mlsanityData to 14 Oct 2026

Towards Explainable AI Writing Assistants for Non-native English Speakers

arXiv 2304.02625 ↗First posted 5 Apr 2023cs.CLcited by 0

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Abstract (arXiv)

We highlight the challenges faced by non-native speakers when using AI writing assistants to paraphrase text. Through an interview study with 15 non-native English speakers (NNESs) with varying levels of English proficiency, we observe that they face difficulties in assessing paraphrased texts generated by AI writing assistants, largely due to the lack of explanations accompanying the suggested paraphrases. Furthermore, we examine their strategies to assess AI-generated texts in the absence of such explanations. Drawing on the needs of NNESs identified in our interview, we propose four potential user interfaces to enhance the writing experience of NNESs using AI writing assistants. The proposed designs focus on incorporating explanations to better support NNESs in understanding and evaluating the AI-generated paraphrasing suggestions.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 12 of its 41 references that are in the map. First posted on arXiv 5 Apr 2023.

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References · 12

  1. 2016"Why Should I Trust You?": Explaining the Predictions of Any Classifiercited by 5,070
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  5. 2018On Human Predictions with Explanations and Predictions of Machine Learning Models: A Case Study on Deception Detectioncited by 159
  6. 2023Co-Writing with Opinionated Language Models Affects Users' Viewscited by 148
  7. 2022Explanations Can Reduce Overreliance on AI Systems During Decision-Makingcited by 111
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  9. 2021The Impact of Multiple Parallel Phrase Suggestions on Email Input and Composition Behaviour of Native and Non-Native English Writerscited by 61
  10. 2017A causal framework for explaining the predictions of black-box sequence-to-sequence modelscited by 58
  11. 2019exBERT: A Visual Analysis Tool to Explore Learned Representations in Transformers Modelscited by 33
  12. 2022Interpretability for Language Learners Using Example-Based Grammatical Error Correctioncited by 13

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