This concise volume serves as a valuable resource on understanding the integration and impact of generative AI (GenAI) and evolving technologies on translation workflows.
This concise volume serves as a valuable resource on understanding the integration and impact of generative AI (GenAI) and evolving technologies on translation workflows.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Produktdetails
Produktdetails
Routledge Focus on Translation and Interpreting Studies
Michä Kornacki is Assistant Professor at the Institute of English Studies at the University of ¿ód¿, Poland. Paulina Pietrzak is Associate Professor at the Institute of English Studies at the University of ¿ód¿, Poland.
Inhaltsangabe
Contents List of Figures List of Tables Introduction Chapter 1: (R)evolution of translation technology 1.1. History and evolution of translation tools 1.1.1. Machine translation 1.1.2. Computer-assisted translation (CAT) tools 1.1.3. Translation management systems 1.1.4. Writing assistants and checking tools 1.1.5. Generative artificial intelligence in translation 1.2. The current state of translation technology 1.3. Stages of AI development Chapter 2: Translator-AI interaction 2.1. Augmented translation 2.2. Hybrid workflows in translation 2.3. The impact of technology on translator profession: new avenues and new anxieties 2.4. Ethical considerations in AI-assisted language service provision Chapter 3: Translators as AI-assisted language specialists 3.1. Translators' new roles and status 3.2. Future translator expertise: what is missing? 3.3. Technical skills for hybrid workflows 3.4. From anxiety to digital resilience 3.5. Personal resources and metacognitive capacity 3.6. The translator's self-concept in AI interactions Chapter 4: Attitudes towards AI in translation: an academic exploration 4.1. Research design 4.2. Limitations of the study 4.3. Data analysis 4.3.1. Findings on the use of AI technologies in translation 4.3.2. Perspectives on GenAI integration in translator education 4.3.3. Risks associated with using GenAI tools in translator training 4.4. Summary of the findings: challenges and lessons learned Chapter 5. Implications for translator training 5.1. To teach or not to teach? 5.2. What's in it for translation students? 5.3. Suggested ways of introducing AI-assisted translation practice 5.3.1. Exercises in AI-assisted translation 5.3.2. AI tools for terminology management 5.3.3. AI-assisted quality assessment 5.3.4. AI-generated feedback 5.3.5. Ethical code of conduct in AI use 5.4. Fostering personal resources in translator training 5.4.1. Self-reflection: what am I missing? 5.4.2. Self-efficacy: building digital resilience 5.4.3. Self-concept: reducing technological anxiety Chapter 6: Final reflections Appendix Index
Contents List of Figures List of Tables Introduction Chapter 1: (R)evolution of translation technology 1.1. History and evolution of translation tools 1.1.1. Machine translation 1.1.2. Computer-assisted translation (CAT) tools 1.1.3. Translation management systems 1.1.4. Writing assistants and checking tools 1.1.5. Generative artificial intelligence in translation 1.2. The current state of translation technology 1.3. Stages of AI development Chapter 2: Translator-AI interaction 2.1. Augmented translation 2.2. Hybrid workflows in translation 2.3. The impact of technology on translator profession: new avenues and new anxieties 2.4. Ethical considerations in AI-assisted language service provision Chapter 3: Translators as AI-assisted language specialists 3.1. Translators' new roles and status 3.2. Future translator expertise: what is missing? 3.3. Technical skills for hybrid workflows 3.4. From anxiety to digital resilience 3.5. Personal resources and metacognitive capacity 3.6. The translator's self-concept in AI interactions Chapter 4: Attitudes towards AI in translation: an academic exploration 4.1. Research design 4.2. Limitations of the study 4.3. Data analysis 4.3.1. Findings on the use of AI technologies in translation 4.3.2. Perspectives on GenAI integration in translator education 4.3.3. Risks associated with using GenAI tools in translator training 4.4. Summary of the findings: challenges and lessons learned Chapter 5. Implications for translator training 5.1. To teach or not to teach? 5.2. What's in it for translation students? 5.3. Suggested ways of introducing AI-assisted translation practice 5.3.1. Exercises in AI-assisted translation 5.3.2. AI tools for terminology management 5.3.3. AI-assisted quality assessment 5.3.4. AI-generated feedback 5.3.5. Ethical code of conduct in AI use 5.4. Fostering personal resources in translator training 5.4.1. Self-reflection: what am I missing? 5.4.2. Self-efficacy: building digital resilience 5.4.3. Self-concept: reducing technological anxiety Chapter 6: Final reflections Appendix Index
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