此門課同時是臺灣大專院校人工智慧學程聯盟（Taiwan Artificial Intelligence College Alliance，簡稱TAICA）的主導課程，有關TAICA相關資訊請參考其網站 https://taicatw.net/。本課程旨在鼓勵學生批判性的思考AI對個人、社會與制度的影響，引導學生了解AI倫理的多元面向。課程架構分為三部分：基礎篇 (W1-W5)，建立AI倫理基本概念，包含簡介機器學習與大型語言模型的基本原理，並教導實踐倫理常用來分析相關議題或案例的批判思維工具。核心主題篇 (W6-W10)，探討AI系統的責任歸屬、演算法偏誤問題與公平性、ML與LLM的資訊安全倫理，揭示技術設計中隱含的風險與價值判斷。特定議題篇 (W11-W13)，檢視陪伴式AI應用程式、物理AI、AI助攻或威脅民主、AGI與人類生存風險等。

This course is also a leading course of the Taiwan Artificial Intelligence College Alliance (TAICA). For relevant information about TAICA, please refer to its website https://taicatw.net/. This course aims to encourage students to think critically about the impact of AI on individuals, society and institutions, and to guide students to understand the diverse aspects of AI ethics. The course structure is divided into three parts: Basics (W1-W5), which establishes the basic concepts of AI ethics, including an introduction to the basic principles of machine learning and large-scale language models, and teaches critical thinking tools commonly used in practical ethics to analyze related issues or cases. Core topics (W6-W10) explore the responsibility of AI systems, algorithm bias issues and fairness, the information security ethics of ML and LLM, and reveal the risks and value judgments implicit in technical design. Specific topics (W11-W13) examine companion AI applications, physical AI, AI assists or threatens democracy, AGI and human survival risks, etc.

1.Boddington, P. (2023). AI ethics. Singapur: Springer International Publishing. [AIE]
2.Borg, J. S., Sinnott-Armstrong, W., & Conitzer, V. (2024). Moral AI: And How We Get There. Random House. [MAI]

1.Boddington, P. (2023). AI ethics. Singapur: Springer International Publishing. [AIE]
2. Borg, J. S., Sinnott-Armstrong, W., & Conitzer, V. (2024). Moral AI: And How We Get There. Random House. [MAI]