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題名 模擬ChatGPT導入政府資料開放平臺的使用體驗
Simulating the User Experience of Integrating ChatGPT into Government Open Data Platforms作者 謝佾伶
Hsieh, Yi-Ling貢獻者 蕭乃沂
Hsiao, Nai-Yi
謝佾伶
Hsieh, Yi-Ling關鍵詞 ChatGPT
政府資料開放
使用體驗
有用性
易用性
ChatGPT
Government Open Data
User Experience
Usefulness
Usability日期 2024 上傳時間 5-八月-2024 14:23:28 (UTC+8) 摘要 ChatGPT的問世改變了人類於日常生活中的瑣事，如文字撰寫、程式編輯、翻譯等等，ChatGPT都能夠處理，許多的政府也在思考如何將ChatGPT應用於政府業務之中，但礙於數據隱私的原因，ChatGPT導入的審查就越困難。因此本文將ChatGPT應用的想法用於政府資料開放平臺之中，透過其開放資料的性質，預先探討使用者對於ChatGP導入政府資料開放平臺做為輔助服務的使用體驗。 本研究透過線上面訪並以Figma軟體模擬ChatGPT導入政府資料開放平臺的模擬介面，藉由模擬介面去了解平臺使用者的需求與期待，更近一步的去了解導入ChatGPT的政府資料開放平臺，對於吸引非資料分析專業族群前來使用與降低使用政府開放資料的門檻的影響。 研究結果發現，導入ChatGPT後的政府資料開放平臺確實能夠帶來便利，降低使用門檻，但原先非政府資料開放平臺的使用者針對ChatGPT的導入與否，其關連性並不大，也就是說有了ChatGPT並不會吸引他們來使用政府資料開放平臺，主要原因是缺少了使用這些資料的動機。 其次是導入ChatGPT對於政府資料開放平臺服務體驗的影響，使用者對於ChatGPT的導入大部分都是正面態度，但使用者非常在意ChatGPT導入政府資料開放平臺的控管機制及問責制度，希望可以讓政府資料開放平臺在使用生成式人工智慧過程中大幅度的降低負面影響。 最後，本研究依研究結果對未來政府資料開放平臺導入ChatGPT提出四點實務建議，第一點建議政府資料開放平臺能夠與先前已導入ChatGPT的部門單位聯繫，向其借鏡當初的開發經驗，後續也能將這些機關納入政府資料開放平臺的評選委員，將導入經驗傳承至平臺中。第二點則是在未來如政府資料開放平臺確定要導入ChatGPT做為介面的話，或許可以考量於開發階段時，先進行為期半年至一年的內部測試，邀請數據分析專家、統計專家及相關領域的專業人士進行試用，以利於降低風險，並提高系統的可靠度。第三點則是在查詢機器人的頁面中，加上引導提示按鈕，像是資料年份、年齡層等等，這樣有助於使用者找到更精準的資料，也能避免使用者輸入內容太過廣泛，而使資料搜尋結果不佳的情形出現。第四點則是提供多元的機器人服務，讓機器人不僅僅只是查找資料，而是能夠連結不同資料集、不同政府單位的資料內容後進行分析，並依照使用者需求進行圖表繪製，判別趨勢變化，最終給予政策建議，將該功能發展成強大且具有吸引力的工具，也許就能帶給使用者幫助，藉此擴展使用族群。
The advent of ChatGPT has transformed various human daily tasks such as writing, code editing, translation, and more. Many governments are considering integrating ChatGPT into their operations, but due to concerns about data privacy, the review process for its implementation is rather challenging. This paper explores the idea of applying ChatGPT to government open data platforms. By leveraging the open nature of these platforms, we aim to investigate user experiences with ChatGPT as an auxiliary service. This study uses online interviews and the Figma software to simulate the interface of integrating ChatGPT into a government open data platform. Through the simulated interface, we aim to understand the needs and expectations of platform users and further explore the impact of integrating ChatGPT on attracting non-data-analysis professionals and lowering the barrier to using government open data. The research results indicate that integrating ChatGPT into government open data platforms can indeed provide convenience and lower the usage threshold. However, for users who did not previously use these platforms, the existence of ChatGPT has little correlation with their decision. In other words, ChatGPT does not necessarily attract new users for government open data platforms due to a lack of motivation to use these data. Additionally, regarding the impact of ChatGPT integration on the user experience of government open data platforms, most users respond positively to this integration. However, they are quite concerned about the control procedure and accountability system of integrating ChatGPT into government open data platforms. They hope that the platforms can significantly reduce the potential negative impacts while implementing generative AI. Finally, based on the research results, this study proposes four practical suggestions for the future integration of ChatGPT into government open data platforms. First, we recommend government open data platforms to connect with departments that have previously integrated ChatGPT to learn from their development experiences. Subsequently, these agencies can be included as members of the evaluation committee for government open data platforms, passing on their integration experiences. Secondly, if the government open data platforms decide to use ChatGPT as an interface in the future, they could consider conducting an internal test for six months to a year during the development phase. Data analysis experts, statisticians, and professionals from related fields can be invited to test the system to reduce the risks and improve system reliability. 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國立政治大學
公共行政學系
109256035資料來源 http://thesis.lib.nccu.edu.tw/record/#G0109256035 資料類型 thesis dc.contributor.advisor 蕭乃沂 zh_TW dc.contributor.advisor Hsiao, Nai-Yi en_US dc.contributor.author (作者) 謝佾伶 zh_TW dc.contributor.author (作者) Hsieh, Yi-Ling en_US dc.creator (作者) 謝佾伶 zh_TW dc.creator (作者) Hsieh, Yi-Ling en_US dc.date (日期) 2024 en_US dc.date.accessioned 5-八月-2024 14:23:28 (UTC+8) - dc.date.available 5-八月-2024 14:23:28 (UTC+8) - dc.date.issued (上傳時間) 5-八月-2024 14:23:28 (UTC+8) - dc.identifier (其他 識別碼) G0109256035 en_US dc.identifier.uri (URI) https://nccur.lib.nccu.edu.tw/handle/140.119/152850 - dc.description (描述) 碩士 zh_TW dc.description (描述) 國立政治大學 zh_TW dc.description (描述) 公共行政學系 zh_TW dc.description (描述) 109256035 zh_TW dc.description.abstract (摘要) ChatGPT的問世改變了人類於日常生活中的瑣事，如文字撰寫、程式編輯、翻譯等等，ChatGPT都能夠處理，許多的政府也在思考如何將ChatGPT應用於政府業務之中，但礙於數據隱私的原因，ChatGPT導入的審查就越困難。因此本文將ChatGPT應用的想法用於政府資料開放平臺之中，透過其開放資料的性質，預先探討使用者對於ChatGP導入政府資料開放平臺做為輔助服務的使用體驗。 本研究透過線上面訪並以Figma軟體模擬ChatGPT導入政府資料開放平臺的模擬介面，藉由模擬介面去了解平臺使用者的需求與期待，更近一步的去了解導入ChatGPT的政府資料開放平臺，對於吸引非資料分析專業族群前來使用與降低使用政府開放資料的門檻的影響。 研究結果發現，導入ChatGPT後的政府資料開放平臺確實能夠帶來便利，降低使用門檻，但原先非政府資料開放平臺的使用者針對ChatGPT的導入與否，其關連性並不大，也就是說有了ChatGPT並不會吸引他們來使用政府資料開放平臺，主要原因是缺少了使用這些資料的動機。 其次是導入ChatGPT對於政府資料開放平臺服務體驗的影響，使用者對於ChatGPT的導入大部分都是正面態度，但使用者非常在意ChatGPT導入政府資料開放平臺的控管機制及問責制度，希望可以讓政府資料開放平臺在使用生成式人工智慧過程中大幅度的降低負面影響。 最後，本研究依研究結果對未來政府資料開放平臺導入ChatGPT提出四點實務建議，第一點建議政府資料開放平臺能夠與先前已導入ChatGPT的部門單位聯繫，向其借鏡當初的開發經驗，後續也能將這些機關納入政府資料開放平臺的評選委員，將導入經驗傳承至平臺中。第二點則是在未來如政府資料開放平臺確定要導入ChatGPT做為介面的話，或許可以考量於開發階段時，先進行為期半年至一年的內部測試，邀請數據分析專家、統計專家及相關領域的專業人士進行試用，以利於降低風險，並提高系統的可靠度。第三點則是在查詢機器人的頁面中，加上引導提示按鈕，像是資料年份、年齡層等等，這樣有助於使用者找到更精準的資料，也能避免使用者輸入內容太過廣泛，而使資料搜尋結果不佳的情形出現。第四點則是提供多元的機器人服務，讓機器人不僅僅只是查找資料，而是能夠連結不同資料集、不同政府單位的資料內容後進行分析，並依照使用者需求進行圖表繪製，判別趨勢變化，最終給予政策建議，將該功能發展成強大且具有吸引力的工具，也許就能帶給使用者幫助，藉此擴展使用族群。 zh_TW dc.description.abstract (摘要) The advent of ChatGPT has transformed various human daily tasks such as writing, code editing, translation, and more. Many governments are considering integrating ChatGPT into their operations, but due to concerns about data privacy, the review process for its implementation is rather challenging. This paper explores the idea of applying ChatGPT to government open data platforms. By leveraging the open nature of these platforms, we aim to investigate user experiences with ChatGPT as an auxiliary service. This study uses online interviews and the Figma software to simulate the interface of integrating ChatGPT into a government open data platform. Through the simulated interface, we aim to understand the needs and expectations of platform users and further explore the impact of integrating ChatGPT on attracting non-data-analysis professionals and lowering the barrier to using government open data. The research results indicate that integrating ChatGPT into government open data platforms can indeed provide convenience and lower the usage threshold. However, for users who did not previously use these platforms, the existence of ChatGPT has little correlation with their decision. In other words, ChatGPT does not necessarily attract new users for government open data platforms due to a lack of motivation to use these data. Additionally, regarding the impact of ChatGPT integration on the user experience of government open data platforms, most users respond positively to this integration. However, they are quite concerned about the control procedure and accountability system of integrating ChatGPT into government open data platforms. They hope that the platforms can significantly reduce the potential negative impacts while implementing generative AI. Finally, based on the research results, this study proposes four practical suggestions for the future integration of ChatGPT into government open data platforms. First, we recommend government open data platforms to connect with departments that have previously integrated ChatGPT to learn from their development experiences. Subsequently, these agencies can be included as members of the evaluation committee for government open data platforms, passing on their integration experiences. Secondly, if the government open data platforms decide to use ChatGPT as an interface in the future, they could consider conducting an internal test for six months to a year during the development phase. Data analysis experts, statisticians, and professionals from related fields can be invited to test the system to reduce the risks and improve system reliability. Third, adding guided prompt buttons on the query robot's page, such as data year and age group, can help users find more precise data and avoid overly broad inputs that could lead to poor search results. Fourth, providing diverse robot services can enhance functionality. This means that the robot should not only search for data but also link and analyze content from different datasets and government units. Based on user needs, it can generate charts, identify trend changes, and ultimately offer policy recommendations. Developing this feature into a powerful and attractive tool can assist users and expand the user base. en_US dc.description.tableofcontents 第一章 緒論 1 第一節 研究背景 1 第二節 研究動機 2 第三節 研究目的與問題 6 第四節 研究流程圖 7 第二章 文獻探討 9 第一節 人工智慧與ChatGPT 9 第二節 ChatGPT的應用與導入 13 第三節 政府開放資料與導入 22 第四節 政府資料開放平臺如何善用ChatGPT 28 第五節 小結 31 第三章 研究設計 32 第一節 研究問題 32 第二節 研究方法 33 第三節 研究對象與來源 34 第四節 面訪內容與步驟 38 第五節 研究限制 44 第四章 研究結果與分析 46 第一節 受訪者樣態與介面體驗分析 46 第二節 政府資料開放平臺使用動機及情形 52 第三節 ChatGPT與政府資料開放平臺 56 第四節 綜合分析與討論 64 第五章 研究結論 73 第一節 研究發現 73 第二節 實務建議 75 第三節 研究限制與後續研究建議 76 參考文獻 78 zh_TW dc.format.extent 4864337 bytes - dc.format.mimetype application/pdf - dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0109256035 en_US dc.subject (關鍵詞) ChatGPT zh_TW dc.subject (關鍵詞) 政府資料開放 zh_TW dc.subject (關鍵詞) 使用體驗 zh_TW dc.subject (關鍵詞) 有用性 zh_TW dc.subject (關鍵詞) 易用性 zh_TW dc.subject (關鍵詞) ChatGPT en_US dc.subject (關鍵詞) Government Open Data en_US dc.subject (關鍵詞) User Experience en_US dc.subject (關鍵詞) Usefulness en_US dc.subject (關鍵詞) Usability en_US dc.title (題名) 模擬ChatGPT導入政府資料開放平臺的使用體驗 zh_TW dc.title (題名) Simulating the User Experience of Integrating ChatGPT into Government Open Data Platforms en_US dc.type (資料類型) thesis en_US dc.relation.reference (參考文獻) Alexopoulos, C., Saxena, S., Janssen, M., & Rizun, N.(2023). 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