companies, our cultural sovereignty faces the risk of “technological colonization.”
 

2. Response Strategies

• Building Algorithmic Literacy: Algorithmic literacy is not merely "technical training" but must become a capacity for critical understanding—understanding how data is produced, manipulated, and used to influence our cognition and decision-making. This encompasses technical, critical, ethical, and practical literacy.

• Building a Healthy Ecosystem: We must approach this from the perspective of algorithmic Culture development, rectify algorithmic rules, guide algorithms toward doing good, empower national governance through algorithms, and ensure the people share in the benefits of digital civilization.

• Improving the Governance System: A governance framework comprising “ethical guidelines—industry standards—laws and regulations” should be established to clarify the boundaries of responsibility for all parties and foster a collaborative governance model.
 

V. Future Outlook

As a product of digital civilization’s evolution into the intelligent era, the future development of algorithmic Culture will place greater emphasis on human-machine symbiosis and humanistic care. We must transcend the subject-object dichotomy, transform our understanding of technology (algorithms), and establish a harmonious, symbiotic relationship with algorithms.

In this process, the philosophy of the “slow science” movement offers valuable insights. It emphasizes that scientists must take seriously the concerns and objections they typically dismiss as unscientific, and pay close attention to the ethical and social controversies raised by technology. This philosophy helps us pursue technological progress without neglecting humanistic care and social responsibility.

Ultimately, the healthy development of algorithmic Culture requires the synergistic collaboration of rationality, virtue, humanism, law, and institutional frameworks. It necessitates strengthening guidance over algorithmic Culture while ensuring the harmonious integration of human freedom, using advanced scientific and technological Culture to underpin digital civilization and guarantee the Sustainability of building a new form of human civilization.

Further Reading

• Original Wikipedia entry: Algorithmic Culture
• Related entries:
  • Digital Culture
  • Filter bubble
  • AI art
  • Cultural diversity