AI & Society Journal

Deadline: June 30, 2025

Since the unprecedented agreement that the Writers Guild of America (WGA) managed to negotiate in relation to the use of generative AI in the workplace in 2023, cultural workers—in sectors such as music, film and television, journalism, social media content creation and gaming have been in the spotlight as one of the main exponents of how workers, individually and collectively, have responded to the development of generative AI around the world. These issues range from questions of workforce replacement and the reshaping of labor processes, working conditions, forms of building collectivities (e.g. unions, associations, cooperatives, guilds) and how cultural workers have understood the meanings and practices of AI (e.g. culturally, discursively and politically).

Themes:

This topical collection of AI & Society (AI&S) focuses on how workers in the cultural sector—understood as actors, writers, musicians, game performers, journalists, content creators, etc.—are engaging with generative AI in the workplace. It aims to analyze, on the one hand, the ways that cultural labor is being reshaped by AI in terms of labor process and cultures of production, and, on other hand, the ways that cultural workers are collectively fighting back against AI, through bargaining, co-operative formation or refusal. We are looking for articles that centre workers and work experience in relation to AI around the world. The collection will include empirically-grounded articles with original arguments covering different geographies and sectors. Topics and themes will include:

• Labor Processes: How generative AI is reshaping labor processes in the cultural sector, both within and beyond the point of production, including the role of social reproduction.
  
• Cultures of Production: How generative AI is reshaping the cultures of production and creative practices in cultural industries.
  
• Working Conditions: Experiences of everyday work with generative AI in the cultural sector around the world, and in different sub-sectors of the cultural industries.
  
• Identities: The ways that social and global hierarchies and intersectional inequalities (e.g. gender, sexuality, race, ability, nationality, class, etc.) embedded in generative AI models intersect with uses, experiences and organizations of power in the cultural industries.
  
• Data Work: The role of AI data work (Miceli & Posada 2022) in cultural industries. Who are the data workers feeding the machine (Muldoon, Graham & Cant 2024) for the cultural sector, and what are the conditions and politics of their labor?
  
• Worker Organizing: The ways that cultural workers are organizing for and against generative AI in the workplace. How are workers bargaining, campaigning, protesting and mobilizing in relation to AI? How do cultural workers intervene in policies through collective action? How do they collectively learn about and come to understand generative AI?
  
• Worker-Led Reappropriations: How cultural workers are reappropriating AI in non-dominant work arrangements, e.g. cooperatives and collectives, in terms of “computing otherwise” (Amrute & Murillo 2020)?
  
• Geographies and Value Chains: The commonalities and differences of cultural workers’ experiences in relation to generative AI. The role of global dependencies in the cultural sector in relation to AI (e.g. a fair agreement for an actor in one country can badly affect voice actors in another country). How to connect the AI value chains in the cultural industries.
  
• Industry Changes: How is generative AI changing cultural sectors at the industry level? What are the impacts of Big Tech’s increasing involvement in cultural production, especially their investments in generative AI? Who are the tech workers behind these projects on generative AI in cultural production? How is the political economy of cultural production transforming due to the introduction of generative AI?
  
• Intimacies: How generative AI is transforming the nature of relationships between cultural producers and their audiences and fans, for example through the introduction of personalized chatbots trained on the data of (micro)celebrities and through the emergence of AI-generated influencers.

Guest Editors:

• Dr Rafael Grohmann, University of Toronto, Canada, rafael.grohmann@utoronto.ca
  
• Dr Daphne Idiz, University of Toronto, Canada, daphne.idiz@utoronto.ca
  
• Dr Zoë Glatt, Microsoft’s Social Media Collective, United States, zoe.glatt@microsoft.com 
  

Contribution Types:

We welcome contributions in the format of research papers (max 10K words) with substantial theoretical, methodological, and empirical interventions. Original papers will be double blind peer-reviewed by two reviewers and the editorial team.

Firstly, send a 500-word abstract to rafael.grohmann@utoronto.ca, outlining a) the main argument; b) the theoretical background; c) methods; d) main findings. If your abstract is accepted, you will be invited to submit the full manuscript.

Important Dates:

• Abstract submission: 30th June 2025
  
• Manuscript submission: 31st October 2025
  
• Notifications: 28th February 2026
  
• Revised papers due: 30th April 2026

Submission:

You can find more information about formatting under the section “Submission guidelines” ​https://www.springer.com/journal/146. 

For inquiries and to submit your abstract, please contact: rafael.grohmann@utoronto.ca  with the subject “AI&S Special issue on Cultural Workers and Generative AI.”

After approval of the abstract please do submit your manuscript via the 'Submit your manuscript' button available on https://www.springer.com/journal/146.