Notes: Translation concepts, AI-assisted reading responses, and course logistics

Key concepts in translation

• The course centers on two keywords: translation and the interplay between global society and public enterprise. The instructor builds on prior definitions of translation and expands with Glass/Glaser’s ideas and related case studies.
• Translation basics highlighted in the lecture:
  • Translation as a process: the activity of producing translation, including activities like using dictionaries and thought about word choice.
  • Translation as a product: the tangible output produced (the translated text).
  • Translation as a phenomenon: the broader topic and field of study around translation.
  • The importance of distinguishing these senses (process vs product vs phenomenon) in analysis and discussion.
• Jakobson’s tripartite framework for translation (three kinds of translation):
  • Intralingual translation: translation within the same language (e.g., English to English) where meaning is reformulated but language remains the same. Example discussed: interpreting a term like "pizza pie" as a regional or contextual variant of "pie".
  • Interlingual translation (translation proper): translation between different languages (language A to language B).
  • Intrasemiotic translation (intrasemiotic or intrasymiotic): translation between sign systems or media (e.g., film -> book, book -> podcast, podcast -> video).
• Language as a central but not sole focus: word clouds show that people associate translation with language, but other crucial aspects include communication, understanding, and cultural context.
• Non-linguistic facets of translation highlighted:
  • Communication and understanding as core aims in many domains (business, legal, medical, court-room contexts).
  • Cultural understanding and cross-cultural awareness as critical to effective translation.
  • Diversity, equity, inclusion, and multilingualism as themes connected to translation work.
  • Connections and bridging/bridging roles in translation, along with potential negatives like confusion or rewording when accuracy is lost.
• The idea that translation is not only linguistic but also a writerly act: translation involves style, tone, and the circumstances surrounding a message, especially in different professional contexts.
• A recurring motif: translation as a form of writing that can shape perception and action, not just convey information.

The two hands of translation: examples and deeper implications

• Intralingual translation examples:
  • English-to-English reinterpretation (regional or context-driven shifts). Example given: interpreting "sack" as a burlap sack vs. plastic bag depending on context.
  • This type demonstrates how meaning shifts within a language due to culture, region, or usage.
• Interlingual translation examples:
  • The classic cross-language translation work (A to B) and how it can create or reinforce borders between languages.
  • Theoretical note: translation can participate in constructing language boundaries rather than simply crossing them.
• Intrasemiotic translation examples:
  • Moving between media (film to book, book to podcast, etc.).
• The planet-money T-shirt case study (stand-in example) used to illustrate practical translation questions and real-world cases.
• The Corn sweat example from prior discussions used to illustrate how translation handles context and nuance.
• The “sac/p burlap sack” distinction shows how even everyday vocabulary can require translation decisions.

Reading selections and course logistics

• Required reading progression:
  • Week begins with no class on Labor Day; the next day (Tuesday) you read Chapter 1 of Kitsea and Demopolis’ Speaking in Tongues.
  • The book needs to be acquired; options discussed include Prairie Lights, IU bookstore, and PDFs with page numbers for citation.
  • If stock is an issue, the course will provide a scanned Chapter 1 to buy time; PDFs may be used to ensure page numbers align for assignments.
• Reading response structure and scheduling:
  • Each reading response must respond to the assigned day’s reading, not to earlier readings.
  • The blog/room for questions includes discussion about the availability of the book and alternative access options.

Reading responses: structure, options, and goals

• Two primary options for the reading response (for the day’s assignment):
  • Option A: Psychopomp chat (AI-assisted): five to seven prompts total, with back-and-forth exchanges between you and the AI, including:
  • A thesis stated by you, supported by evidence from the reading.
  • A final thesis statement produced by the AI in under $75\,\text{words}$ and then edited by you to reclaim your voice.
  • The process emphasizes authorial control, use of AI to model your own voice, and techniques to prevent the AI from diluting your argument.
  • Option B: Handwritten blog post: open-ended; you can express ethical objections to AI and choose to submit a handwritten version instead. If you object to AI use ethically, you must still complete a comparable amount of work (handwritten and photographed for submission).
• Number of paid opportunities and grading scheme:
  • A total of $11$ opportunities across AI-assisted and handwritten formats, but you must complete at least $10$ of them.
  • The grading emphasizes student engagement with course themes, close reading, and effective prompt engineering.

Detailed workflow for the AI-assisted reading response (Option A)

• Step 1: Exchange one
  • One sentence idea (your initial thesis concept) based on the reading.
• Step 2: Exchange two
  • Provide a concrete passage or evidence from the reading to support the idea (with page number or time stamp for a video).
• Steps 3–5: Exchanges three to five
  • Three to five exchanges with Psychopomp that help develop the idea, refine evidence, and push toward a more nuanced argument.
• Step 6: Penultimate exchange
  • Psychopomp drafts a thesis statement based on the exchanges above.
• Step 7: Final exchange
  • You present your edited thesis statement (less than $75\,\text{words}$) that you stand behind, with evidence and a coherent argument.
• Step 8: Transcripts and submission
  • Paste the full transcript of your side of the conversation (your prompts and your responses) into iCON; the transcript is what will be graded.
• Requirements and tips for AI use
  • Align with course themes: global perspective, translation and conflict, accessibility, live interpretation, labor and multilingualism, circulation, ethics, power, coloniality.
  • Show close reading: include a short quote with a page number (or a precise timestamp for video discussions).
  • Practice prompt engineering: define tasks, scope, constraints (e.g., the <75 words thesis), and request evidence and style guidance.
  • Model your own writing voice in the prompt to help the AI mirror a strong academic tone.
  • Provide corrective feedback: flag hallucinations or distortions and correct them with specific references to the text.
  • Avoid disclosing sensitive information and ensure you model clear, precise writing.
  • The AI is trained on public information and may hallucinate; you must supply the precise quotes, context, and page references from assigned texts.

Behavioral and ethical considerations for AI use in the course

• The instructor emphasizes that AI is a tool intended to prepare you for a future where AI is ubiquitous in academia and professional life.
• The university is developing an AI certificate program to formalize AI-literacy across programs; this course acts as an early exposure to AI-enabled writing and critical thinking.
• There is an accompanying AI acknowledgment form for courses that do not require AI use, to communicate why a student opts out and to ensure equivalent work is completed.
• The conversation highlights several ethical concerns:
  • Risk of plagiarism and misrepresentation when using AI tools.
  • The need to avoid sharing sensitive personal information with AI systems.
  • The importance of maintaining student voice and argument originality, with the AI assisting rather than replacing student thinking.
  • The necessity of fact-checking and citing sources properly when AI-generated content includes factual claims or quotes.
• The instructor stresses that if AI is used, it should be clearly integrated with citations and a demonstration of how the AI was used, including the exact prompts and the edited results.

Classroom tools and accessibility considerations

• Use of the course platform (iCON) to submit and view assignments, including AI-assisted reading responses.
• The instructor notes limitations of AI tools; e.g., poor performance with table-rich course schedules and time/date accuracy in tabular formats.
• The course includes a live AK (TA) discussion section on Fridays to continue dialogue about readings and responses.
• Emphasis on using AI responsibly to model and refine your own writing rather than producing generic, low-effort work.

Practical takeaways for students

• Focus on close reading and textual detail: cite specific passages with page numbers or precise time stamps.
• Be deliberate about your thesis: aim to produce a clear, original, argument that can be supported by close reading and textual evidence.
• If using AI, structure prompts to ensure concise output and room for editing; target five to seven prompts and a final under-75-word thesis for efficient editing.
• If opting out of AI, be prepared to provide a handwritten, legible, and photo-submitted alternative that demonstrates equivalent effort and engagement.
• Remember the tripartite nature of translation (intralingual, interlingual, intrasemiotic) and apply these lenses to readings and your own analyses.
• Consider ethical and practical implications of translation in real-world contexts (global society, public enterprise, and issues of equity, inclusion, and access).

Final practical notes you should remember for the assignment

• The two central concepts: translation as process, translation as product, and translation as phenomenon.
• The three kinds of translation to keep straight: intralingual, interlingual, and intrasemiotic.
• Always tie your analysis to specific passages, with page numbers or video timestamps.
• Use AI as a tool for refining your voice and argument, not as a substitute for your own thinking.
• Be mindful of the ethical framework: avoid sharing sensitive data; acknowledge AI use when appropriate; provide citations and check for factual accuracy.
• Keep your final thesis under $75\,\text{words}$, and ensure your final submission clearly reflects your own voice and understanding of the readings.

Quick glossary of terms mentioned in the lecture

• Translation: the act, product, or field of rendering meaning from one language or sign system to another.
• Intralingual translation: translation within a single language.
• Interlingual translation: translation between languages.
• Intrasemiotic translation (intrasmiotic): translation between sign systems or media (e.g., book to film, book to podcast).
• Global society: broader social context in which translation operates across cultures and nations.
• Public enterprise: translation work informed by practical, often policy-related, public-sector aims.
• Glass/Glaser definitions: translation as process; translation as product; translation as phenomenon.
• Noki Sakai: theorist cited in discussions of language borders and translation’s role in creating languages.
• Corn sweat: prior example used to illustrate translation in context.
• Planet Money T-shirt case study: a real-world case used to discuss translation issues.
• Kitsea and Demopolis, Speaking in Tongues: primary text for the first reading assignment.
• Prairie Lights: local bookstore mentioned as a source for course texts.
• iCON: course management system used for submissions and communication.
• Psychopomp (AI assistant): an AI tool used in Option A for reading responses, requiring careful prompt engineering and editing to preserve student voice.
• AI acknowledgment form: institutional tool to document AI use and related considerations in assignments.
• Garbage in, garbage out: reminder that input quality directly shapes AI output.

References to key numbers and constraints (formatted in LaTeX)

• Number of prompts in the Psychopomp chat: $5\text{-}to\text{-}7$ prompts per assignment.
• Final thesis length constraint for the AI-generated thesis: <75\,\text{words}.
• Total AI-assisted and handwritten opportunities: $11$ opportunities; must complete at least $10$.
• Number of basic uses for Psychopomp before trying others: $3$.
• Chapter 1 intake when stock is low: we provide scanned Chapter 1 liquidity (no explicit number of pages given).
• Number of top grades considered: $10$ (top $10$ grades).
• Number of opportunities that can be used if you submit more than the minimum: $11$ opportunities with a top-$10$ grading scheme.
• Page references and quotes: require a short quote with a page number; if the material is a video, provide a precise timestamp.
• Distinctions among translation types are qualitative rather than numerical, but the framework uses the tripartite model to categorize examples.