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1 1 (July 27, 2023)

handle is hein.crs/govemiz0001 and id is 1 raw text is: Con gressionol Research Service Informing the IegisI9tive debate since 1914 July 27, 2023 Social Media Algorithms: Content Recommendation, Moderation, and Congressional Considerations Social media plays an integral role in modern life for many. It facilitates the spread of information and serves as a key source of news, entertainment, and financial opportunity. In 2022, over 70% of Americans received some of their news from social media, according to the Pew Research Center. Recently, social media companies have faced criticism for potentially enabling the spread of harmful content, suppressing certain viewpoints, contributing to social polarization and radicalization, collecting and monetizing personal data, and adversely affecting children. As part of broader discussions around social media, some stakeholders and policymakers have taken interest in legislative proposals to regulate or address social media algorithms. This In Focus provides a high-level overview of content recommendation and moderation algorithms employed by social media platforms. It examines issues that arise from the use of social media algorithms and discusses considerations for Congress. Overview of Social Media Algorithms Social media companies use a number of algorithms and artificial intelligence (AI) systems to recommend or moderate content on their platforms and perform a variety of other functions. Algorithmic recommendation systems sort, curate, and disseminate content deemed relevant to specific users. Algorithmic content moderation systems are often used, along with human moderators, to identify and restrict illegal material and content that violates a company's policies and terms of use and service. Social media companies may also use algorithms for other purposes, such as targeting and delivering digital advertising or providing in-app search functions. Due to definitional ambiguity, algorithms are often conflated with a variety of different technologies and applications. For example, algorithms are often colloquially used to refer to artificial intelligence, but the two terms are not synonymous. Certain algorithms may fall under the broad category of Al (such as machine learning algorithms), while others do not use the predictive or data- mining techniques that are characteristic of Al. Due to this definitional ambiguity, some scholars and policymakers have opted to instead use the language of automated decision-making systems or automated systems in broader policy discussions-such as in the White House's Blueprint for an Al Bill of Rights. Additionally, some scholars and policymakers instead focus on specific outcomes and impacts regardless of what technology or technologies are implicated-such as discriminatory or disparate impacts. Congress may consider what language and terms are best suited for legislation targeting social media, or other technologies. Definitions * Algorithm: A specific process or sequence of computational steps followed by a computer in performing a task or problem-solving operation. Algorithms vary in complexity depending on the task and context. Recommendation Systems: Systems that use algorithms to personalize the sorting, ranking, and displaying of content for a user based on their previous engagements and other collected data. Also called recommendation engines or recommendation algorithms. Moderation Systems: Systems that use algorithms to identify, filter, and flag undesirable or illegal content for removal, demonetization, downranking, or other forms of moderation. Section 230 and Algorithms Section 230 of the Communications Act of 1934 (47 U.S.C. §230), enacted as part of the Communications Decency Act of 1996, broadly protects providers of interactive computer services from liability for information provided by a third party and content moderation decisions. There has been debate whether Section 230 liability protections should extend to the use of recommendation algorithms. So far, courts have held that recommendation algorithms are protected under Section 230. In 2023, the Supreme Court declined to weigh in on the Section 230 issue in two cases: Twitter v. Taamneh, No. 21-1496, and Gonzalez v. Google LLC, No. 21-1333. Both cases considered whether social media companies could be liable for recommending terrorist content. The Court did not rule on whether Section 230 granted immunity to the companies' recommendation algorithms. Instead, it concluded that the companies-regardless of Section 230- were not liable under the relevant antiterrorism federal statute because their conduct did not amount to aiding and abetting an act of international terrorism. For more information on Section 230, see CRS Report R46751, Section 230: An Overview, by Valerie C. Brannon and Eric N. Holmes. Issues and Concerns Algorithms are a key component of social media platforms. They help sort, moderate, and disseminate massive volumes of user-generated content to individuals. This in turn facilitates targeted digital advertising, a major source of revenue for social media platforms. However, policymakers, stakeholders, and researchers have raised concerns about their use. 0

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