ABSTRACT Multistakeholderism is widely regarded as a means to ensure equal representation for stakeholders, promote democratic processes, and enable effective governance. Given the interconnected nature of the internet, much of global internet governance is influenced by multistakeholder approaches with a prominent role of transnational actors. This raises questions about the effects of transnational influence on the legitimacy of multistakeholder internet governance. Therefore, this article explores how transnational influence affects the input, throughput, and output legitimacy of the Internet Governance Forum (IGF), a key node within the internet governance ecosystem. The analysis combines qualitative content analysis of 600 statements made during cybersecurity governance debates at the IGF from 2016 to 2023 with 18 expert interviews. The findings reveal that transnational actors affect the IGF's legitimacy unevenly, producing both legitimacy gains and legitimacy deficits. Broad stakeholder participation contributes to high levels of input legitimacy, yet the prominence of specific transnational actors in panel discussions and policy contributions raises concerns regarding throughput legitimacy, reflecting persistent inequalities in access, resources, and visibility. While transnational actors' contributions significantly shape IGF policy outcomes, their influence is disproportionately concentrated among Global North actors. This article contributes to scholarship on transnational influence, the legitimacy of international organizations, and multistakeholderism.
ABSTRACT US gambling debates often center on the legal status of sports‐betting, but advertising can also be used as a distinct policy lever. This paper presents the findings of two related studies. Study 1 links quarterly state‐level gambling advertising outlays across paid media (2014–2023) to Google Trends indices for 116 problem‐gambling help‐seeking queries across 41 states (1640 state‐quarters). Study 2 combines surveys with passive digital traces from 419 exposure‐eligible mobile‐platform users. Higher state‐level ad spend, but not sports‐betting legal status, was associated with greater help‐seeking search interest, and this association strengthened over time. Platform‐specific gambling‐ad exposure on Facebook, TikTok, and X was associated with gambler status, gambling frequency, and the probability of any observed gambling‐site visit. Clean gambling ads were also associated with higher 24‐h odds of subsequent gambling touchpoints, especially web visits; among gamblers, ad‐triggered touchpoints were associated with problem‐gambling scores more consistently than raw clean ad volume. Convergent state‐level and individual‐level evidence links gambling advertising with engagement and harm‐related indicators, while the observational designs do not identify causal effects. The findings support stronger restrictions on advertising volume, placement, inducements, and targeting.
ABSTRACT As generative artificial intelligence (GenAI) technology rapidly permeates higher education, it creates opportunities to transform teaching, research, and workforce preparation while raising ethical, social and environmental concerns. Academic scientists have a unique role in this transition as their early exposure to publicly accessible GenAI tools shapes emerging practices, norms, and institutional responses. Existing research often treats AI‐related risk as a single construct, limiting understanding of how distinct risk dimensions shape regulatory preferences. This study investigates how academic scientists’ experience with GenAI relates to risk perceptions over agency loss and data breach, and how these perceptions are associated with their regulatory attitudes during its formative stage. Using survey data collected between September and November 2023, shortly after ChatGPT became widely accessible, we find that greater GenAI experience is associated with lower perceived risks. Meanwhile, different risk perceptions are linked to distinct regulatory preferences: perceived risk of agency loss is associated with a greater likelihood of supporting federal regulation and a lower likelihood of supporting academic self‐regulation, whereas perceived data breach risk is associated with a greater likelihood of supporting federal regulation but not associated with the likelihood of supporting self‐regulation. These findings provide an early baseline understanding of faculty attitudes toward GenAI regulation in academic contexts.
The scale and volume of user-generated content produced in the Web 2.0 era have led to content moderation becoming an essential aspect of most online platforms' business models. This form of digital labour is often performed by human content moderators (CMs) in the Global South, however, artificial intelligence (AI) technology has increasingly changed the nature of this work leading to serious questions about the future of this industry. A mixed-methods survey was conducted with Africa-based CMS (n = 107) who responded to several open-ended questions related to their perceptions of AI and its potential use in content moderation. Thematic analysis revealed strong support for the use of AI in content moderation. However, CMs noted several barriers to AI implementation, such as an inability to apply context, which limits its efficacy. The findings suggest that African CMs appreciate the potential benefits that AI can offer to the content moderation industry, yet still see a clear need for AI to be balanced with human oversight to properly address the contextual nuance that is inherent to the role. Web 2.0(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic).(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)"(sic)(sic)(sic)(sic)"(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(CMs)(sic)(sic);(sic)(sic), (sic)(sic)(sic)(sic)(AI)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic).(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(n = 107)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)AI(sic)(sic)(sic)(sic)AI(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic).(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)AI(sic)(sic)(sic)(sic)(sic)(sic)(sic).(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)AI(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)--(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)--(sic)(sic)(sic)(sic)(sic)(sic)(sic).(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)AI(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)AI(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic). La magnitud y el volumen del contenido generado por los usuarios en la era de la Web 2.0 han convertido la moderaci & oacute;n de contenido en un aspecto esencial de los modelos de negocio de la mayor & iacute;a de las plataformas en l & iacute;nea. Esta labor digital suele ser realizada por moderadores de contenido humanos (MC) en el Sur Global; sin embargo, la tecnolog & iacute;a de inteligencia artificial (IA) ha transformado cada vez m & aacute;s la naturaleza de este trabajo, lo que plantea serias dudas sobre el futuro de este sector. Se realiz & oacute; una encuesta con m & eacute;todos mixtos a MC con sede en & Aacute;frica (n = 107), quienes respondieron a varias preguntas abiertas relacionadas con sus percepciones sobre la IA y su posible uso en la moderaci & oacute;n de contenido. El an & aacute;lisis tem & aacute;tico revel & oacute; un fuerte apoyo al uso de la IA en la moderaci & oacute;n de contenido. No obstante, los MC se & ntilde;alaron varias barreras para la implementaci & oacute;n de la IA, como la incapacidad de aplicar el contexto, lo que limita su eficacia. Los resultados sugieren que los MC africanos aprecian los beneficios potenciales que la IA puede ofrecer al sector de la moderaci & oacute;n de contenido, pero a & uacute;n perciben la necesidad de equilibrar la IA con la supervisi & oacute;n humana para abordar adecuadamente los matices contextuales inherentes a esta funci & oacute;n.
As algorithmic platforms increasingly mediate public service delivery, data-driven systems shape how citizens experience trust and privacy while generating digital traces that inform policy decisions. In the context of public mobility, these dynamics manifest through routine interactions with systems that track movement, log behavior, and process personal information, transforming everyday travel into a site of data extraction with policy implications. This study investigates how individuals in Chile interpret and respond to digital transport systems, focusing on their concerns about data privacy, institutional trust, and the value of the data they generate. Drawing on interviews (N = 27) and six focus groups (N = 48), the paper uses the notion of privacy asymmetries to characterize the uneven dispositions users hold across three dimensions: (1) between functionality trust in digital platforms and data privacy concerns; (2) between acceptance of data collection practices by private companies and by the state, and (3) across demographic lines, particularly gender. These asymmetries reflect how historical legacies, political context, and sociodemographic categories shape trust and skepticism toward data use in public systems. (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic).(sic)(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)--(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic),(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic).(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic),(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic).(sic)(sic)(sic)(sic)(N=27)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(N=48)(sic)(sic)(sic), (sic)(sic)(sic)(sic)"(sic)(sic)(sic)(sic)(sic)"(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic):(1)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic);(2)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic);(3)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic) ((sic)(sic)(sic)(sic)(sic)) (sic)(sic)(sic)(sic).(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic),(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic). A medida que las plataformas algor & iacute;tmicas median cada vez m & aacute;s en la prestaci & oacute;n de servicios p & uacute;blicos, los sistemas basados en datos configuran la forma en que los ciudadanos experimentan la confianza y la privacidad, al tiempo que generan rastros digitales que fundamentan las decisiones pol & iacute;ticas. En el contexto de la movilidad p & uacute;blica, estas din & aacute;micas se manifiestan a trav & eacute;s de interacciones rutinarias con sistemas que rastrean el movimiento, registran el comportamiento y procesan informaci & oacute;n personal, transformando los desplazamientos cotidianos en un espacio de extracci & oacute;n de datos con implicaciones pol & iacute;ticas. Este estudio investiga c & oacute;mo los individuos en Chile interpretan y responden a los sistemas de transporte digitales, centr & aacute;ndose en sus preocupaciones sobre la privacidad de los datos, la confianza institucional y el valor de los datos que generan. A partir de entrevistas (N = 27) y seis grupos focales (N = 48), el art & iacute;culo utiliza la noci & oacute;n de asimetr & iacute;as de privacidad para caracterizar las diferentes posturas de los usuarios en tres dimensiones: (1) entre la confianza en la funcionalidad de las plataformas digitales y las preocupaciones sobre la privacidad de los datos; (2) entre la aceptaci & oacute;n de las pr & aacute;cticas de recopilaci & oacute;n de datos por parte de empresas privadas y del Estado; y (3) en funci & oacute;n de las caracter & iacute;sticas demogr & aacute;ficas, en particular el g & eacute;nero. Estas asimetr & iacute;as reflejan c & oacute;mo los legados hist & oacute;ricos, el contexto pol & iacute;tico y las categor & iacute;as sociodemogr & aacute;ficas configuran la confianza y el escepticismo hacia el uso de datos en los sistemas p & uacute;blicos.
