Examining embedded apparatuses of AI in Facebook and TikTok

Abstract

In popular discussions, the nuances of AI are often abridged as “the algorithm”, as the specific arrangements of machine learning (ML), deep learning (DL) and automated decision-making on social media platforms are typically shrouded in proprietary secrecy punctuated by press releases and transparency initiatives. What is clear, however, is that AI embedded on social media functions to recommend content, personalize ads, aggregate news stories, and moderate problematic material. It is also increasingly apparent that individuals are concerned with the uses, implications, and fairness of algorithmic systems. Perhaps in response to concerns about “the algorithm” by individuals and governments, social media platforms utilize transparency initiatives and official statements, in part, to deflect official regulation. In the following paper, I draw from transparency initiatives and statements from representatives of Facebook and TikTok as case studies of how AI is embedded in these platforms, with attention to the promotion of AI content moderation as a solution to the circulation of problematic material and misinformation. This examination considers the complexity of embedded AI as a material-discursive apparatus, predicated on discursive techniques—what is seeable, sayable, knowable in a given time period—as well as the material arrangements—algorithms, datasets, users, platforms, infrastructures, moderators, etc. As such, the use of AI as part of the immensely popular platforms Facebook and TikTok demonstrates that AI does not exist in isolation, instead functioning as human–machine ensemble reliant on strategies of acceptance via discursive techniques and the changing material arrangements of everyday embeddedness.

Hyperconnected: children and adolescents on social media. The TikTok phenomenon

“…12,19 The TikTok search engines have a great filtering and compiling capacity based on the platform's own objectives and those of the brands that advertise on it. 16 Such information filtering causes what are known as filter bubbles, where users see only content of interest to them and lose the power of choice or autonomy; the information they receive increasingly captures their attention, generates more dopaminergic stimulation and, consequently, prevents them from discontinuing the app use. 16 As a result, an echo chamber is produced, where only a filtered fraction of content is replicated and different views are not represented.…”

“…16 Such information filtering causes what are known as filter bubbles, where users see only content of interest to them and lose the power of choice or autonomy; the information they receive increasingly captures their attention, generates more dopaminergic stimulation and, consequently, prevents them from discontinuing the app use. 16 As a result, an echo chamber is produced, where only a filtered fraction of content is replicated and different views are not represented. Therefore, interactions and viralizations occur only among users with the same preferences.…”

“…Therefore, interactions and viralizations occur only among users with the same preferences. 16 In relation to inappropriate content, the TikTok engine can recognize and analyze it, but lacks the ability to justify its analysis. 16 So, filtering failures occur and extreme content of hate speech, racism, discrimination, and promotion of anorexia may be displayed.…”

“…16 In relation to inappropriate content, the TikTok engine can recognize and analyze it, but lacks the ability to justify its analysis. 16 So, filtering failures occur and extreme content of hate speech, racism, discrimination, and promotion of anorexia may be displayed. 16 Regarding the issues of data protection, privacy, security, and content moderation, the scope of the algorithms of this platform is not clear.…”

Guest editorial

“…A word of caution and conservatism is in order, particularly for legacy firms and legacy technology, as not all companies will or can adopt and adapt. There is also the very real challenge of the dark side of digitalization, with integrity concerns relating to the power, fairness and bias within algorithms and other inappropriate use which is becoming increasingly evident (Grandinetti, 2021). Also concerns abound at firm, industry and societal levels in relation to the power and dominance enjoyed by "big tech" (Amazon, Apple, Facebook, Google (Alphabet) and Microsoft).…”