From fragmentation to collaboration
Building a multi-actor community for Al-Assisted translation
Bibliographic Data
| ID | 16675703 |
|---|---|
| Authors | Xiaoyan Tan (0009-0008-1439-190X, University of Warwick, corresponding author) |
| Year | 2026 |
| Pages | 1-22 |
| Publication date | 2026-04-13 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Perspectives (JOURNAL) |
| Journal identifiers | ISSN: 0907-676X • E-ISSN: 1747-6623 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/0907676x.2026.2649607 |
| OpenAlex | W7154094202 |
| Language | EN |
| References cited | 36 |
The integration of artificial intelligence (AI) into translation practices has profoundly reshaped professional workflows, redefined translator agency, and introduced pressing ethical, environmental, and socio-economic concerns. Existing studies and frameworks often prioritise individual agency while overlooking broader systemic misalignments – particularly between evolving AI technologies and underdeveloped regulatory oversight, between sophisticated digital tools and limited AI literacy among users, and between the speed of AI innovation and the slow evolution of professional training. Furthermore, digital divides across regions perpetuate AI (neo)coloniality and reinforce global inequalities. Recognising the interconnection of these issues, this paper proposes a multi-actor, augmented community for AI-assisted translation that foregrounds interdisciplinary collaboration, ethical innovation, and sustainable advancement. Drawing on the Community of Practice, it introduces a five-phase participatory framework, spanning from stakeholder mapping to challenge response, to serve as a roadmap for building this community. This framework is then applied to evaluate the EU AI Act, illustrating how these principles can inform and strengthen its implementation. Rather than casting AI as either a threat or a saviour, this article re-centres human agency to foster AI-assisted translation as a collaborative, human-centred practice. More broadly, this proposed approach offers a pathway towards an inclusive, adaptive, and ecologically conscious AI-human ecosystem.
Feature (linguistics · Fragmentation (computing · Process (computing · Term (time · Translation (biology · Natural Language Processing Techniques · Text Readability and Simplification · Translation Studies and Practices
Communities of Practice
Evolution of Wenger's concept of community of practice
Digital inequality beyond the digital divide
Society-in-the-loop
The Ethics of AI Ethics
Brussels effect or experimentalism? The EU AI Act and global standard-setting
From human-centered to social-centered artificial intelligence
What has changed with neural machine translation? A critical review of human factors
Environmental impact and net-zero pathways for sustainable artificial intelligence servers in the USA
A survey of machine translation competences
Translators in the platform economy
Digitalisation, neo-Taylorism and translation in the 2020s
The politics of machine translation. Reprogramming translation studies
Human-centric AI governance
Collaborative Governance in Theory and Practice
Situated Learning
| Citation velocity | historical |
|---|---|
| Highly cited | No |