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| Title: | 談話型AI如何扭曲與塑形全新的使用者體驗？
How do biases in conversational artificial intelligence distort and shape a new user experience? |
| Authors: | 舒天宓
Saquet, Thémis |
| Contributors: | 莊皓鈞
Chuang, Howard
舒天宓
Thémis Saquet |
| Keywords: | 偏見
對話式人工智能
對話式營銷
用戶體驗
Bias
Conversational Artificial Intelligence
Conversational Marketing
User Experience |
| Date: | 2023 |
| Issue Date: | 2023-07-06 16:34:53 (UTC+8) |
| Abstract: | In our post-COVID-19 societies, more and more consumers rely on conversational AI such as voice assistants or chatbots to perform any kind of task, from asking for the weather to having personal conversations. Companies have seized on this demand to continue developing their conversational AI to create an ever-better user experience. However, the racial or sexist biases implemented in these AIs distort the original user experience, sometimes creating a new one depending on when the bias is implemented. We will try to analyze the effect of these different biases on the user experience and know how they can distort the user experience, especially depending on the moment when these biases appear. To do so, we will analyze the biases in the case of voice assistants and interactive social chatbots through a case study between XiaoIce and MicrosoftTay. We will analyze the appearance of these biases and their effects using the three-stage framework for artificial intelligence in marketing. The main conclusions are that racial biases, mainly embedded because of insufficiently diverse data and engineers, and gender biases, tend to reinforce the structural inequalities that affect our societies. By reinforcing these inequalities, the user experience is negatively impacted in terms of accessibility, representation, and experience conveyed by the use of the product. |
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| Description: | 碩士
國立政治大學
國際經營管理英語碩士學位學程(IMBA)
111933056 |
| Source URI: | http://thesis.lib.nccu.edu.tw/record/#G0111933056 |
| Data Type: | thesis |
| Appears in Collections: | [國際經營管理英語碩士學程IMBA] 學位論文
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