Pith. sign in

REVIEW 3 cited by

AI Suggestions Homogenize Writing Toward Western Styles and Diminish Cultural Nuances

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2409.11360 v3 pith:TNMZW35Q submitted 2024-09-17 cs.HC cs.AI

classification cs.HCcs.AI
keywords writingsuggestionswesternculturalmodelsapplicationshomogenizenuances
verification ladder T0 review T1 audit T2 compute T3 formal
0 comments
read the original abstract

Large language models (LLMs) are being increasingly integrated into everyday products and services, such as coding tools and writing assistants. As these embedded AI applications are deployed globally, there is a growing concern that the AI models underlying these applications prioritize Western values. This paper investigates what happens when a Western-centric AI model provides writing suggestions to users from a different cultural background. We conducted a cross-cultural controlled experiment with 118 participants from India and the United States who completed culturally grounded writing tasks with and without AI suggestions. Our analysis reveals that AI provided greater efficiency gains for Americans compared to Indians. Moreover, AI suggestions led Indian participants to adopt Western writing styles, altering not just what is written but also how it is written. These findings show that Western-centric AI models homogenize writing toward Western norms, diminishing nuances that differentiate cultural expression.

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 3 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Prototypical Human-AI Collaboration Behaviors from LLM-Assisted Writing in the Wild

    cs.CL 2025-05 conditional novelty 6.0 of 10

    Seven prototypical collaboration behaviors, such as asking for more outputs, asking questions, and adding content, explain most variation in how users follow up with writing assistants in the wild.

  2. Meta-Cultural Competence: Climbing the Right Hill of Cultural Awareness

    cs.CY 2025-02 conditional novelty 6.0 of 10

    The paper argues that LLMs should be evaluated and built for meta-cultural competence rather than static knowledge of specific cultures, and gives a first, illustrative measurement of one component.

  3. The Impact of Artificial Intelligence on Human Thought

    cs.CY 2025-08 unverdicted novelty 1.0 of 10

    A review-style preprint argues that AI use may weaken independent thought through cognitive offloading and filter bubbles, but it presents no new evidence.

Pith tools