人とチャットボットの交流におけるコミュニケーションエラー:チャットGPTアラビア語メンタルヘルスサポートの調査事例
Ghuzayyil Mohammed Al-Otaibi1, Hind M Alotaibi1, Sami Sulaiman Alsalmi1
1Department of English, College of Language Sciences, King Saud University, P.O. Box 2460, Riyadh 11451, Saudi Arabia.
Behavioral sciences (Basel, Switzerland)
|August 28, 2025
まとめ
この研究では,ChatGPT-3.5とのアラビア語でのコミュニケーションエラーを分析し,主に文法的なエラーと繰り返しを発見しました. これらの洞察は メンタルヘルス支援のような 敏感な分野における会話AIの課題を 強調しています
科学分野:
- 自然言語処理
- 人工知能の倫理
- 人とコンピュータの相互作用
背景:
- 大型言語モデル (LLM) はますます普及しているが,その有効な利用にはさらなる探求が必要である.
- コミュニケーションのニュアンスを理解することは メンタルヘルスのような 繊細な領域に AIを導入するのに不可欠です
研究 の 目的:
- 人とチャットGPT-3.5の対話におけるコミュニケーションの誤りを特定し,分類する.
- 文法的な誤り,反復,矛盾,曖昧さ,社交性の欠如を含む誤りの種類を分析する.
- メンタルヘルス支援の文脈における現在の会話AIの限界を洞察する.
主な方法:
- オンラインのフォーラムから アラビア語の6つのメンタルヘルスの相談を集めました
- ChatGPT-3.5に投稿されたユーザーからの問い合わせ
- 通信エラーに対する ChatGPT-3.5 の応答を分析した.
主要な成果:
- チャットGPT-3.5のアラビア語の応答で 102の異なる通信エラーを特定しました.
- 大半の誤りは文法的なもので,繰り返しあった.
- 矛盾,曖昧な言葉,無視された質問,社交性の欠如など
結論:
- ChatGPT-3.5のような現在の会話AIシステムでは アラビア語のコミュニケーションエラーが顕著です
- こうしたエラーは 特にメンタルヘルスのような 繊細な領域では AIが正確かつ共感的に情報を伝える能力に 限界があることを示しています
- 専門的なアプリケーションのためのLLMコミュニケーションを改善するためにさらなる研究が必要です.
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