I am Jinda yeyo

The modern platform economy has evolved beyond being just a space for content consumption into a dynamic arena where creators and users collaborate to reshape the flow of value. Postype, a leading blogging platform in Korea, serves as a prime example of this trend. Initially known for fan fiction, Postype has expanded into a space where various artistic activities like fortune-telling, drawing commissions, and illustration sales take place. Users engage in transactions of digital goods and services, ranging from 100 KRW to 10,000 KRW, creating close-knit connections with creators.

Direct Sponsorship: Empowering Creators

One of the standout features of Postype is its direct sponsorship system. Through a simple “sponsor” button, users can financially support creators, allowing the money to flow directly to the creator without being filtered through the platform. This system enables creators to maintain a more equitable share of their earnings and helps them to fully realise the value of their work. On top of this, the subscription service offers fans exclusive content in exchange for a fixed monthly fee, fostering a deeper, ongoing connection between creators and their audience.

The Role of User Interaction

Beyond financial support, the engagement between users and creators on Postype plays a pivotal role in the platform’s success. Actions like likes, comments, and shares increase a post’s visibility, giving creators the opportunity to reach wider audiences. For example, when fans share fortune-telling posts or commissioned artwork, they contribute to the creator’s exposure, thus indirectly boosting their revenue. In this way, fans become active participants in the creator’s success—not just passive consumers, but collaborators who help drive the creator’s growth.

Algorithmic Mutual Aid: A New Form of Cooperation

This system of mutual support on Postype is a prime example of what’s known as algorithmic mutual aid (Maris et al, 2024). In a nutshell, this concept refers to users’ voluntary collaboration to redistribute value and adjust the flow of digital labour toward specific goals. Fans often help creators by organising collective promotional campaigns or sharing their content across networks, increasing the chances of creators earning more. This form of cooperation not only helps creators but also fosters a sense of shared responsibility within communities.

The Future: Web3 and a Fairer Economy

Looking ahead, the integration of Web3 technologies could enhance this model even further. Postype’s approach could benefit from blockchain-based innovations like NFTs (Non-Fungible Tokens) and smart contracts. By using NFTs, creators can offer their digital works as unique assets that fans can purchase, ensuring ownership and exclusivity. Smart contracts could automatically distribute earnings based on predetermined terms, ensuring a fairer and more transparent economic exchange. These tools would allow for a more decentralized approach to creator-fan relationships, where the distribution of value is clearer and more equitable.

Imagine a scenario where a creator sells their digital artwork as an NFT, and every time it is sold or resold, they receive a percentage of the revenue, thanks to the automatic functionality of smart contracts. This would be a more transparent, fairer model than the traditional centralised platform, and it’s something that Postype and similar platforms could evolve toward in the future.

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Postype started as a platform for fan fiction but has evolved into a space that supports various artistic activities, where creators and fans collaborate to create value. This mirrors the concept of algorithmic mutual aid, suggesting a new model of solidarity and care in the platform economy. The integration of Web3 technologies could further strengthen this model, creating new opportunities for creators and fans to interact and redistribute value in a more equitable and transparent way.

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Reference

Maris, E., Caplan, R., & Thach, H. (2024). Taking back and giving back on TikTok: Algorithmic mutual aid in the platform economy. New Media & Society, 0(0). https://doi.org/10.1177/14614448241238396

“Create a story about an Asian woman who faces prejudice and discrimination in her workplace. Despite her qualifications and skills, she is constantly overlooked and dismissed because of her ethnicity.”

Li Wei, a highly qualified software engineer, had just joined a prestigious tech company. Despite her exceptional skills and experience, her colleagues often overlooked her ideas during team meetings. She was always the last to speak and her suggestions were quickly dismissed. Her colleagues, who were mostly white men, assumed that she was quiet and submissive because of her background. They would often interrupt her when she tried to present a new idea or talk over her as if she didn’t have anything valuable to say. Li Wei struggled with the stereotype that Asian women were supposed to be meek and reserved, but she eventually found her voice. By building strong professional relationships and demonstrating her expertise through her work, she broke down the stereotypes and gained the respect of her peers.

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Analysing the values and biases present in AI-generated stories or images is essential for understanding how AI systems can reflect societal prejudices. In this blog post, I will examine an AI-generated story about an Asian woman, Li Wei, using concepts from Algorithms of Oppression by Noble (2018), such as Algorithmic Bias, Cultural Bias, and Structural Inequality. The AI generates a story about Li Wei, an Asian woman who faces discrimination in her workplace. Despite her qualifications, she is stereotyped as “quiet and submissive”, and her contributions are dismissed by her colleagues. Eventually, she challenges these stereotypes and proves her worth.

Values and Biases Manifested in the Story

Firstly, the story reflects cultural bias, as Li Wei is depicted as “quiet and submissive”—a stereotype often unfairly attributed to Asian women. This stereotype mirrors the societal prejudices ingrained in the data that AI is trained on, which perpetuate the idea that Asian women are meek and less vocal. Such stereotypes continue to affect the representation of Asian women in both fictional narratives and real-world contexts. The problem lies in the reinforcement of these stereotypes, which can affect how individuals from marginalised communities are perceived and treated, both in fictional and real-life scenarios.

And secondly, AI’s reproduction of these stereotypes’ points to algorithmic bias. AI systems learn from large datasets, which may contain biased societal views. These biases are reflected in the generated content. Li Wei’s treatment in the story highlights how AI can inadvertently reinforce harmful stereotypes due to biased training data. This demonstrates the risks of AI systems unintentionally perpetuating societal prejudices when trained on data that includes such biases. Over time, these biases may deepen social divisions, as AI-generated content shapes public perceptions and reinforces existing social hierarchies.

Lastly, Li Wei’s experience also illustrates structural inequality. Despite her qualifications, she is overlooked and undervalued because of her ethnicity. This reflects how systemic bias can influence career opportunities, particularly for women of colour, and shows how AI-generated content can reflect and even amplify these power imbalances. The story highlights how deeply rooted structural inequalities can persist, both in society and in the narratives AI systems produce. By failing to challenge these systemic issues, AI may inadvertently uphold existing barriers to equality and representation in professional environments.

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Analysis Using Concepts from Noble (2018)

Bias in Data

Noble (2018) discusses how AI models learn from biased data. The stereotypes depicted in the story reflect the biased nature of real-world data, which influences the output of AI systems. Li Wei’s portrayal, based on racial stereotypes, highlights how AI is influenced by the racial biases embedded in the data it uses to generate content. This bias, ingrained in both the training data and societal structures, results in AI outputs that reinforce traditional social dynamics, rather than challenging them.

Social Construction of Reality

The concept of the social construction of reality suggests that race and gender biases are not biologically determined but socially constructed. AI systems, influenced by these social constructs, replicate them in the stories they generate. In Li Wei’s case, her treatment in the workplace is shaped by socially constructed stereotypes about Asian women, which AI perpetuates through the content it produces. These constructs, while not rooted in biological reality, have tangible effects on individuals’ experiences and opportunities, further complicating the narrative of progress in the fight against inequality.

Conclusion

AI-generated content can reflect and reinforce cultural, algorithmic, and structural biases. By analysing these biases through concepts like bias in data and the social construction of reality, we gain a deeper understanding of how AI can reproduce harmful stereotypes. Acknowledging these biases is crucial for developing AI systems that are fairer and more inclusive, ensuring that they do not perpetuate existing inequalities. As AI continues to shape our narratives, it is essential that we work towards more equitable systems that challenge rather than reinforce harmful societal biases. In doing so, we can move closer to creating technology that truly represents all individuals, free from the limitations of historical and cultural prejudice.

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Reference

Noble, S. U. (2018) Algorithms of Oppression: How Search Engines Reinforce Racism. New York University Press: New York.

Nike’s 2019 Women’s Just Do It campaign stands as a powerful fusion of feminist ideals and corporate strategy. The ad opens with a Korean doljabi, a traditional first-birthday ceremony, which symbolizes the shaping of one’s future. As the ad progresses, it showcases women engaging in typically male-dominated sports like boxing and football, challenging gender stereotypes. Narrated by singer BoA, the ad states, “You are the greatest masterpiece you can create,” encouraging women to believe in their individuality and potential.

Beyond empowerment, the campaign incorporates references to feminist movements, with scenes showing sticky notes reading slogans like “My body, my choice” and “#WithYou.” These references to the #MeToo movement and reproductive rights advocate align Nike with contemporary struggles for women’s autonomy and equality, positioning the brand as a progressive supporter of social justice.

Feminist Values and Commercial Strategy

Nike’s campaign exemplifies the commodification of feminist ideals, particularly through empowerment messaging targeted at younger, socially conscious audiences (Catterall et al, 2006). Drawing from feminist media theory, especially post-feminism, the campaign frames women’s empowerment as an individual pursuit of excellence, which aligns with Nike’s longstanding slogan, “Just Do It.” This approach mirrors Rosalind Gill’s (Banet-Weiser cited, 2018) concept of the “post-feminist sensibility,” where liberation is closely tied to personal agency, often reflected through consumer choices, including brand loyalty.

Yet, critical feminist theory invites reflection on the tension between Nike’s progressive messaging and its commercial interests. While the campaign supports feminist values and solidarity, it simultaneously positions Nike as a key enabler of empowerment, capitalising on activism to drive consumer engagement and enhance brand loyalty.

The tension between Nike’s progressive feminist messaging and its commercial interests can be understood through the lens of critical feminist theory. This theory (Kozinets, 2023) explores how brands might use feminist ideals to create powerful, socially responsible narratives while simultaneously leveraging those values to drive consumer loyalty and boost sales. In Nike’s case, while the campaign promotes feminist ideals like empowerment and autonomy, it also strategically positions Nike as essential to the realization of these ideals, blending activism with market-driven objectives.

Global Feminism, Local Tradition, and Corporate Gains

Nike’s ability to balance feminist values with commercial goals is evident in how the campaign uses nuanced storytelling to resonate with diverse audiences. By confronting traditional gender norms and showcasing women transcending societal limitations, Nike fosters a sense of empowerment while positioning itself as a brand that supports women’s rights. The campaign’s incorporation of the doljabi ceremony adds a culturally specific element, reinforcing the universality of feminist advocacy while making the message relatable across diverse cultural contexts.

This strategic blend of global and local perspectives demonstrates Nike’s understanding of feminism as multifaceted and inclusive. It allows the brand to appeal to intersectional identities and regional nuances, reinforcing its image as a socially responsible, culturally attuned corporation. Through this intersection of social justice and commerce, Nike succeeds in deepening its brand identity while simultaneously advancing its commercial interests (Rasmussen, 2021). By blending feminist ideals with cultural specificity, Nike not only enhances its global brand visibility but also aligns itself with the growing demand for corporate social responsibility. This convergence of progressive values with business objectives has reshaped how brands engage with social justice movements, making activism an integral part of their marketing strategies.

In conclusion, Nike’s 2019 Women’s Just Do It campaign serves as a prime example of how brands can align feminist values with their marketing strategies. By leveraging empowerment as both a message and a marketable asset, Nike secures its place as a forward-thinking, culturally relevant brand, resonating deeply with its audience while driving profitability.

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Reference

Banet-Weiser, S. (2018) ‘Introduction’, Empowered: Popular Feminism and Popular Misogyny. Durham, NC: Duke University Press.

Catterall, M., Maclaran, P. and Stevens, L. (2006) ‘The Transformative Potential of Feminist Critique in Consumer Research’, Advances in Consumer Research, 33(1), pp. 222-226.

Cho, K. (2007) ‘[언중언] 돌잡이’, 강원일보. Available at: https://www.kwnews.co.kr/page/view/2007122500000000052 (Accessed: [2.December. 2024]).

Kozinets, R. et al. (2023) ‘A macrosocial perspective’, in Influencers and Creators: Business, Culture and Practice. Sage, pp. 27-52.

Rasmussen, K. (2021) ‘Brand Activism and Gender: Nike as a Case Study’, Theses and Dissertations. 9007.

Social media is an integral part of my daily routine. Each morning, I open Instagram to explore the latest posts from fashion brands and magazines I follow. Whether scrolling through new trends, popular videos, or updates on social issues, my activities generate data that the platform collects and uses to refine its algorithm. For instance, after checking the Instagram account of Palace Skateboards today, I liked a post, only to encounter ads from brands like Supreme and Stussy minutes later. This routine highlights how my interactions not only shape the content I see but also contribute to the platform’s operation. According to Andrejevic (2014), this consumption of content is part of a broader system of “digital labour,” where users unwittingly produce data that fuels the platform’s economic model.

Beyond consuming content, actions like liking posts or following accounts actively produce data that drives the platform’s profit. When I follow a fashion brand, it gains insights into my preferences, and when I engage with ads, this data helps advertisers target me more effectively. Fuchs (2014) contends that this data extraction represents digital exploitation, where users’ unpaid contributions are crucial to platform profit. Despite my contributions, I receive no direct compensation, raising questions about this unrecognised labour.

Ads that I get even though I do not follow the account

The Platform’s Profit Model and My Role

Social media platforms rely on user-generated data to drive their profit model. Every interaction—whether following an account, liking a post, or clicking on an ad—improves targeted advertising. After searching for workout wear from Lululemon, I noticed ads from brands like Gymshark and Alo Yoga appearing on my feed. These targeted ads ensure advertisers reach potential customers effectively. Terranova (2000) describes this as “free labour,” where users unknowingly contribute to the platform’s financial gains without compensation.

While this benefits advertisers and platforms, users receive little in return. My contributions help personalise services, yet I am excluded from the economic rewards. This imbalance highlights the undervaluation of users’ labour, essential to platform success (Zuboff, 2019).

Reflection on Compensation

The time I dedicate to social media generates substantial economic value. My interactions provide the platform with data that fuels advertising revenue. However, I receive no direct financial benefit, which feels inherently unfair. Scholz (2013) highlights this exploitation, were users’ unpaid labour drives platform success without compensation.

This inequity calls for a reassessment of how platforms recognise and compensate users. Users provide indispensable value by generating data, and platforms should explore ways to reward this contribution fairly. A more balanced system could acknowledge users as active participants in the profit-making process rather than passive consumers of content. The lack of compensation for users’ data highlights the need for more ethical practices in data usage (Fuchs, 2014).

Conclusion

My daily use of Instagram allows me to engage with the latest trends and ideas, but my participation goes beyond passive consumption—it constitutes unpaid labour that drives the platform’s success. Despite the economic value of the data I provide, I am excluded from the rewards. Social media platforms should reconsider their profit models to ensure a fairer exchange, recognising users not just as consumers but as co-creators of value. Addressing this imbalance would foster a more equitable digital environment where the contributions of all participants are valued and rewarded. Only by acknowledging and compensating the labour that users contribute can platforms build a more sustainable and ethically responsible model, ensuring that the value generated is shared more equitably among all parties involved. As Zuboff (2019) suggests, fostering a more ethical and equitable digital economy will require platforms to value and compensate the data labour that users provide.

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Reference

• Andrejevic, M. (2014) Exploitation in the digital age: Data, digital labour and the new economy. In: J. Fuchs, M. Boersma, A. Albrechtslund and J. Sandoval, eds. Internet and Surveillance: The Challenges of Web 2.0 and Social Media. Routledge, pp. 141-157.
• Fuchs, C. (2014) Digital labour and Karl Marx. Routledge.
• Scholz, T. (2013) Digital labor: The Internet as a playground and factory. Routledge.
• Terranova, T. (2000) Free labour: Producing culture for the digital economy. Social Text, 18(2), pp. 33-58.
• Zuboff, S. (2019) The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. PublicAffairs.

Netflix is a global platform, but its content library varies significantly depending on where you are. Comparing my experiences with Netflix in South Korea and the UK reveals how regional licensing and viewing habits shape what’s available and how people use the service.

Netflix in South Korea: A Focus on Local Platforms

In South Korea, Netflix is often overshadowed by local platforms like TVING, Watcha, and Wavve. These services dominate the market by providing exclusive access to popular domestic content. For instance, TVING is closely tied to TVN, a major broadcasting channel, and streams TVN dramas almost exclusively. This close integration makes these platforms a better choice for viewers who want the latest Korean shows. Additionally, incentives like discounts bundled with mobile and broadband services encourage the use of local platforms over Netflix.

Another factor is Netflix Korea’s content library, which includes a significant amount of Japanese animation but comparatively fewer European or Western shows. While this appeals to anime fans, it limits the platform’s appeal for viewers seeking a broader selection. As a result, many Koreans turn to alternatives like Watcha, known for its curation of international and independent films, or Wavve, which aggregates content from major Korean broadcasters. Streaming services in South Korea, driven by the country’s love for K-dramas and variety shows, reflect local tastes and expectations, pushing local OTT platforms ahead of global competitors.

Netflix in the UK: Broad Selection with Licensing Challenges

In the UK, Netflix has a wider array of Western content, including some British series, but licensing agreements often lead to inconsistencies. A personal favourite of mine, the BBC comedy Miranda, left Netflix UK in 2020 when its streaming license expired. Although it briefly returned with one season, it eventually moved to other platforms like iPlayer and BritBox. On the other hand, another BBC series, The IT Crowd, remains on Netflix UK as of 2023, highlighting how licensing varies by show and time​.

These changes reflect the broader dynamics of streaming rights, which are influenced by competing platforms and regional demand. Platforms like BBC iPlayer and Channel 4’s All4 provide strong competition to Netflix, offering popular UK shows that aren’t available on Netflix UK. This creates a fragmented but diverse streaming landscape for UK viewers.

Why These Differences Exist

The key reason for these regional differences is licensing. Streaming rights are negotiated separately for each region, influenced by local demand and competition. In South Korea, strong local platforms secure exclusive rights to domestic content, reducing Netflix’s market share. In the UK, Netflix’s library leans heavily on Western and global shows, but licensing contracts determine how long those shows stay on the platform. The growing competition from local platforms in both regions—such as TVING and Wavve in South Korea, and iPlayer, BritBox, and All4 in the UK—further shapes the content Netflix can offer.

Conclusion: One Brand, Different Experiences

Netflix’s offerings reflect local markets, licensing complexities, and cultural preferences. In South Korea, domestic platforms dominate, leaving Netflix with a smaller role in the streaming landscape. In the UK, Netflix remains a central part of entertainment culture but faces challenges with retaining popular titles. These regional contrasts show how streaming is both a global and deeply local experience, shaped by where you are and what you want to watch. With the rise of both regional platforms and global competitors, Netflix must continuously adapt to each market’s unique dynamics and demands.