Generative artificial intelligence (GenAI) is disrupting creative work and challenging occupational identities, yet limited research has examined how creators experience and respond to these changes. Drawing on Albert Ellis’s ABC model, this study investigates relationships among GenAI adoption, identity threat, job crafting, and identity consequences. Using a two-stage exploratory mixed-method design with digital content creators in China, we combined BERTopic analysis of 2994 open-ended responses with structural equation modelling of matched survey data from 1698 creators. The findings show that GenAI is widely perceived through coexisting beliefs about threat, opportunity, and the unknown, and that these beliefs give rise to differentiated job crafting behaviours, including approach crafting, avoidance crafting, and identity crafting. Notably, identity crafting plays an important role in fostering a responsible creative identity and self-actualization. This study advances theorizing on AI technological innovation and creative labour by showing how job crafting translates GenAI disruption into responsibility-oriented and meaning-centered identity reshaping. It also offers actionable insights for creators, platforms, and creative communities seeking to support collaborative, sustainable, and ethically grounded human–AI co-creation.
The method, ECCOLA, is presented, which aims at making the high-level AI ethics principles more practical, making it possible for developers to more easily implement them in practice.
Ville Vakkuri, Kai-Kristian Kemell, P. Abrahamsson· EUROMICRO Conference on Soft...· 64 citations· ⚡6
The goal is to not only refine the accuracy of the LLM-based tool but also to underscore its potential in streamlining the software development lifecycle through proactive code improvement and education.
Z. Rasheed, Malik Abdul Sami, Muhammad Waseem et al.· arXiv.org· 62 citations· ⚡3
A comprehensive overview of how enhanced sampling methods are reshaping the field, with a particular focus on the data-driven construction of collective variables, is provided.
Kai Zhu, Enrico Trizio, Jintu Zhang et al.· Chemical Reviews· 58 citations
The use of large language models to automatically improve the user story quality in Austrian Post Group IT agile teams is explored, with a reference model for an Autonomous LLM-based Agent System developed and implemented at the company.
Zheying Zhang, M. Rayhan, Tomas Herda et al.· International Conference on...· 48 citations· ⚡4
This paper introduces a novel multi-AI-agent system designed to fully automate SLRs, and demonstrates how it substantially reduces the time and effort traditionally required for SLRs while maintaining comprehensiveness and precision.
Abdul Malik Sami, Z. Rasheed, Kai-Kristian Kemell et al.· arXiv.org· 44 citations· ⚡2
The proposed LLM-based multi-agent system automates qualitative data analysis process, creating opportunities for researchers and practitioners, and future improvements focus on enhancing multilingual performance and integrating continuous expert feedback.
Z. Rasheed, Muhammad Waseem, Aakash Ahmad et al.· arXiv.org· 41 citations
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