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Recent developments in Artificial Intelligence (AI) technology, especially Generative AI (GenAI), are helping individuals in content generation and collaborative work, thus enhancing the quality of the work. In this paper, we investigate if ChatGPT, one of the most popular GenAI tools, is ready to cater to the capabilities, expectations and needs of the non-English speaking, emergent users of digital technologies. To understand this space among non-English speakers, we conducted a user study with 15 non-English speakers in the state of Telangana, India. To assess the experience of emergent users using ChatGPT, we set them tasks of querying ChatGPT, and contrasted it with the same tasks on Google, a traditional search engine. We asked them to rate the platforms for ease of use and the understanding of the users’ language. We draw insights from the study through user ratings of the interactions and logging user observations during the interactions. We derive a few design recommendations for designers and researchers working on voice-based conversational GenAI tools.

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Is ChatGPT Ready for Indian-Language Speakers? Findings From a Preliminary Mixed Methods Study

  • 会议论文

  • 发表日期：

    2025年

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  • C. R. Chaitra,
  • Prajna Upadhyay,
  • Dipanjan Chakraborty

摘要

Recent developments in Artificial Intelligence (AI) technology, especially Generative AI (GenAI), are helping individuals in content generation and collaborative work, thus enhancing the quality of the work. In this paper, we investigate if ChatGPT, one of the most popular GenAI tools, is ready to cater to the capabilities, expectations and needs of the non-English speaking, emergent users of digital technologies. To understand this space among non-English speakers, we conducted a user study with 15 non-English speakers in the state of Telangana, India. To assess the experience of emergent users using ChatGPT, we set them tasks of querying ChatGPT, and contrasted it with the same tasks on Google, a traditional search engine. We asked them to rate the platforms for ease of use and the understanding of the users’ language. We draw insights from the study through user ratings of the interactions and logging user observations during the interactions. We derive a few design recommendations for designers and researchers working on voice-based conversational GenAI tools.