Author: Diana Ignatovich

The tendency to measure our worth against unrealistic beauty standards is hardly a new concern, yet it persists even as feminist theory challenges these ideals and media efforts claim to represent diverse bodies. Platforms like TikTok, for example, argue their core values prioritize diversity, with policies that uplift underrepresented communities. Still, self-objectification of both women and men is largely driven by mainstream media (Rodgers, 2015), significantly impacting users’ self-esteem. An increasing body of research emphasizes self-objectification in reported decline of cognitive functioning and is associated with many mental health issues such as depression and eating disorders (Fredrickson and Roberts, 1997). But with such widespread awareness, why does self-objectification remain so prevalent? 

Researchers Corinna Canali and Miriam Doh uncover the “truth” behind the algorithmic structures that construct identities and perpetuate this self-objectification online. Bodies and forms of self-expression deemed as “true,” “normal,” or “obscene,” are not actually objective categories. They are rather social constructs created by institutions who have the power to define them, such as governments, corporations, or tech platforms. One structure that reinforces self-objectification, and distorts self-perception is the use of augmented reality filters. These AR filters have become popular across social media networks that an estimated 90 percent of American young adults visit daily, with 58 percent of teens using TikTok alone (Bhandari & Bimo, 2022). The ways in which these filters, incentivized by algorithmic systems, affect identity, prefer uniformity, and marginalize diversity are explored in Filters of Identity: AR Beauty and the Algorithmic Politics of the Digital Body, co-authored by Corinna and Mariam Doh.

Corinna is a research associate at the Weizenbaum Institute and Design Research Lab, and her project partner, Mariam, is a PhD student with the AI for the Common Good Institute / Machine Learning Group at the Université Libre de Bruxelles. Corinna’s initial inspiration began with a study on nudity in digital and social media contexts. This led to a broader analysis of digital governance engrained “obscenifying” beliefs, where systems are built on the assumption that certain bodies, identities, and forms of expression are inherently obscene. From this, she has developed extensive experience across institutions in examining how platforms and policies act as regulatory infrastructures that shape who is seen, censored, or silenced in digital environments.

In an interview conducted for this article, Corinna discusses how AI-driven beauty filters do more than simply mirror existing beauty norms, but actively construct and reinforce them.

Although TikTok’s effect house policy has been implemented to ban filters that promote unrealistic beauty standards, the platform continues to circulate effects that do exactly that. As an example, Corinna analyzes the Bold Glamour filter, which edits users’ faces in ways that are difficult to detect but tend to favor Eurocentric and cisgender features such as lighter skin, narrow noses, and larger eyes. It also frequently misidentifies or distorts the facial features of certain racial groups. The highest “misclassification rates” were detected in black women, where the filter failed to accurately detect a person’s face or altered their features in ways that don’t reflect their real appearance. This systematic exclusion of non-conforming bodies manifests into a larger trend in technological design, where digital systems tend to perpetuate dominant norms. Bodies that fall outside these norms, including those that are disabled, fat, Indigenous, or Black, are frequently invisible or misrepresented within the algorithm. 

Corinna argues that these marginalized identities also have the most underrepresented narratives when it comes to bias in content moderation:

“Also, if you (tech company) own all the means of knowledge, circulation and production it’s quite difficult to allow any other narrative to exist within these spaces.” 

She then identifies a serious problem in the subtle ways this discrimination persists unnoticed outside academic circles. She noted that while users may recognize individual instances of bias, they often lack the tools or social power to challenge them within digital spaces.

Notably, the marginalization of these groups has deep roots in the broader historical context of racial capitalism, a system in which racial hierarchies are used to justify and sustain economic exploitation (Ralph & Singhal, 2019). When asked about whether these systems were just reflecting the norms obtained from biased datasets, or if they are actively structured to serve deeper capitalist goals, Corinna describes the influence of deliberate human intervention:

“The algorithm does not work on its own. It works within a system that is constantly being tweaked by real-time content moderation from humans.” 

She underlines the active decisions made by people moderating content from policies servicing business and corporate models, ultimately benefitting the platform’s profitability. 

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Research shows that frequent use of appearance-enhancing filters is associated with increased body image concerns and higher levels of body dissatisfaction (Caravelli et al., 2025). This lowered self-esteem carries significant economic consequences, with body dissatisfaction-related issues costing an estimated $226 and $507 billion globally in 2019 alone (ibid.). Such widespread dissatisfaction is not incidental but is embedded within the algorithmic logics of these platforms.

To elaborate, these filters produce idealized versions of the self that adhere to capitalist interests by making users more desirable, and easier to manipulate with ads. One’s face becomes a data point, and their emotions and desires are recognized as commodities. Additional findings emphasize how these automated categorization systems and targeted advertisements actively shape user identity. According to Bhandari and Bimo (2022), the system influences how people construct, perform, and manage their sense of self in ways that benefit the platform economically but may be harmful to the user.

Corinna addresses this when asked whether TikTok truly allows space for authentic self-expression, or if users are instead shaping their identities to align with platform incentives. She feels conflicted, but responds with insight into how the platform promotes self-governing systems, where the primary commodities are users, their data, and their attention:

“When there is this constant negotiation between your own self expression and agency against this corporate logic of profit, it is always difficult to understand to what extent you are actually free to be who you want to be.”

To promote a more authentic version of self-expression, Corinna’s work suggests filters that give inclusive filtering options, allowing users to specifically choose their own aesthetic preferences. However, the persistence of algorithmic bias reveals the challenge of resisting systemic power: even when AR filters are redesigned to reject dominant beauty standards, the algorithm may continue to privilege a certain aesthetic.

Bearing this in mind, Corinna introduces a transdisciplinary approach utilizing design and theory. She describes the nature of this problem as multifaceted and interconnected, necessitating an equally dynamic solution that addresses the whole system. She describes the benefits of design, as her background in visual cultures allows her to embrace visual ethnographic methods to interpret the implications of images for a unique perspective on bias. She says,

“Images are a product of visual tradition that has its own biases outside of technology. Technology has inherited a lot of this bias, discrimination and representation from other traditions that live outside of it.” 

In this way, Corinna uses design as a tool to reveal and critique bias. This approach does not require technical expertise, but instead encourages people to recognize the significance of what they’re looking at, and in doing so, begin to see the discriminatory practices embedded within it.

Corinna’s next steps address both the internal complexity of these systems and the broader socio-political contexts in which they function. She offers one possible solution in creating opportunities to rethink and rebuild these platforms, but for this, there needs to be space for alternative systems. Corinna highlights that it is extremely difficult now to access any social network that does not come from big tech companies, because they have created conditions where they hold a near-monopoly over these platforms and infrastructures. The process will require time and multiple layers of reworking, starting with how users are educated about these technologies.

To address the lack of adequate understanding on these issues, she plans to develop tools that promote media literacy by helping users acknowledge what these systems are, how they function, and what their greater societal impacts may be. This perspective would stress the reciprocal relationship between society and technology, emphasizing how each continuously shapes the other.

The Design Research Lab and Berlin Open Lab have many projects that explore research through design, uniquely combining critical theory from the humanities with hands-on material production. The lab takes a different path from traditional product design by emphasizing critical reflection on both how products are made and the ways they shape society. Several research projects in this lab consider this approach, including one that addresses the theme of surveillance capitalism discussed here. For a deeper look into how the lab works, check out the spotlight article linked here!

Whether it’s unwinding after a long day or killing time in line for coffee, social media has become a major source of entertainment and connection. The immediate satisfaction it often brings can boost the mood, but it’s not just entertainment we’re absorbing. Amidst the lighthearted content, is exposure to a wide range of information, much of which we may not fully process. Research suggests a link between high social media usage and lower self-control, which may also perpetuate processes of dissociation that many refer to as mindless scrolling. As we passively absorb media from smiling koalas to political protesting, how are we actually understanding the more consequential information and even shaping our opinions?

Lion Wedel and Jakob Ohme consider these influences in collaboration with Bayerischer Rundfunk, Stuttgarter Zeitung, and the University of Zürich in their project, Dein feed, deine Wahl, (Your Feed, Your Choice/Election). In this ongoing initiative, TikTok users are encouraged to donate their data in an anonymous manner and in turn receive a direct analysis of the political content and parties appearing in their feed.

Jakob and Lion shared their perspectives in an interview, offering insight backed by their expertise in political communication and digital media research.

To begin, Lion and Jakob discuss the broader implications of media on shaping one’s ideological framework. Specifically, which types of content shape opinions the most, and how do they attract attention?

To this, Lion responds,

“The more time you spend preparing a video, the less popular it gets. Like quick and dirty typically works better.”

This was in reference to a podcast titled, Was tun? Die Strategien hinter dem Comeback der Linkspartei (1/3): Wie Heidi Reichinnek die AfD auf TikTok überholte, in which Felix Schulz, social media manager in Heidi Reichinnek’s office, explores the strategic use of TikTok to engage young voters. From this, Lion highlights the influential processes through which opinions are likely to form online. He quotes the manager’s technique, asserting that his videos did so well because they managed to make a compelling statement in the first one to three seconds of the clip. Even in regard to political news, Lion describes, “It does not matter if it’s true or false, or if it’s catchy or misleading, you just have to get that attention grabbing moment.” He concludes by suggesting this content that keeps its audience engaged to the video’s end, is more likely to shape opinions.

But what are the implications to the broader democratic landscape in Germany if people form political opinions based on whatever content is most stimulating in their feed, regardless of its credibility? Can the use of traditional media repertoires play a role in fact-checking political discourse?

Statistics of the 2025 Weizenbaum panel report exploring last year’s political participation in Germany may suggest otherwise. Since 2021, there has been a decline in the use of traditional media sources such as newspapers and radio for news consumption, while internet usage has remained consistently stable. Moreover, over 60% of voters up to the age of 30 receive their political information from social networking (Schöffel et al., 2025), suggesting platforms such as TikTok are inevitably shaping how many engage in political debate.

Given recent civic tensions in Germany, including shifts in numerous elections and widespread protests, there appears to be a similar polarization in the spread of social media information. As many are more likely to express their opinions than change them, and online discussions often dominate in one direction of opinion (Xiong & Liu, 2014), raising awareness of these influences not only to our personal perspective but also the broader political environment becomes critical.

According to Jakob, the nature in which algorithmic selection processes function, “affect political landscapes to an extent that we probably ten years ago did not think was possible.” He outlines his interpretation of how algorithmic platforms contribute to political shifts, attributing the cause to the often passive behavior of individuals online, where their feeds reflect the content they prefer. As seen in previous research, social networking individuals may feel a reduced sense of self awareness and volition (Baughan et al., 2022), often consuming the content that is most interesting and aligns with their worldview. Jakob concurs, stating, “We can all function like this from time to time.”

He continues,

“There is content that works better with the algorithm and especially on TikTok. We can see that as soon as something works, it will capture a lot of attention, but as soon as something doesn’t work, it will completely drown. There are certain kinds of political content that work better and that is the emotional appeal, opinionated, negative and extreme information.”

Jakob asserts that certain political parties, especially those on the right-wing, are more adept at taking advantage of this dynamic, as their content tends to perform better online. Algorithms may as a result appear to favor them, not because of any inherent political bias, but because these parties successfully leverage a system that operates based on audience engagement patterns to maximize their impact.

Consequently, the Dein Feed, deine Wahl initiative establishes an objective foundation for identifying usage patterns within TikTok’s algorithms that ultimately contribute to the broader political climate. Jakob emphasizes the significance of these usage trajectories, aiming to explore their association with voting decisions and provide a descriptive overview of the extent to which individuals encounter political party-related content. In addition to this, he expresses the ambition to reverse-engineer algorithms to mitigate their effects. By examining how usage patterns influence algorithmic decisions and lead individuals to encounter more of the same content over time, researchers are better equipped to address these dynamics. This approach is especially essential given that analyzing video content and user interaction data has been largely unexplored due to its methodological complexity.

Overall, this project paves the way for regulating social media platforms in the long term, with the hope that it remains accessible for prospective political debates and elections. However, to move forward, Lion identifies the collection of data donations as one of the first priorities. The quality of the analysis significantly depends on the number of public contributions volunteered to their data donation lab.

Therefore, if you’d like to support the project or are curious of the political makeup in your own feed, please donate your usage here!