Assignment 4: Selfie Transliteration - Vera Chen

 ✨ Negotiating Identity in the Algorithmic Mirror: A Journey Through AI-Generated Selfies

Creating AI-generated selfies through Meitu and other platforms has been a visually rich, creatively satisfying, and intellectually challenging experience. What began as an artistic experiment quickly became a critical reflection on how I perform, construct, and negotiate my identity in a digital, globalized world. This blog post chronicles that journey from design choices to academic critique while reflecting on the broader implications of algorithmically mediated self-representation.

🧭 The Creative Journey: From Prompt to Portrait

Using Meitu’s intuitive AI tools, I set out to craft a digital self-portrait that captured my identity as a Chinese international student navigating between tradition, modernity, and digital culture. Inspired by Hanfu aesthetics, I incorporated traditional Chinese elements such as golden fish, symbolic attire, and auspicious colors with a futuristic cityscape to reflect themes of globalization and innovation.

Later, I experimented with a second AI model DALL-E to push the concept further by integrating AR-style overlays and digital data streams. While the result was visually compelling, the process exposed AI’s limitations: it could reproduce surface-level aesthetics but failed to grasp more nuanced metaphors like multi-layered identity or dynamic social interaction.

Throughout this process, I found myself asking: Is this image really “me”? As Senft and Baym (2015) suggest, selfies are more than snapshots, they are acts of performative identity. While Meitu allowed me to amplify aspects of my cultural background, it also modified my appearance in subtle but telling ways lightening my skin, enlarging my eyes, and smoothing imperfections in alignment with East Asian beauty standards.

This aligns with critiques from Meier (2022) and Buolamwini and Gebru (2018), who argue that AI tools often reinforce dominant racial and gendered aesthetics. Rather than offering a neutral canvas for self-expression, AI subtly steers users toward homogenized ideals, which can shape how we see ourselves and how others see us.

Platforms like Instagram and WeChat don’t just host our images, they algorithmically curate them. As Gillespie (2018) explains, content that aligns with aesthetic norms is more likely to be seen, shared, and validated. My AI-enhanced selfies, had I posted them, would likely receive more attention than raw, unfiltered images. This reveals a feedback loop: platforms incentivize conformity to algorithmic beauty, which in turn shapes user behavior and self-presentation.

Van Dijck (2013) calls this the co-construction of identity, where platform infrastructures and social validation converge. In this sense, digital self-representation is never fully in our control; it’s always negotiated within invisible systems of platform governance.

The process of creating AI-generated selfies raises urgent ethical and cultural questions around representation of gender and ethnicity, user agency, and digital privacy.

From a gender perspective, AI-enhanced selfies often reinforce narrow standards of femininity such as delicate features, large eyes, and soft skin textures that align with hyper-feminized digital aesthetics. These traits, embedded into beautification filters, encourage women to conform to platform-specific visual norms (Meier, 2022). For instance, while experimenting with Meitu, I observed how the app’s default filters feminized my appearance in subtle ways, even when I chose not to apply overt beautification.

Culturally, apps like Meitu tend to prioritize East Asian ideals of beauty such as pale skin and symmetrical features. While these reflect certain regional aesthetics, they risk erasing internal diversity and promoting a single, idealized ethnic identity. As Buolamwini and Gebru (2018) reveal, commercial AI tools often marginalize darker skin tones and non-Eurocentric features, limiting inclusive digital representation. My experience mirrors this as the app’s enhancements aligned more with generalized beauty archetypes than my individual traits, suggesting that “personalization” is often algorithmically constrained.

Ethically, AI-generated selfies complicate digital consent and privacy. Users often overlook how their images and the biometric data embedded in them can be stored, shared, or monetized by the platforms and third-party algorithms involved (Gillespie, 2018). The very act of creating and uploading a selfie subjects users to a wider digital economy where visibility is rewarded but control is diminished. Van Dijck (2013) terms this phenomenon the “platformization of identity,” where personal data becomes infrastructural capital.

In the broader context of digital media ethics, these issues speak to the need for critical awareness and equity-oriented design. Noble (2018) warns of the dangers posed by algorithms that replicate and amplify social inequalities, while also controlling access to visibility and representation. Ethical digital design must center diverse voices, resist one-size-fits-all beauty norms, and give users transparent control over their data.

In short, AI selfies are not just images, they are technologically mediated narratives. They invite us to reflect on who gets to be visible, how beauty is codified, and what trade-offs we accept in exchange for digital participation.

🔁 Translating Analysis into a Blog Format

Adapting my academic analysis into a blog post pushed me to reframe dense theory into accessible, engaging language without diluting the ideas. In doing so, I practiced what this course calls transliteracy: communicating fluently across media, modes, and platforms. As McLuhan reminds us, “the medium is the message” and in this case, the blog medium demanded clarity, multimodality, and reflexivity.

The visual layout, inclusion of AI-generated images, and web-friendly tone helped convey complex insights in a digestible way. It reminded me that knowledge-sharing is not just about what we say, but how we say it and who we invite into the conversation.

This assignment and the course more broadly taught me that digital self-representation is never neutral. It is shaped by aesthetics, algorithms, platform incentives, and cultural politics. I now view AI not just as a creative tool, but as a mediator of identity and meaning.

Moving forward, I will be more intentional with how I represent myself online. I’ll seek out diverse tools, challenge algorithmic norms, and remain critically aware of how platforms influence visibility and voice. Most of all, I will continue exploring how technology can support, not silence authentic, pluralistic self-expression.

References

Barker Nathian, V., & Rodriguez, S. (2019). This Is Who I Am: The Selfie as a Personal and Social Identity Marker. International Journal of Communication, 13, 1143–1166. https://ijoc.org/index.php/ijoc/article/viewFile/9723/2588

Buolamwini, J., & Gebru, T. (2018). Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification. Proceedings.mlr.press; PMLR. https://proceedings.mlr.press/v81/buolamwini18a.html

Gillespie, T. (2018, January). Custodians of the internet: Platforms, content moderation, and the hidden decisions that shape social media. ResearchGate. https://www.researchgate.net/publication/327186182_Custodians_of_the_internet_Platforms_content_moderation_and_the_hidden_decisions_that_shape_social_media

Alice Emily Marwick. (2013). Status update : celebrity, publicity, and branding in the social media age. Yale University Press.

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

Jill Walker Rettberg. (2014). Seeing ourselves through technology : how we use selfies, blogs and wearable devices to see and shape ourselves. Palgrave Macmillan Uk.

Senft, T. M., & N.K. Baym. (2015). What does the selfie say? Investigating a global phenomenon. 9(1), 1588–1606. https://www.researchgate.net/publication/313750318_What_does_the_selfie_say_Investigating_a_global_phenomenon

Jose Van Dijck. (2013). The culture of connectivity: a critical history of social media. Oxford University Press.