AI Interpretation Use Cases
This project explored the human dimensions of interpretation and the potential role of AI in supporting it. While translation apps focus on word-for-word accuracy, interpretation requires cultural sensitivity, nuance, and contextual understanding. The study examined what makes interpretation uniquely human, and where AI might add value without undermining these human elements.
Methods & Rationale
We designed this study in two phases to better understand the human side of interpretation and how it differs from simple translation. In the first phase, we ran 25 dyad interviews where pairs of bilingual participants had conversations through an interpreter. Afterward, each person reflected on what they understood from the exchange, what stood out, and how the interpreter’s style shaped the conversation.
The second phase expanded to 25 triad interviews with three bilingual speakers and three interpreters. This added complexity let us see how interpretation works when multiple voices, perspectives, and cultural cues overlap. Each session included both the conversation itself and a mix of individual and group reflections.
In total, we held 50 sessions on Zoom using the interpreter setting, with 125 participants fluent in English and one of six other languages: Spanish, French, Chinese, Japanese, Portuguese, and Hindi.
We designed the study to capture both the practical flow of communication and the cultural nuances interpreters contribute. By comparing one-on-one and group conversations, we were able to see how communication dynamics shift across contexts, and which aspects of language and interaction become most important in each setting.
Participants & Constraints
A total of 50 sessions were conducted: 25 dyad interviews and 25 triad interviews, involving 125 participants overall. All participants were bilingual, fluent in English and one of the following languages: Spanish, French, Chinese, Japanese, Portuguese, or Hindi.
Constraints
Remote setting: All sessions took place on Zoom, limiting the role of nonverbal cues such as eye contact and body language, which are central to in-person interpretation.
Technological mediation: Reliance on Zoom’s interpreter function may have influenced flow and naturalness of conversation.
Research Questions
What are the parts of interpretation that are uniquely human?
How do interpreters incorporate culture, tone, and context into communication?
In what settings could AI interpretation add value without losing essential human elements?
Data Collection & Synthesis
The study was structured in two phases to capture both one-on-one and group dynamics of interpretation. The design intentionally involved bilingual participants who could reflect on both the content of the interpreted conversation and the process itself.
Data Collection & Synthesis
Phase 1: Dyad Interviews — Two bilingual speakers conversed through an interpreter, followed by reflections on what they understood, how the conversation felt, and observations about the interpreter’s communication choices.
Phase 2: Triad Interviews — Three bilingual speakers engaged in conversation via three interpreters, followed by individual interviews and group discussion.
In total: 50 sessions, 90 minutes each.
Data was analyzed for recurring themes, with particular focus on cultural nuance, communication style, and breakdowns in understanding.
In Conclusion
Key Insights
Culture shapes language
Interpretation is not just about transferring words but about carrying meaning across cultural contexts. Culture is deeply embedded in the way language is spoken and cannot be separated from it. This makes interpretation uniquely human because it requires not only accuracy but also sensitivity to cultural nuance, tone, and context.
Limits of AI
AI struggles with conversational interpretation, where meaning is shaped by subtle cultural and nonverbal signals.
High-value use cases exist
AI interpretation could be valuable in settings that require precision—such as medical or legal contexts—where factual accuracy is prioritized over conversational flow.
Recommendations
Position AI interpretation as a complement to human interpreters, not a replacement, especially in relational or culturally sensitive contexts.
Prioritize development for use cases where accuracy outweighs nuance (e.g., healthcare, law).
Consider hybrid models where AI handles translation of factual information while humans mediate cultural and contextual meaning.
Explore how Meta Glasses could integrate AI interpretation in situational, utility-driven contexts while acknowledging the technology’s limits in everyday conversation.
Reflections
This project was challenging in the sense of managing technology and people. There was much reliance on technology to work in zoom as well as getting multiple intepretors on and making sure everyone was in the right zoom channel for this to work. We had many periods where we had to adjust the tech and it caused some delays but it was my job as the moderator to keep participants going and the flow to continue. Some of our language speakers were also not as fluent as they claimed which proved difficult in fully grasping the depth of how well the intepretation worked. But all in all, this was a really interesting project.