Part 3 of Selfie Assignment reflection

Navigating the Complexities of Digital Self-Representation: A Critical Analysis of AI-Enhanced Selfies

In our increasingly digitized world, the selfie has transcended its humble beginnings as a simple self-portrait. It has evolved into a medium for self-expression and identity formation. My previous analysis in Part 1 delved into the challenges of digital self-representation. For instance, I exploredhow culture, technology, and identity interact, particularly through the lens of selfie culture. However, transferring that critical assessment into a blog post style, as required in Part 3, allows better understanding of this phenomenon in the context of online platforms. As Tiidenberg (2015) argues, the socio-technological conditions of specific platforms shape the self-representations that emerge. Recognizing this, I aim to contextualize my AI-enhanced selfie as a "location" within the digital landscape. To achieve this, I enhanced my selfie using Fotor AI tools. I then shared one of the images on three different social media platforms i.e., Twitter, Facebook and Instagram. This post then examines how the three different platform influences the perception, interpretation, and (re)presentation of the selfie. I will also engage on the ethical and cultural implications of sharing our identities across various online spaces. The aim is to uncover the relationship between individual expression, and platform-specific contexts. Then, I will show how sharing a selfie becomes a symbolic representation of our different identities within the digital realm.

Enhancing the Selfie with AI: The Creative Process

I chose to utilize the Fotor AI to enhance my original selfie. I choose the Fotor AI tool because it has a free trial, different customization options and is easy to use. The process of creating the AI-enhanced selfie began with me taking a basic photograph of myself. I then uploaded this image to the tool. As noted, Fotor AI has rich customization options. This gave me the leeway me to experiment with the visual elements of the selfie. For example, using Fotor's AI-powered tools, I adjusted the lighting, color, texture, and artistic effects of the original image. In addition, I played with the exposure and contrast settings to make my features more pronounced. I also experimented with various filters. The resultant image was as shown in Image 1 below:

Image 1: Fotor AI enhanced image of myself

Throughout this process, I could not help but be captivated by the things technology can achieve. With just a few prompts or clicks, the image became more “enhanced.” However, at the same time, the exercise was also thought-provoking. I was keenly aware of the implications these technologies can have on the authenticity of the self-representation.

Moreover, I posted the photo in Image 1 above on Facebook, Twitter and Instagram. Notably, the selfie was interpreted differently on the three platforms. As Marwick (2013) notes, sharing an image on any platform is not just passive distribution. Instead, Marwick shows that when we shareour images online, we are actually constructing our digital identities. Since the three platforms have different ecosystems, each has its own specific socio-technical contexts that we navigate when we post our images there. To explain, Murthy and others (2016) observe that each online space has its own algorithmic logic, cultural implications, and technological affordances. For instance, Instagram insist on visual content that is often edited and has captions that give context. On the other hand, the Murthy and others (2016) claim that Twitter emphasizes on text with images only being used as supplement to text. However, Facebook falls in between with an emphasis on both texts and visual content. Such platform emphasis will influence how people interpret images. This was reflected in the comments I received when I shared the AI-enhanced selfie on the three platforms. The next section will examine in detail how the AI-enhanced selfie was interpreted across the threeplatforms.

Analyzing the Representation of the AI-Enhanced Selfie Across Platforms

Posting my AI-enhanced selfie across different social media platforms showed how digital self-representations are interpreted. Across these platforms, the audience's expectations, social norms, and engagement patterns play a crucial role in how images are perceived (Wilding et al., 2018). Wilding and other’s study show that another factor affecting image interpretation is the platform specific algorithms. This is because algorithms determine the visibility and prominence of content within users' feeds. In light of this, I examined the different responses and engagement on Instagram, Facebook, and Twitter.

First, the AI-enhanced selfie garnered the greatest engagement on Instagram. The reason for this is the platform's emphasis on visual content. As Abidin (2016, p. 23) observes, the Instagram selfie is often defined by its "visually striking nature and its focus on lifestyle aesthetics." Notably, the comments praised the "fire" filter and "editorial vibes" of the image.

 

This aligns with Abidin (2016) findings of this platform’s specific norms. Therefore, the AI-enhanced image resonated with Instagram's culture of curated self-presentation. However, some users also expressed skepticism about the authenticity of the image. One questioned whether it was truly a representation of me. I have attached Image 2 below that shows a screenshot of reactions to my AI enhanced image. The names are redacted to protect the user’s identity.

Image 2: Instagram reactions to my AI-enhanced selfie

These reactions highlight the tension between expression and authenticity that arises on social media platforms. Notably, the line between reality and idealized self-representation becomesblurred (Tiidenberg, 2015). As van Dijck (2013) argues, the performance of the self on platforms like Instagram is often heavily influenced by the technological affordances and cultural expectations of the specific digital environment.

In contrast, on Facebook, the AI-enhanced selfie elicited different responses from my social network. On Facebook, some of my friends and family members appreciated the creative aspects of the image. Below is an example of a comment I received. 

Image 3: A comment on Facebooks on my AI enhanced image

However, others expressed concerns about the potential disconnect between the digital representation and my "true" self. This was expressed through comments such as "Cool edit, but it doesn't really look like you" and "Why did you change your appearance so much?" 

Image 4: A concerned user comment on Facebooks on my AI enhanced image

This finding aligns with Boyd's (2014) concept of "context collapse." Notably, Boyd (2014) noted a scenario where the boundaries between different audience groups become blurred, complicating claims about digital identity. To explain, Facebook is more intimate and personal. Thus, users may have higher expectations of authenticity and familiarity, leading to deeperanalysis and critical reception of the AI-mediated selfie.

The reaction on Twitter, however, took on a different tone. Notably, users engaged in discussions about the ethical implications of AI-powered self-representation. For instance, there comments about the potential biases and limitations of the algorithms used to generate the image. In addition, there were concerns about privacy risks. One comment that caught my eye was as shown below.

Image 5: A comment on Twitter on my AI enhanced image.

These comments reflect the Twitter's role as a place for public discourse. 

This exercise aligns with Varsha's (2023) findings on the importance of examining the societal impact of AI systems. This is particularly important in this context since AI systems have been utilized for self-expression. In the end, this exercise has shown that the "location" of the selfie shapes its interpretation. To explain, the location refers to the specific technological, cultural, and audience-based contexts in which the image is shared (Rader & Gray, 2015). As has been shown, each of the three platforms has their unique preferences and norms. These have created different ecosystems that interpret the same messages in different ways. Thus, on each of the three platform, the selfies were situated in its own "location" for self-representation.

However, the fact that AI-enhanced selfies are on the riseraises questions about the implications of these platforms on identity formation and self-representation. As scholars like Abidin (2016) and van Dijck (2013) have observed, each platform's uniqueness shapes the way individuals curate and present their identities online. For instance, Instagram emphasizes visual and edited images. With AI tools, this will likely lead to a distortion of authentic identities in favor of idealized representations. The platform's visual content emphasis features may compel users to embrace AI-generated enhancements or filters that conform to unrealistic beauty standards. This phenomenon aligns with Chua and Chang's (2016) findings that social media platforms can facilitate peer comparison and promote insecurities. As such, it can lead toindividuals sacrificing authenticity for the sake of validation. On the other hand, we saw that Facebook values personal connections and social networks. This can mean that the pressure to maintain a "likable" online persona may influence individuals to present AI-enhanced selfies that align with the expectations of their specific audience. This dynamic resonates with Boyd's (2014) concept of "context collapse." On the one hand, AI tools offer avenues for self-representation and identity exploration. However, the platform used to for distribution images will likely lead to unrealistic ideals. Thus, the differences in platforms can distort authentic identities in favor of idealized representations.

Incorporation of Feedback

The peer review process played a pivotal role in helping me refine my argument. Notably, the comments touched on the need to critically examine the connections between technology, culture, and identity. As a result, I focused my analysis on critically examining how AI generated selfies are received different platforms. For example, the peer insisted that I should be more analytical when showing the impact a platform has on the how content is consumed. Heeding this feedback, I engaged three different platforms including Facebook, Instagram and Twitter. The intention was to show how the different audiences on each platform perceived the same image. This process was instrumental in strengthening my appreciation for the challengesof digital identity formation across platforms. Additionally, one comment from my instructor asked me to re-evaluate the narratives that shape our perceptions of identity and self-representation on the social media. Heeding this feedback, I sought to draw from scholars like Abidin (2016). The intention was to better understand how platforms like Instagram develop the ecosystems that determine how people consume materials. Reflecting on the feedback, I was more analytical and focused on the topic of "selfies as locations." As such, my analysis shows the pivotal role that online platforms play in influencing self-representations.

Ethical and Cultural Considerations

As I carried out the exercise, different ethical and cultural considerations emerged. First, AI tools offer new ways for self-expression. However, they also raise concerns about the potential biases and limitations in the algorithms that power these technologies. Scholars like Varsha (2023) have highlighted the risks these algorithms have when used for diverserepresentations. Varsha cautioned that this could lead to the perpetuation of harmful stereotypes or misrepresentations. As such, it is paramount to examine the training data and methodologies that power AI tools. In addition, it is vital to advocate for more inclusive and ethical practices in their development and deployment. Moreover, the cultural influences that shape our perceptions of identity and self-representation cannot be ignored. As Abidin (2016) notes, platforms like Instagram foster a culture of lifestyle aesthetics. As this essay has shown, this can lead to distortion of authentic identities in favor of idealized representations. Thus, it is crucial to acknowledge these cultural narratives and to resist the narrow representations of our identities (Cote & Pybus, 2011).

Adapting to the Digital Medium

Transitioning from a traditional academic paper to a blog post format necessitated an awareness of the effects of medium on message delivery. On the one hand, a blog post is more informal and the writer is required to be creative. However, a traditional academic paper must follow a specific format and structure. However, the blog presents both challenges and opportunities for communicating ideas. One of the key considerations is the best way to leverage the digital medium to enhance the narrative that engages the reader. Nonetheless, a blog post incorporates multimodal elements such as images, screenshots. This is important for enriching the storytelling experience. Importantly, a blog post also aligned with the visual nature of the subject matter. Furthermore, adapting the writing style to suit the more conversational tone of blogpost platforms was essential. To achieve this, I aimed to strike a balance between depth and clarity without compromising academicintegrity. This process showed me the importance of gainingappreciation for the differences of medium in how we communicate. Thus, I now appreciate the importance of tailoring one's message to a specific medium and audience. Therefore, it is important to develop additional skillsets such as blog postwriting. This will enable one to effectively communicate ideas across various digital platforms and formats without compromising quality or depth.

The Future of Digital Identity

As we look towards the future, the interaction between technology, culture, and identity will undoubtedly continue to shape the landscape of digital self-representation. The rapid advancement of tools such as AI will usher in new ways of identity expression. On the one hand, scholars like Ahn, Le, and Bailenson (2013) and Huang, Rauch, and Liaw (2010) have highlighted the potential of these tools for creating engaging experiences. On the other hand, Kilteni, Groten, and Slater (2012) and Turkle (2011) caution against the risks of dissociation that these technologies may unintentionallypropagate. For instance, this analysis has shown that different platforms have different ecosystems. These ecosystems influence how people on the platform interpret different messages. The implication is that people will use AI to curate content such as images that conform to idealized representations on the target platform. Ultimately, the selfie, as a digital location, represents the challenges and opportunities that arise as digital identities change due to tools such as AI. It serves as a reminder of the need for understanding of the connectionbetween culture, technology, and identity. Thus, it becomes imperative to maintain discourse surrounding the implications of AI-mediated self-representations.



References

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