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18 S. J. Pol'y & Just. 1 (2024)
When Algorithms See Us: An Analysis of Biased Corporate Social Media Algorithm Programming and the Adverse Effects These Social Media Algorithms Create When They Recommend Harmful Content to Unwitting Users

handle is hein.journals/srebwsude18 and id is 6 raw text is: SO UTHERNJO URNAL OFPOLICYAND JUSTICE WHEN ALGORITHMS SEE US: AN ANALYSIS OF BIASED CORPORATE SOCIAL MEDIA ALGORITHM PROGRAMMING AND THE ADVERSE EFFECTS THESE SOCIAL MEDIA ALGORITHMS CREATE WHEN THEY RECOMMEND HARMFUL CONTENT TO UNWITTING USERS Sikudhani Foster- McCray* CONTENTS INTRODUCTION---------------------------------------------------2 I. PREVIOUS WORK ON RACIALLY BIASED ALGORITHMS: ALGORITHMS OF OPPRESSION, BY DR. SAFIYA UMOJA NOBLE------------------------------------------------- 3 A. Background and Synopsis-----------------------------------------4 B. Groundbreaking Elements in the Text---------------------------------------------- 5 1. Technological Interface from Black Perspectives ------------------------------6 2. Immunity of Information Technology Corporations-------------------------- 8 C. Points of Critique within the Text---------------------------------------9 1. Narrow Focus on the Negative Experiences of Black Girls and Women --- 11 2. Stunted Inquiry into Solely Search Programs --------------------------------- 11 II. THESIS: SOCIAL MEDIA ALGORITHMS RECOMMEND NEGATIVE AND HARMFUL CONTENT TO USERS, ROOTED IN RACIAL STEREOTYPING AND VIRALITY ------- 13 A. Harmful Racial Stereotype Reinforcement through Virality ---------------------14 B. How Social Media Algorithms Perform Actions and Push Negative Content---17 1. Historical Representative Instances of Racial Content -----------------------17 2. Contemporary Representative Instances of Racial Content--------------- 19 3. How Social Media Algorithms Push --------------------------------------21 III. LEGAL IMPLICATIONS OF DETRIMENTAL ACTIVITIES INVOLVING SOCIAL MEDIA ALGORITHMS---------------------------------------------------23 A. Negligence Harms and Corporate Tortious Liability Based in Algorithmic Actions ------------------------------------------------23 B. Criminal Harms and Corporate Civil Immunity Based in Algorithmic Actions-25 CONCLUSION-------------------------------------------------------27 *Sikudhani Foster- McCray is a JD candidate at Emory University School of Law. Foster- McCray completed a B.A. in Business Management and Analytics in 2021 at Loyola University of New Orleans. Foster- McCray acknowledges Dr. Safiya Umoja Noble for her trailblazing efforts in the study of the intersectionality between artificial intelligence and race-based discrimination. Foster- McCray further extends her thanks to Dr. Ifetayo Ojelade from A Healing Paradigm Psychology Office for her interview contributions to this Paper. I [Vol . 18:1

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