隨著生成式人工智慧逐漸進入文化教育服務情境，高齡志工如何理解並運用此類工具，以及其使用經驗對服務準備、角色分工、參與動機與持續投入意願所呈現的變化，值得進一步探究。本研究以功能性取徑志願服務理論為分析基礎，探討高齡志工將生成式人工智慧運用於志願服務準備之經驗與評價、對人機角色關係及分工之理解，以及價值、理解、社會、職涯、保護與增強六項動機功能之知覺變化及其與持續投入意願的關聯。
本研究採任務導向質性設計，以高雄市文化教育機構10位年滿60歲且具有一年以上正式志願服務經驗之高齡志工為研究對象。受訪者先以Google Gemini完成服務主題提問、依服務對象調整內容及檢視生成資訊等操作任務，再接受半結構式深度訪談，所得資料採主題分析法進行整理與分析。
研究結果顯示，生成式人工智慧可協助高齡志工即時取得資料、統整重點及調整解說內容，有助於縮短服務準備時間；惟生成內容仍可能出現資訊錯誤、來源不明、表達制式化，以及在地語言與文化脈絡不足等問題，仍須由志工進行查證、判讀與轉譯。受訪者多將生成式人工智慧定位為資料蒐集與內容整理的輔助工具，志工則負責內容取捨、依服務對象調整說明方式及現場互動，其服務角色因而更著重於內容判讀與情境轉譯。就動機功能而言，價值與保護功能多延續既有服務經驗，理解與職涯功能較明顯受到支持，社會與增強功能則因使用方式及機構安排而呈現差異。當生成式人工智慧有助於學習、資料取得及減輕準備負荷時，較有助於維持志工的持續投入意願；若數位工具被用於縮減真人服務，志工的被需要感可能下降，其持續投入意願亦可能受到不利影響。據此，文化教育機構運用生成式人工智慧時，宜以人機互補為原則，兼顧服務效率、志工增能，以及其服務角色與被需要感。

As generative artificial intelligence (GenAI) is increasingly introduced into cultural and educational service settings, further research is needed to understand how older adult volunteers perceive and use such tools, as well as how their experiences may relate to changes in service preparation, role division, volunteer motivation, and intentions to continue volunteering. Drawing on the Functional Approach to Volunteerism, this study examines older adult volunteers’ experiences and evaluations of using GenAI in preparation for volunteer service, their understanding of the roles and division of labor between volunteers and AI, and perceived changes in the six motivational functions of values, understanding, social, career, protective, and enhancement, together with their relationships to intentions to continue volunteering.
This study employed a task-oriented qualitative design and recruited ten volunteers aged 60 or older from cultural and educational institutions in Kaohsiung City. All participants had at least one year of formal volunteering experience. Participants first used Google Gemini to complete a series of tasks, including asking questions related to their service topics, adapting content for different target audiences, and reviewing generated information. They subsequently participated in semi-structured in-depth interviews. The collected data were organized and analyzed using thematic analysis.
The findings indicate that GenAI can assist older adult volunteers in obtaining information promptly, identifying and organizing key points, and adapting interpretive content, thereby reducing the time required for service preparation. Nevertheless, AI-generated content may contain inaccurate information, unclear sources, formulaic expressions, and insufficient sensitivity to local languages and cultural contexts. Verification, interpretation, and contextual translation by volunteers therefore remain necessary. Most participants regarded GenAI as an auxiliary tool for information gathering and content organization, whereas volunteers remained responsible for selecting content, adapting explanations to different audiences, and managing on-site interactions. Their service roles consequently placed greater emphasis on content interpretation and contextual translation. With regard to motivational functions, the values and protective functions remained largely consistent with participants’ existing volunteering experiences, whereas the understanding and career functions received more evident support from GenAI use. Changes in the social and enhancement functions varied according to patterns of use and institutional arrangements. When GenAI supported learning, facilitated access to information, and reduced the burden of preparation, it was more likely to sustain volunteers’ intentions to continue volunteering. Conversely, if digital tools were used to reduce the provision of in-person services, volunteers' sense of being needed might decline, and their intentions to continue volunteering could also be adversely affected. Based on these findings, cultural and educational institutions should adopt a principle of human–AI complementarity when applying GenAI, while balancing service efficiency, volunteer capacity building, volunteers’ service roles, and their sense of being needed.

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