Course Syllabus

Course Information：

Year-Semester Course Number Course Name Phase Credits Hours Required/Elective Instructor Class Student NO. Withdraw Note

Spring Semester
Year 2023 317130 Artificial Intelligence, Business and Society 1 3.0 3 ★ Wei-Lun Chang GBM
IMBA
IMFI
CMGT 51 1 經管所、管理博和IMBA&IMFI合開

Year-Semester	Course Number	Course Name	Phase	Credits	Hours	Required/Elective	Instructor	Class	Student NO.	Withdraw	Note
Spring Semester Year 2023	317130	Artificial Intelligence, Business and Society	1	3.0	3	★	Wei-Lun Chang	GBM IMBA IMFI CMGT	51	1	經管所、管理博和IMBA&IMFI合開

Course Plan：

Instructor Wei-Lun Chang　Office Hours

Email wlchang@ntut.edu.tw

Last Updated 2022-12-19 19:12:48

Course Objective This course provides an overview of AI and its role in business transformation. The purpose is to improve understanding of AI and being used in the industries. The brief technical overview of AI will be covered such as big data, data mining, machine learning, etc. The objectives are to learn how digital technologies will be applied to various business settings and how to adapt business strategy and operation in the era of digital transformation. Finally, learning how to utilize AI as the source of competitive advantage.

Course Schedule W1: Orientation W2: AI for Business Course Intro (Is AI a General Purpose Technology?) W3: Intro to Big Data and AI W4: Understanding the use of AI in business (chap 2&3 of T2) W5: AI (Machine Learning) (chap 4&5 of T1) W6: Business Applications of Machine Learning (chap 3 of T1) W7: OFF W8: Psychology of algorithm (chap 6&7 of T1) W9: AI-driven strategy (chap 4 of T2) W10: Midterm week W11: Building and Investing in AI-Based Businesses (R4) W12: Introduction to Business Analytics (R5, R6, R7) W13: AI tasks, organizational structures, and business processes (chap 5 of T2) W14: Jobs and skills in a world of smart machines (chap 6 of T2) W15: Risks with AI (chap 10 of T1) W16: Organizational, social, and ethical implications (chap 8 of T2) W17: Final Presentation

Evaluation and grading policy Final project presentation: 60% Attendance: 10% Assignments: 30%

Materials All right reserved. Do not reproduce without permission.

Foreign-language textbooks:Yes
Textbook: T1. A Human’s Guide to Machine Intelligence by Kartik Hosanagar T2: The AI Advantage: How to Put the Artificial Intelligence Revolution to Work (Management on the Cutting Edge) Other supplements: R1.Brynjolfsson E, McAfee A. 2017. The Business of Artificial Intelligence. Harvard Business Review. Available at: https://hbr.org/cover-story/2017/07/the-business-of-artificialintelligence. R2.Fountaine, T., McCarthy, B., & Saleh, T. (2019). Building the AI-Powered Organization. Harvard Business Review, 97(August), 1–13. • Hagiu, A., & R3.Wright, J. (2020). When Data Creates Competitive Advantage. Harvard Business Review, 98(January–February), 94–102. R4.Venkat Srinivasan, “Context, Language, and Reasoning in AI: Three Key Challenges,” MIT Technology Review, October 4, 2016 (https://www.technologyreview.com/2016/10/14/156968/context-language-and-reasoning-in-ai-three-key-challenges/) R5.Davenport article - “Competing on Analytics” (Harvard Business Review) R6.LaValle et al. article - “Analytics: The New Path to Value” (MIT Sloan Management Review) R7.Davenport and Harris article - “The Dark Side of Customer Analytics” (Harvard Business Review) R8. Loveman article – “Diamonds in the Data Mine” (Harvard Business Review)

The access to curricular consultation Please contact via email: wlchang@ntut.edu.tw

The course corresponds to the SDGs

Note
Google Meet + Google Classroom

Instructor	Wei-Lun Chang　Office Hours
Email	wlchang@ntut.edu.tw
Last Updated	2022-12-19 19:12:48
Course Objective	This course provides an overview of AI and its role in business transformation. The purpose is to improve understanding of AI and being used in the industries. The brief technical overview of AI will be covered such as big data, data mining, machine learning, etc. The objectives are to learn how digital technologies will be applied to various business settings and how to adapt business strategy and operation in the era of digital transformation. Finally, learning how to utilize AI as the source of competitive advantage.
Course Schedule	W1: Orientation W2: AI for Business Course Intro (Is AI a General Purpose Technology?) W3: Intro to Big Data and AI W4: Understanding the use of AI in business (chap 2&3 of T2) W5: AI (Machine Learning) (chap 4&5 of T1) W6: Business Applications of Machine Learning (chap 3 of T1) W7: OFF W8: Psychology of algorithm (chap 6&7 of T1) W9: AI-driven strategy (chap 4 of T2) W10: Midterm week W11: Building and Investing in AI-Based Businesses (R4) W12: Introduction to Business Analytics (R5, R6, R7) W13: AI tasks, organizational structures, and business processes (chap 5 of T2) W14: Jobs and skills in a world of smart machines (chap 6 of T2) W15: Risks with AI (chap 10 of T1) W16: Organizational, social, and ethical implications (chap 8 of T2) W17: Final Presentation
Evaluation and grading policy	Final project presentation: 60% Attendance: 10% Assignments: 30%
Materials	All right reserved. Do not reproduce without permission. Foreign-language textbooks:Yes Textbook: T1. A Human’s Guide to Machine Intelligence by Kartik Hosanagar T2: The AI Advantage: How to Put the Artificial Intelligence Revolution to Work (Management on the Cutting Edge) Other supplements: R1.Brynjolfsson E, McAfee A. 2017. The Business of Artificial Intelligence. Harvard Business Review. Available at: https://hbr.org/cover-story/2017/07/the-business-of-artificialintelligence. R2.Fountaine, T., McCarthy, B., & Saleh, T. (2019). Building the AI-Powered Organization. Harvard Business Review, 97(August), 1–13. • Hagiu, A., & R3.Wright, J. (2020). When Data Creates Competitive Advantage. Harvard Business Review, 98(January–February), 94–102. R4.Venkat Srinivasan, “Context, Language, and Reasoning in AI: Three Key Challenges,” MIT Technology Review, October 4, 2016 (https://www.technologyreview.com/2016/10/14/156968/context-language-and-reasoning-in-ai-three-key-challenges/) R5.Davenport article - “Competing on Analytics” (Harvard Business Review) R6.LaValle et al. article - “Analytics: The New Path to Value” (MIT Sloan Management Review) R7.Davenport and Harris article - “The Dark Side of Customer Analytics” (Harvard Business Review) R8. Loveman article – “Diamonds in the Data Mine” (Harvard Business Review)
The access to curricular consultation	Please contact via email: wlchang@ntut.edu.tw
The course corresponds to the SDGs
Note	Google Meet + Google Classroom