Knowledge Resource · Open access
Research Summary: Locating Translation as a Craft in the Age of AI
- Original authors
- Attribution requires verification
- Original source
- arXiv — Computers and Society
- Summary & Analysis prepared by
- Aziz Shuaib Ausi
- Resource type
- Research Summary / Knowledge Resource
- Resource published on AZIZ OS
- 18 September 2026
- Last updated
- 22 September 2026
- Reading time
- 1 min
- Publication type
- Knowledge Resource
- Availability
- Open access
About this Summary & Analysis
AZIZ OS provides independently prepared summaries and analytical interpretations of externally published research and knowledge sources. The underlying works remain attributable to their original authors and rights holders. This resource is intended to improve accessibility and understanding and does not replace the original publication.
Rapid advancements in Large Language Models (LLMs) and other automated translation technologies are significantly impacting the professional translation sector. A study conducted with 19 professional translators reveals cautious adoption of these tools, with prevalent concerns regarding the potential displacement of human translation work by machine translation (MT) and LLMs.
Why it matters
The emergence of advanced AI-driven translation technologies presents both opportunities for efficiency gains and significant challenges to established professional practices. Understanding the perspectives of human practitioners is crucial for developing sustainable strategies that integrate technology while preserving human expertise and quality in specialized domains.
Key insights
- Large Language Models and similar automated methods are rapidly developing, influencing the landscape of translation technologies.
- Concerns are increasing within the translation community about the outsourcing of translator work to automated tools.
- Professional translators are cautious about integrating new technologies into their workflows.
- Translators express concerns regarding the implications of machine translation and LLMs on their profession.
Source
arXiv — Computers and Society — https://arxiv.org/abs/2604.00758
Related resources
Previous
Value Faces: Surfacing How Self-Presentation Shifts Across Relationships
Next
Detecting Deceptive Recruitment: A Signal-theoretic Machine Learning Framework for Early Identification of Labour Exploitation
From memorization to meaningful learning: ADEA webinar explores critical thinking for transformative education in Africa
Knowledge Resource
ADEA drums up support for a more focused push for classroom delivery at the IBSA Quality foundational learning symposium
Knowledge Resource
Beyond the lab: ecological validation of classroom-native multimodal learning analytics in an active learning classroom
Knowledge Resource
What makes a “good” counterexample? Criteria for the comparison of counterexamples and for fostering subject matter-oriented reflections among preservice teachers
Knowledge Resource
Predictive impact of supported teaching in school practicum on pre-service teachers’ professional readiness to teach foundational literacy and numeracy
Knowledge Resource
Welcoming Tom Savage as Coursera’s New Chief Legal Officer and Secretary
Knowledge Resource
Citation
Cite the original work (APA 7)
The original source is authoritative for this citation. Cite the source publication directly — this attribution is pending verification. Open the original source.
Verification
This is an authenticated AZIZ OS resource record.
- Verification ID
- ASA-EXE-2026-00720
- Version
- v1.0 · r0
- Issued
- 18 September 2026
- Resource prepared by
- Aziz Shuaib Ausi
- Resource status
- Research Summary / Knowledge Resource
- Underlying work
- Locating Translation as a Craft in the Age of AI
- Original authors
- Attribution requires verification
- Original source
- arXiv — Computers and Society
- Provenance status
- Attribution requires verification
- Rights
- Underlying publication rights remain with the respective copyright holder(s). Refer to the original source for authoritative publication and licensing information.
This verification confirms the AZIZ OS resource record and its documented provenance. It does not establish authorship of the underlying external work.