Aug 2026· AI & SOCIETY· 0 citations· 38 references
TL;DR
This study shows AI enables a cohort of “Internet entrepreneurs” to enter cultural production, driven by a “money hustling culture” that encourages formerly idle and low-skilled individuals to pursue rapid monetisation.
Abstract
As generative AI becomes embedded in platform-based cultural production, new forms of creative labour are emerging that challenge established understandings of what it means to be a “creator.” This article examines AI slop creators in China, a group that uses generative tools to benchmark viral content, test formats, operate matrix account systems, and formalise production, transforming virality from an unpredictable outcome into an object of systematic management. Drawing on ethnographic research conducted between 2023 and 2025 in China, this study shows AI enables a cohort of “Internet entrepreneurs” to enter cultural production, driven by a “money hustling culture” that encourages formerly idle and low-skilled individuals to pursue rapid monetisation. The findings suggest that AI slop creators organise production less around authorship, identity and aspiration, and more around operational mastery, strategic disposability, and algorithmic opportunism. Rather than cultivating personal brands, they prioritise speed, scale and adaptability, pointing toward a post-creator mode of cultural labour in contemporary platform economies.
With the rapid diffusion of generative AI-based short-video technologies, AI-generated cute pet videos have emerged as a representative medium through which the public’s technological anxiety surrounding artificial intelligence is alleviated by means of healing visual symbols. These videos also provide a valuable lens for observing public perceptions of AI and the formation of collective sociotechnical imaginaries. Existing studies on AI-generated content (AIGC) in the entertainment industry have primarily focused on industrial production, content governance, and user experience, while paying insufficient attention to how sociotechnical imaginaries of AI are co-constructed through interactions among multiple stakeholders. Drawing upon Sheila Jasanoff’s theory of sociotechnical imaginaries, this study analyzes 398 AI-generated cute pet short videos and 4,358 valid user comments published on Douyin. Employing multimodal discourse analysis, the study codes and interprets the discourses of three key actors: technology companies, short-video platforms, and ordinary users. The findings reveal that continuous interaction and negotiation among these actors have established a complete closed-loop mechanism integrating technological supply, platform governance, and user feedback. Through this dynamic process, they collectively construct an AI imaginary that is closely aligned with everyday entertainment experiences and centered on emotional resonance.
Siyuan Zhang· Advances in Education, Human...· 0 citations
It is argued that AI-driven “style replication” is fundamentally a negotiation of social relations, one that recentres platform power and reorganises the conditions of human-AI collaboration.
Generative artificial intelligence (AI) is revolutionizing digital marketing by enabling content creation, customer engagement, and strategic decision-making at unprecedented speed and scale. Yet, despite its transformative potential, research on the factors driving marketers’ adoption of generative AI tools such as ChatGPT remains scarce, particularly in emerging economies. Against this backdrop, this study aims to investigate the determinants influencing digital marketers’ adoption of ChatGPT and chart directions for future research. Quantitative research design was employed, drawing on constructs from the TAM and the UTAUT, while incorporating contextual variables such as industry influence, organizational culture, and perceived credibility. Data were collected from 500 digital marketers in Bangladesh using convenience sampling and analyzed using PLS-SEM. The findings reveal that performance expectancy, awareness, effort expectancy, and industry influence significantly shape attitudes toward ChatGPT, whereas organizational culture does not play a significant role. Attitude and perceived credibility emerged as the strongest predictors of actual usage, underscoring the centrality of favorable perceptions and trust in adoption behavior. The chapter makes threefold contributions. Academically, it extends adoption models by highlighting contextual variables in the adoption of AI. Practically, it offers guidance for marketers and organizations to build trust and showcase performance benefits. At the policy level, it calls for regulatory frameworks ensuring credibility and responsible use. Collectively, the study enriches understanding of generative AI adoption and lays a foundation for future research in this rapidly evolving field.
Md. Soleman Mollik, Mohammad Faruk, Md. Marsudur Rahman· Asian Management and Busines...· 0 citations
Streaming has transformed the landscape of screen production since Netflix launched its video-on-demand service in 2007 and later moved into commissioning content. Rather than treating streaming as a universal industrial logic, this special issue foregrounds the contextually-bound practices, infrastructures, and technologies that condition the creative labor behind these productions. “Streaming production cultures” emerges as a subfield within production studies that deserves scholarly attention, and the featured articles surface empirical findings that help demarcate the debates fueling this area of inquiry. Despite challenges in accessing streaming production networks, we argue for a bottom-up approach that attends to the lived experiences of workers in the online screen industry. The contributions apply this lens to a range of production cultures, spanning diverse media services that operate at national, regional, and global scales. As such, this special issue provides a kaleidoscope of streaming production research in order to advance this critical field.
D. Idiz, Nina Vindum Rasmussen· Television & New Media· 0 citations
The findings reveal an “Authenticity Paradox”: the lack of traditional human touch in AIGC does not alienate Generation Z; rather, the resulting “mindful friction”—quantified by a significant negative path effect between sentiment and identity—functions as a subcultural filter.
Jun Liang, Yixin Li, Zhileng Xiong· Frontiers in Psychology· 0 citations
This article examines the platform-creator dyadic relationship that has taken shape around generative AI visual media. Rather than asking only whether AIGC (Artificial Intelligence Generated Content) lowers the technical threshold of image and video production, it asks how platforms rearrange Internet communication power through infrastructure, algorithms, data capture, and visibility allocation. Drawing on Manuel Castells's theory of communication power, the study develops a three-part account of production power, distribution power, and definitional power in AIGC platforms. The analysis combines theoretical interpretation, public platform cases, and practice-based observation. It argues that AIGC platforms do not simply de-professionalise or decentralise creation. Their low-threshold rhetoric invites ordinary users into visual production, but it also obscures the continuing value of professional expertise. Platform control over models, credits, computing resources, and interfaces then turns creative capacity into a conditionally accessible service. Algorithmic black boxes and traffic recommendation systems further shape how works circulate, are evaluated, and acquire value. AIGC platforms therefore widen entry while re-concentrating key forms of production, distribution, and definitional power. The study offers a cautious framework for creators, platform observers, and scholars of communication power.
Yufeng Deng· Lecture Notes in Education P...· 0 citations