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| 題 名 | AI介入長照下居服員的專業意義與留任動力:以情境倫理觀點探討公共服務人才=Professional Meaning and Retention Motivation of Home Care Worker under AI-Mediated Long-Term Care: A Situational Ethics Perspective on Public Service Talent Strategies |
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| 作 者 | 鄧光宇; | 書刊名 | 科際整合月刊 |
| 卷 期 | 11:2 2026.02[民115.02] |
| 頁 次 | 頁44-68 |
| 分類號 | 312.83 |
| 關鍵詞 | 情境倫理; 長照政策; 居服員; 留任動力; AI發展; Situational ethics; Long-term care policy; Home care workers; Retention motivation; AI development; |
| 語 文 | 中文(Chinese) |
| 中文摘要 | 臺灣於2025年正式進入超高齡社會,在長期人力不足的長照體系中,居服員仍是照顧服務運作的核心。隨著GPS離案定位、App勾選服務項目、影像與紀錄上傳、工時自動計算,以及智慧穿戴與AIoT量測工具逐步導入長照體系,AI已實質介入居服員的工作流程,並重塑照護判斷與倫理責任的承擔方式。然而,AI介入如何影響前線工作者的專業判斷、倫理負荷與角色認同,仍有待進一步釐清。本文旨在從「情境倫理」與「公共服務人才」的視角,探討AI介入長照服務後,居服員如何重新理解其專業意義、倫理負荷與留任動力,以補足長照科技化研究中對人員倫理能動性關注不足的研究空白。本研究採用質性研究方法,透過深度訪談五位長照管理者與五位居服員,蒐集其對AI工具使用、判斷依據與責任歸屬的實務經驗與觀點,藉以呈現管理層與前線人員在科技介入下的認知差異。研究資料以主題分析法進行整理與分析,並透過交叉檢核提升研究結果的可信度。研究結果顯示五項關鍵現象:第一,AI難以掌握照護情境中的脈絡與非語言訊息,導致系統建議與現場判斷產生落差。第二,流程標準化雖提升服務一致性,卻壓縮前線裁量空間,使居服員的隱性知識更難被承認。第三,居服員在系統提示與臨場判斷間承擔更高的倫理負荷。第四,管理層與前線人員在數據信任與情境依賴上的差異,形成跨層級的人機信任落差。第五,AI同時具備監控與專業認可效果,使居服員的角色認同與留任動機出現重新調整。本文指出,AI發展不僅是技術導入問題,更涉及專業判斷與倫理能動性的重構;本研究補充科技倫理研究中對照護勞動與情境判斷之經驗性不足,並深化AI治理中倫理能動性的實證理解,對長照政策與組織治理具有重要啟示。 |
| 英文摘要 | Taiwan officially entered a super-aged society in 2025. Within a long-term care system facing chronic labor shortages, home care workers remain the core workforce sustaining service delivery. With the gradual introduction of GPS-based off-duty location tracking, mobile application-based service selection, digital record uploads, automated work-hour calculations, and smart wearables and AIoT tools, artificial intelligence (AI) has become embedded in home care work processes, reshaping care-related judgment and ethical responsibility. However, the implications of AI for frontline workers' professional judgment, ethical burden, and role identity remain underexplored. Drawing on the perspectives of situational ethics and public service personnel, this study examines how home care workers reinterpret their professional meaning, ethical burden, and retention motivation following AI integration into long-term care services. This qualitative study conducted in-depth interviews with five long-term care managers and five home care workers. Data were analyzed using thematic analysis with cross-checking to enhance credibility. The findings reveal five key phenomena: (1) AI struggles to capture care contexts and non-verbal cues, creating gaps between system recommendations and on-site judgment; (2) process standardization improves consistency but constrains frontline discretion and obscures tacit knowledge; (3) home care workers bear increased ethical burdens when navigating between system prompts and situational judgment; (4) differences in data trust and contextual reliance between management and frontline staff generate cross-level human-machine trust gaps; and (5) AI simultaneously operates as surveillance and professional recognition, reshaping role identity and retention motivation. This study shows that AI development is not merely technical but involves the reconfiguration of professional judgment and ethical agency, with implications for long-term care policy and organizational governance. |
本系統中英文摘要資訊取自各篇刊載內容。