Shall AI moderators be made visible? Perception of accountability and trust in moderation systems on social media platforms

Ozanne, Marie; Bhandari, Aparajita; Bazarova, Natalya N.; DiFranzo, Dominic

doi:10.1177/20539517221115666

Cited by 10 publications

(2 citation statements)

References 55 publications

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“…For instance, warning labels are more effective when attributed to fact-checkers than layperson crowds (38). Algorithmic content moderation also suffers from low perceived confidencelabels attributed to AI are even less effective than those from the public (38), and visible AI moderator systems are subject to less perceived trust and accountability in the moderation process (39). Furthermore, a recent experiment of 100 Facebook users found that moderation decisions made by expert panels were perceived as more legitimate than decisions from layperson juries or algorithms (40).…”

Section: Significance Statementmentioning

confidence: 99%

Perceived legitimacy of layperson and expert content moderators

Martel,

Berinsky,

Rand

et al. 2024

Preprint

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Content moderation is a critical aspect of platform governance on social media and of particular relevance to addressing the belief in and spread of misinformation. However, current content moderation practices have been criticized as unjust. This raises an important question – who do Americans want deciding whether online content is harmfully misleading? We conducted a nationally representative conjoint survey experiment (N=3,000) in which U.S. participants evaluated the legitimacy of hypothetical content moderation juries tasked with evaluating whether online content was harmfully misleading. These moderation juries varied on whether they were described as consisting of experts (e.g., domain experts), laypeople (e.g., social media users), or non-juries (e.g., computer algorithm). We also randomized features of jury composition (size, necessary qualifications) and whether juries engaged in discussion during content evaluation. Overall, participants evaluated expert juries as more legitimate than layperson juries or a computer algorithm. However, modifying layperson jury features helped increase legitimacy perceptions – nationally representative or politically balanced composition enhanced legitimacy, as did increased size, individual juror knowledge qualifications, and enabling juror discussion., Maximally legitimate layperson juries were comparably legitimate to expert panels. Republicans perceived experts as less legitimate compared to Democrats, but still more legitimate than baseline layperson juries. Conversely, larger lay juries with news knowledge qualifications who engaged in discussion were perceived as more legitimate across the political spectrum. Our findings shed light on the foundations of procedural legitimacy in content moderation and have implications for the design of online moderation systems.

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Section: Significance Statementmentioning

confidence: 99%

Perceived legitimacy of layperson and expert content moderators

Martel,

Berinsky,

Rand

et al. 2024

Preprint

View full text Add to dashboard Cite

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“…Greater consistency may lead to increased trust and improved discourse [35]. Unfortunately, public perception is that content moderation is inconsistently implemented [46,49]. Keller et al [34] also show it is often difficult to determine where, how and according to what rules content moderation is occurring.…”

Section: Introductionmentioning

confidence: 99%

"Community Guidelines Make this the Best Party on the Internet": An In-Depth Study of Online Platforms' Content Moderation Policies

Schaffner,

Bhagoji,

Cheng

et al. 2024

Proceedings of the CHI Conference on Human Factors in Computing Systems

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Moderating user-generated content on online platforms is crucial for balancing user safety and freedom of speech. Particularly in the United States, platforms are not subject to legal constraints prescribing permissible content. Each platform has thus developed bespoke content moderation policies, but there is little work towards a comparative understanding of these policies across platforms and topics. This paper presents the first systematic study of these policies from the 43 largest online platforms hosting user-generated content, focusing on policies around copyright infringement, harmful speech, and misleading content. We build a custom web-scraper to obtain policy text and develop a unified annotation scheme to analyze the text for the presence of critical components. We find significant structural and compositional variation in policies across topics and platforms, with some variation attributable to disparate legal groundings. We lay the groundwork for future studies of everevolving content moderation policies and their impact on users. CCS CONCEPTS• Human-centered computing → Empirical studies in collaborative and social computing; • Social and professional topics → Hate speech; Political speech; Governmental regulations.

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Enhancing Deliberation with Digital Democratic Innovations

Mikhaylovskaya

2024

Philos. Technol.

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Democratic innovations have been widely presented by both academics and practitioners as a potential remedy to the crisis of representative democracy. Many argue that deliberation should play a pivotal role in these innovations, fostering greater citizen participation and political influence. However, it remains unclear how digitalization affects the quality of deliberation—whether digital democratic innovations (DDIs) undermine or enhance deliberation. This paper takes an inductive approach in political theory to critically examine three features of online deliberation that matter for deliberative democracy: scale, transparency, and the facilitation of equality. It argues that the enhancement of equality should be given special attention when designing and implementing deliberative DDIs. Equality is a basic democratic value that is crucial for the intrinsic quality of deliberation. One way of enhancing equality through digital deliberative practices is via AI facilitation, which can assist human facilitators and help mitigate power dynamics, often present in non-digital settings.

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Shall AI moderators be made visible? Perception of accountability and trust in moderation systems on social media platforms

Cited by 10 publications

References 55 publications

Perceived legitimacy of layperson and expert content moderators

Perceived legitimacy of layperson and expert content moderators

"Community Guidelines Make this the Best Party on the Internet": An In-Depth Study of Online Platforms' Content Moderation Policies

Enhancing Deliberation with Digital Democratic Innovations

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