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東工大の科学技術倫理 / Tokyo Tech Science, Engineering, AI & Data Ethics 2020

Tokyo Tech
Enrollment is Closed

About this course (April 20, 2020) see below for course syllabus in Japanese (コースシラバスは以下です)

Course title: “東工大の科学技術(人工知能データ)倫理・ Tokyo Tech Science, Engineering and AI Data Ethics 2020”
Learn both traditional and aspirational ethics to utilize your science and engineering expertise to improve human well-being. This course is a modified version of the edX MOOC on Science and Engineering Ethics, which was released in 2017 in Japanese. This online course in English and Japanese contains new quizzes and materials on Artificial Intelligence (AI) and Data Ethics, including case studies on ethical issues in developing self-driving cars, AI related health care decision making, and water pollution, etc. To the original course a new section was added on Artificial Intelligence and Data Ethics. In addition, Tokyo Tech students are provided an opportunity to participate in a pioneering online learning research study on metacognition (thinking about thinking related to how to learn effectively) and the development of an AI based personalized online learning agent. The first fifty (50) students who complete all the learning research activities called POALS by December 31, 2020 January 26, 2021 will each receive an Amazon gift card worth JPY 3000 (see below and in the first unit for details).

Course Topics:
Unit 1: Why is Engineering Ethics a Current Focus of Attention?
Unit 2: Engineer Ethical Thinking
Unit 3: Seven-step Guide to Ethical Decision Making
Unit 4: How Should Scientists and Engineers Make Ethical Decisions?
Unit 5: Researcher Ethics
Unit 6: Engineering Ethics 2.0
Unit 7: Artificial Intelligence (AI) and Data Ethics

Science and Engineering Ethics learning objectives:
1. To recognize the significant social and environmental impact of engineering/scientific solutions
2. To apply practical ethics methods as a seven-step guide to case-studies
3. To critique, analyze, and develop best ethical solutions across micro- to metalevels toward real-world problems.
4. To understand how one behaves in an organization professionally as an ethical engineer through the analysis of case studies.
5. To examine and analyze ethics case studies.

Artificial Intelligence (AI) & Data Ethics Unit

Get a first impression and learn where and how to apply ethical principles when handling advanced technologies like artificial intelligence.

This unit covers three key components including applicable ethical principles, how to demonstrate ethical compliance while considering other important domains e.g. legal obligations and technical limitations.

Learning objectives:

    • to understand ethical principles and how to apply them.
    • to understand different ethical guidelines and how to apply them.
    • to demonstrate concept decisions based on ethical & technical standards.
    • to understand possible risks and how to minimize them.

Course target audience: Tokyo Tech faculty, staff and students. Instructor notes are available for unit 7. Please contact OEDO Prof. Cross by email for the instructor notes as well as for access to the student's progress report and course grade.

Course Languages

Science and Engineering Ethics (Units 1 - 6)

    • Content – Japanese/English

    • Assignments/quizzes – Japanese/English
    • Video Lectures – Science and Engineering Ethics Japanese Audio with Japanese/English closed captions
    • Discussion Board – Japanese and English
    • Slides: Japanese and English

AI and Data Ethics (Unit 7)

    • All materials (lectures, quizzes, slides, and case study) are in English whereas transcripts are available in English and Japanese.

Grade assessment is by quizzes at the end of units and within selected videos. Learners are expected to achieve a score of 60% or higher for a passing grade in this online course. Tokyo Tech students, take a screen shot of your progress (in the menu bar) to verify you have completed the course which can be used for meeting your graduation requiment.

Case studies are ungraded in units 3 and 7. These were created for self-study or use by instructors in their ethics related classes.

Course Unit Structure:

    • Learning Objectives– lists topics covered in the unit and learning expectations
    • Contents & Knowledge Check– to help you understand what the Unit is about
    • Unit Quiz– to help you gauge your Unit knowledge
    • References– Unit resources

2020 Course schedule

    • Course Enrollment Starts: April 1, 2020
    • Course Starts: April 20, 2020
    • Enrollment Stop Date: January 31, 2021
    • Course end date: Feb. 28, 2021

This is a self-paced course where learners can study it from April 20, 2020 until February 28, 2021. After the course end date, learners can still have access to course content while they are a student at Tokyo Tech. Slides are available at the beginning of each unit in pdf format.

Expected self-study effort: 2-3 hours/unit for 7 units

Learning Research
Data from learners who choose to participate in a learning research study will be used to develop an AI based personal online learning system for future versions of this course. This research study has been approved by the Tokyo Tech human subject ethical research committee covering the period June 2019 – Sept. 2021 and is being done in collaboration with Tokyo Tech Online Education Development Office and Prof. Jeffrey Cross' lab in the Transdisciplinary Science and Engineering Department. This research is being funded by a Japan Society for Promotion of Science (JSPS) basic research grant B starting in 2020 for 5 years. Further research on learners' engagement with the course and how they learn is also being conducted within this course. Learner data will be handled based upon the edX privacy policy and Tokyo Tech ethical research policy to ensure strict confidentially. 

Course Team the course was prepared by Staff in the Online Education Develop Office, Professor and General Manager Jeffrey S. Cross and instructional designer Ms. Saya Goto (2017 course version and former Tokyo Tech employee). The video lectures were prepared and delivered by former Tokyo Tech Prof. Jun Fudano and now a professor at Waseda Univ. and IT-Deutschland Global Business Solutions KK, Japan, CEO Mr. Daniel Schwarz. OEDO teaching assistants were involved in developing this course and are listed here: Anastasia, May, Ayaka, Cesar, Abraham, Kono, Chen, Tan, Khanh, Ino, Ornida, Shindhu, Anh, Rami, Nopphon, and others.

コースシラバス2020年4月20日 (Course explaination in Japanese below)

コース: “東工大の科学技術(AI・データ)倫理・ Tokyo Tech Science,Engineering and AI Data Ethics 2020”

人間がよく生きること (well-being) を発展するために、学習者の皆さんの科学や工学の専門性に役立つ伝統的かつ志向的な倫理を学びましょう。このコースは2017年度に日本語でリリースされたedX MOOC、科学と工学の倫理の改訂版です。このオンラインコースは人工知能(AI)とデータ倫理の新しいクイズと教材を含んだ英語、日本語のコースです。自動運転、AIでのヘルスケア、水質汚染に関するケーススタディーも含まれています。オリジナルコースにAIとデータ倫理に関する新しいセクションを加えました。さらに、東工大の学生にはオンライン学習におけるメタ認知(効果的な学び方に関する思考)とAIに基づく個人オンライン学習開発に関する研究に参加することができます。また、このオンライン学習開発コース(POALSの研究)を2020年12月31日2021年1月26日までに全て受講完了した学生の方々先着50名にもれなく3,000円分のAmazonギフト券を研究協力の謝礼としてお渡しいたします。詳細は以下とUnit 1を参照してください。









1. 工学的・科学的解決策の重大な社会的・環境的インパクトを認識する。

2. ケーススタディーに対して実用的な倫理手法であるセブン・ステップ・ガイドを応用する。

3. 現実世界の問題に足しひてマクロからメタレベルにかけて倫理的に最も良い解決策を批判し、分析し発展させる。

4. ケーススタディーの分析を通じて、倫理的な技術者として専門的な組織内でどのように個人がふるまうかを理解する。

5. 倫理的ケーススタディーを評価し、分析する。








科学工学の倫理(Unit1- 6

・提出物、クイズ - 日本語、英語

・ビデオ講義 - 音声は日本語、英語と日本語の字幕あり。それぞれのページに2つのビデオがあります。上部は日本語音声、日本語のスライドで、下部のものはスライドとポップアップが英語です。

・ディスカッションボード - 日本語、英語

・スライド -日本語、英語

AI・データ倫理(Unit 7)





- そのユニットと学習体験によってカバーされるトピックのリスト

・学習内容および確認 - そのユニットの理解を助けるための教材

・ユニットクイズ - そのユニットに関する知識の評価(まとめのクイズ)

・参考文献 - そのユニットで使用した参考文献のリスト