Would Dussel ❤️ SM?

Once again I will begin a post praising Enrique Dussel , happily this one brings my adoration in contact with another great fondness I have, Social Media. I feel that Dussel’s beliefs of liberty offer a basis for scrutinizing social media via a framework prioritizing the enormous majority, that I am trying to incorporate in my writings. His perspective aims to disrupt oppressive relations and to advance minority voice, input, and conversation in everyday mediated interactions. Through the rest of my post I will try and present a cognitive analysis of current practices in social media and the correspondence or lack of correspondence regarding adopted liberatory ethics based on Threads, X, TikTok, and Instagram; one I conquered and the other two I am having the most trouble mastering. 

Media Ethics in Practice: Algorithms and Accessibility

I began talking about the manipulation of algorithms decades ago while fighting for privacy on the internet, I lost, while currently I just want to open peoples minds to think rather than just accept. The evil science of algorithms determines the content that users interact with today and what content will be prioritized in social media spaces. We know that in a vacuum, algorithms are intended to improve the quality of user interactions by presenting content according to the users’ interests, the practice shows the framework is inherently questionable and problematic, especially for disadvantaged groups in society.

Threads: The Relevance-Versus-Equity Dilemma

Let me start by saying I DO NOT KNOW what the purpose of Threads is? If it is to compete with Twitter, it fails. Threads, introduced by Meta, is an external recommender system that tailors users’ feeds based on rates of interactions and stated preferences resembling all of the others. On the surface, this should guarantee retrievable and relevant content, making the platform as welcoming and focused on the user as possible (Pentzold & Fechner, 2019). The truth is that this design privileges either promotional or unwanted ‘high-likelihood engagement’ posts, the latter of which are derived from accounts with large numbers of active followers. This forms a cycle where the discourses that are loudly articulated get heard much more. The unfortunate result of this is that discourses that need exposure are less heard, having to fight for attention when they are relevant only because they fit into the trending topics of the platform.

X (formerly Twitter): Monetization and Polarization

I miss early twitter and my debates on the need to protect the privacy of users on the internet, in definite conflict with capitalism. Twitter has changed and now the current  monetization model on X underlines an even starker ethical contrast. Paid verification has made visibility on X null, making it something you must buy. Genuine and many connected to big businesses, celebrities, or firms with sufficient funding get boosted through the algorithm. This “pay-to-play” approach also locks out deserving and potentially more effective participants, such as independent journalists or activists who may not afford costly services.

Furthermore, X’s algorithm has been accused of displaying content that is likely to spark division as it is viewed more obviously. Diabolic or scandalous material opinion causes passion, and passion causes sharing the salacious material.This is diametrically opposed to what should be, is used to confuse and control, unlike informative and elaborate material that requires people’s attention for critical thinking (Zhang et al., 2024). This leads to an environment where more shocking and risky voices can overpower reasoned discussions of important topics such as social justice and media.

The Consequences of These Approaches 

In investigating the process of algorithmic decision-making, Threads and X show that such approaches do not consider the concerns of struggling groups of people. In Threads, I found that the players do not have intentional tools in the algorithm that make the opinions of minorities be heard, thus they are easily erased. On Elon Musk’s X, visibility becomes commercialized to the extent of worsening the existing inequalities in regard to the level of attention granted to particular actors (Zhang et al., 2024). This means that oppressed groups that don’t conform to Musk’s standards get to exercise their right to free speech or speak out on issues affecting them in public forums, but are often restricted from going viral .

Approaches to Design Ethical Algorithm

I wanted to try and envision a kind of platform that aligns with a liberatory media ethic knowing the algorithms must change. Three key strategies to my cauldron of reform include:

Algorithmic Equity: The second focus area is diversity and inclusion, which means creating algorithms that give a platform to diverse individuals while not forcing them to mimic current styles. This goes against the colonialism America was founded upon, so it had to be my first position.

Transparency: Provide information about how content is generated and enable users to change settings based on ethical values, for instance, educational or community feeds.

Support for Small Creators: Build avenues through which grassroots organizations and independent producers can be aired to the public without compromising their financial capability.

Talking about Social Justice and Media literacy

Possibly being Chinese or just wanting to poke the American Bear, TikTok offers a somewhat encouraging matrix in which to employ liberatory media ethics. The platform’s method of content recommendation allows the information from marginalized groups, in opposition to Meta, Musk and the rest, to go viral when there is an interaction with a focus on advocacy or any social justice topic. Such trends that become successful hashtags to get connected.  A prime example is #BlackLivesMatter, which gave voice to marginalized stories and mobilized people across the globe (Schroeder et al., 2024). While it seems to be the best of the platforms, its  poor policy on moderation, including the fact that it is unknown how it operates and if it slows down the suppression of controversy, suggests that TikTok has not fully achieved media liberation.

Instagram positioned itself as an aesthetics site that also provides activists as well as young people a place to find appealing ways to express themselves.This is one I am trying to master while a large number of real influencers use the site properly to promote not only their personal brand awareness but also they also raise awareness about current social justice issues. Due to the demographics of its users,. this model may be one, like TikTok, that could bring activism to a democratic level, however this election cycle showed it has watered down many responsible trending topics to fill our heads full of fecal matter..

Capitalism Vs the Vast Majority

I am not a fan of capitalism, nor do I believe it brings freedom for anyone other than a select few. That being said, my privacy rantings were totally focused on the sinister selling of collated personal information. It may be the biggest business out there as it keeps these sites in business and happily melds with algorithms to drive visions of everything you look at to your feed.  All sites in one way or another are based on the sharing of information. They are solely in the context of capitalistism and are all valued ons the number of active users and information collected, rather than profit. X’s monetization strategy is a clear example of this: visibility is sold in exchange for investment, making potentially relevant but not highly lucrative discourse disappear (Pentzold & Fechner, 2021). On the other hand, applications like Threads or Instagram try to blend the users’ interaction logic with the community engagement objectives. Unfortunately,  these are still predetermined by the advertising/driven revenue generation and the data collection/monetization paradigms.

Dusselling It Up

Bringing in as much as the colander that is my brain can recall, my view of the ethics of liberation with a lens to the media, would look like this by prioritizing the following:

Inclusive Algorithms: I would create a method that brings more focus to minority opinions in the limelight for everyone to have a fair share of voice.

Transparent Moderation: This is a hard one, though I hope to create trust in the moderation process by diversifying the moderators themselves, and clearly defining rules of engagement where contentious issues are concerned much like we learned with help from the Online News Association.

Grassroots Accessibility: I would seek out grassroots organizations the way twitter did originally, making digital resources available for all organizations regardless of their capacities. This would be done through Tor or a new hybrid VPN that could circumvent restrictive government blocks.

Education-Driven Goals: The platforms should include opportunities for media literacy interventions that provide users with resources to confront misinformation and interact with the material, possibly even with tools gained in my media ethics class.

Conclusion: Bridging Ethics and Practice

I believe that should we instill the positive principles into a free system, social media cannot only move from mere enablers of distraction or fanning division, but become a platform for change and bring much needed power to the people. I believe that social media should be free in the way it is designed and created. This way, the “vast majority” may in turn follow our model morphing into places of real discussion, education, and engagement.  Practices today show there is a large gulf between profits and ethical goals, with no balance in sight. I am hopeful that, just as society is in a constant state of change, so too will be us as the consumers standing up and demanding change. 

Works Cited

Pentzold, C., & Fechner, D. (2019). Data journalism’s many futures: Diagrammatic displays and prospective probabilities in data-driven news predictions. Convergence: The International Journal of Research into New Media Technologies, 26(4), 732–750. https://doi.org/10.1177/1354856519880790

Pentzold, C., & Fechner, D. (2021). Probabilistic Storytelling and Temporal Exigencies in Predictive Data Journalism. Digital Journalism, 1–22. https://doi.org/10.1080/21670811.2021.1878920

Schroeder, P., Morgan, N., Luo, H., & Glass, J. (2024). THREAD: Thinking Deeper with Recursive Spawning. ArXiv (Cornell University). https://doi.org/10.48550/arxiv.2405.17402Zhang, P., He, Y., Haq, E.-U., He, J., & Tyson, G. (2024). The Emergence of Threads: The Birth of a New Social Network. ArXiv (Cornell University). https://doi.org/10.48550/arxiv.2406.19277