62360001 Contemporary industrial society

Hiroshima University Syllabus

Japanese

Academic Year 2026Year School/Graduate School Liberal Arts Education Program

Lecture Code 62360001 Subject Classification Area Courses

Subject Name 現代社会と産業

Subject Name
（Katakana）ゲンダイシャカイトサンギョウ

Subject Name in
English Contemporary industrial society

Instructor SHIN JAEYOUL

Instructor
(Katakana) シン　ゼヨル

Campus Across Campuses (videoconferencing, etc.) Semester/Term 1st-Year, First Semester, 2Term

Days, Periods, and Classrooms (2T) Mon5-8：Online

Lesson Style Lecture Lesson Style
(More Details) Online (simultaneous interactive)

Lecture, group discussion
Language to be used in the lecture is only Japanese.

Credits 2.0 Class Hours/Week 4 Language of Instruction J : Japanese

Course Level 2 : Undergraduate Low-Intermediate

Course Area（Area） 24 : Social Sciences

Course Area（Discipline） 05 : Sociology

Eligible Students

Keywords AI, Algorithmic Management, Platform Labour, Labour Process, Deskilling, Precariat, Digital Divide, Industrial Relations, Emotional Labour, LLMs

Special Subject for Teacher Education 　 Special Subject 　

Class Status within
Liberal Arts Education Learn the fundamentals of industrial and labor sociology to understand how the AI Revolution has transformed modern industrial society. This content specifically reflects the latest AI industry changes, including the rapid advancement of agentic AI, the generative AI cost revolution, and global trends in AI regulation during 2024-2025.
Area Subjects (Humanities and Social Sciences Group)　Classification: Law, Political Science, Sociology, Economics, Education
Expected Outcome Accurately understand the impact of algorithmic development on modern industrial society.
Learn the precise application of the latest AI-related tools (text generation, image generation, video production, etc.).
Thoroughly master the ethical issues that must be understood when utilizing AI.
Understand industrial and occupational structures to recognize the diverse problems facing modern industrial society (inequality, industrial accidents, etc.).
Acquire the fundamental knowledge necessary for career path selection.

Here's an example of the video you'll actually create in this class (https://youtu.be/OichDVdmsSU)

Class Objectives
/Class Outline ① Acquire the fundamental concepts and analytical frameworks of industrial sociology and the sociology of work.
② Develop an accurate understanding of how the advancement of algorithms affects labour processes, labour markets, and industrial relations in contemporary industrial society.
③ Learn to use AI-related tools (text generation, image generation, video production, etc.) while cultivating the ability to critically analyse their social implications.
④ Understand the ethical issues associated with AI use and recognise the inequalities generated by changes in industrial and occupational structures.
⑤ Acquire foundational knowledge necessary for career planning.

Class Schedule lesson1　Orientation: What Is Industrial Sociology? The interplay between technology and society / Understanding the concept of "algorithms" / Overview of course structure and grading criteria
lesson2　The Birth of Modern Society and Technology
From the Renaissance to the Scientific Revolution / Transformations in knowledge systems and the precursors of industry
lesson3　Labour Process Theory (1): Taylorism and Scientific Management
Taylor’s principles and the deskilling of labour / The Braverman thesis
lesson4　Labour Process Theory (2): From Fordism to Post-Fordism
The Ford system, JIT, and the Toyota Production System / Flexible specialisation
lesson5　Industrial Relations and Their Transformation
Characteristics and changes in Japanese-style industrial relations / Enterprise unions and the Shuntō (Spring Offensive) today
lesson6　The AI Revolution and Industry 4.0 / Digital Transformation (DX) and Industry 4.0 / The rise of Agentic AI and changes in the industrial ecosystem
[Practical Exercise]
Draft and compare business proposals using multiple LLMs (GPT, Claude, Gemini)
Sociological Question: What design philosophies of each platform company are reflected in the differences among LLM-generated proposals? What kinds of intellectual labour can AI substitute? Can this be explained through Braverman’s deskilling thesis?
Note: All AI tools used in this session are free versions.
lesson7　Platform Labour and Algorithmic Management
Labour control structures in delivery platforms such as Uber Eats / Algorithmic management vs. bureaucratic management
Sociological Question: How does algorithmic management differ from—and resemble—Taylor’s scientific management? How should we analyse the gap between the discourse of "flexible work" and the reality?
lesson8　Telework and the Spatial Reorganisation of Labour
Changes in working practices since the COVID-19 pandemic / Possibilities and limitations of location-independent work
lesson9　AI and Visual Communication
Changes in the visual media industry and the cutting edge of generative video (Sora, Veo, Kling) [Practical Exercise]
Produce a one-minute industry introduction video using AI video-creation tools
Sociological Question: How does AI video-generation technology transform the labour process in the film/media industry? How should we understand the changing status of professionals in the age of "everyone is a creator"?
Note: AI tools other than Sora, Veo, and Kling may also be used.
lesson10　International Division of Labour and Logistics
The structure of global supply chains / Digitalisation of logistics and working conditions
lesson11　 Restructuring of the Labour Market and the Digital Divide
Contemporary developments in dual labour market theory / Polarisation of employment through AI and the precariat
[Practical Exercise]
AI-based job-matching experience — Analyse your future occupation with AI
Sociological Question: Do the algorithms behind AI-powered job matching reproduce existing social inequalities (educational background, gender, region)? Whose interests does the matching serve?
Note: Entering sensitive personal information (full name, contact details, student ID, health data, family circumstances) into AI tools is strictly prohibited.
lesson12　AI Ethics, Industrial Safety, and Algorithmic Bias
Global trends in AI regulation (EU AI Act, etc.) / Sociological perspectives on discrimination and inclusion
Sociological Question: What does "fairness" in algorithms mean? What is the relationship between technological solutions and social solutions?
lesson13　Labour Policy and Legal Issues
The legal status of platform workers (the question of worker classification) / Challenges for labour law and social security in the AI era
lesson14　AI and Career Design
Changes in occupational structure in the AI era and individual career strategies
[Practical Exercise]
Self-analysis and career roadmap creation with AI — Analyse your strengths with AI and apply them to future planning
Sociological Question: Does AI-driven "self-analysis" objectively measure individual abilities, or does it function as a device that internalises the value criteria of a particular labour market? Who decides what the "right job" is?
Note: Entering sensitive personal information (full name, contact details, student ID, health data, family circumstances) into AI tools is strictly prohibited.
lesson15　Conclusion: Industrial Society Past and Future
Review of the entire course / Challenges and prospects for industrial sociology in the AI era

Text/Reference
Books,etc. There are no textbooks. The lecturer distributes the materials.

PC or AV used in
Class,etc. Handouts, Visual Materials, Microsoft Forms, moodle

(More Details)

Learning techniques to be incorporated Discussions, Quizzes/ Quiz format

Suggestions on
Preparation and
Review The lecturer recommends students to read related materials and reference literatures.

Requirements

Grading Method 1.Final Report (50%)
Assignment:
Choose an industry of interest and use AI tools to research and analyse the current state of AI adoption in that industry. Compile your findings into a report.
Required elements:
(a) Types of AI tools used; (b) At which stages and how each tool was used; (c) How AI outputs were revised and refined; (d) A sociological analysis of how AI is affecting the labour process in the chosen industry.

2.AI Practical Exercise Assignments (30%)
Submission of outputs from practical exercises including text generation, video production, job analysis, and self-analysis (4 exercises).
Important: Each practical assignment must include a response to the designated "Sociological Question" (minimum 200 characters). Grading will assess not only the technical quality of the output but also the quality of sociological analysis.

3.Reaction Papers (20%)
Due after every session. Minimum 300 characters each.
⚠ Note: This course is conducted 100% online. Attendance will be strictly monitored through login records and assignment submissions. Students who fail to participate in six or more sessions will automatically be deemed ineligible for course credit.

Practical Experience

Summary of Practical Experience and Class Contents based on it

Message

Other

Please fill in the class improvement questionnaire which is carried out on all classes.
Instructors will reflect on your feedback and utilize the information for improving their teaching.

Academic Year	2026Year	School/Graduate School	Liberal Arts Education Program
Lecture Code	62360001	Subject Classification	Area Courses
Subject Name	現代社会と産業
Subject Name （Katakana）	ゲンダイシャカイトサンギョウ
Subject Name in English	Contemporary industrial society
Instructor	SHIN JAEYOUL
Instructor (Katakana)	シン　ゼヨル
Campus	Across Campuses (videoconferencing, etc.)	Semester/Term	1st-Year, First Semester, 2Term
Days, Periods, and Classrooms	(2T) Mon5-8：Online
Lesson Style	Lecture	Lesson Style (More Details)	Online (simultaneous interactive)
Lecture, group discussion Language to be used in the lecture is only Japanese.
Credits	2.0	Class Hours/Week	4	Language of Instruction	J : Japanese
Course Level	2 : Undergraduate Low-Intermediate
Course Area（Area）	24 : Social Sciences
Course Area（Discipline）	05 : Sociology
Eligible Students
Keywords	AI, Algorithmic Management, Platform Labour, Labour Process, Deskilling, Precariat, Digital Divide, Industrial Relations, Emotional Labour, LLMs
Special Subject for Teacher Education		Special Subject
Class Status within Liberal Arts Education	Learn the fundamentals of industrial and labor sociology to understand how the AI Revolution has transformed modern industrial society. This content specifically reflects the latest AI industry changes, including the rapid advancement of agentic AI, the generative AI cost revolution, and global trends in AI regulation during 2024-2025. Area Subjects (Humanities and Social Sciences Group)　Classification: Law, Political Science, Sociology, Economics, Education
Expected Outcome	Accurately understand the impact of algorithmic development on modern industrial society. Learn the precise application of the latest AI-related tools (text generation, image generation, video production, etc.). Thoroughly master the ethical issues that must be understood when utilizing AI. Understand industrial and occupational structures to recognize the diverse problems facing modern industrial society (inequality, industrial accidents, etc.). Acquire the fundamental knowledge necessary for career path selection. Here's an example of the video you'll actually create in this class (https://youtu.be/OichDVdmsSU)
Class Objectives /Class Outline	① Acquire the fundamental concepts and analytical frameworks of industrial sociology and the sociology of work. ② Develop an accurate understanding of how the advancement of algorithms affects labour processes, labour markets, and industrial relations in contemporary industrial society. ③ Learn to use AI-related tools (text generation, image generation, video production, etc.) while cultivating the ability to critically analyse their social implications. ④ Understand the ethical issues associated with AI use and recognise the inequalities generated by changes in industrial and occupational structures. ⑤ Acquire foundational knowledge necessary for career planning.
Class Schedule	lesson1　Orientation: What Is Industrial Sociology? The interplay between technology and society / Understanding the concept of "algorithms" / Overview of course structure and grading criteria lesson2　The Birth of Modern Society and Technology From the Renaissance to the Scientific Revolution / Transformations in knowledge systems and the precursors of industry lesson3　Labour Process Theory (1): Taylorism and Scientific Management Taylor’s principles and the deskilling of labour / The Braverman thesis lesson4　Labour Process Theory (2): From Fordism to Post-Fordism The Ford system, JIT, and the Toyota Production System / Flexible specialisation lesson5　Industrial Relations and Their Transformation Characteristics and changes in Japanese-style industrial relations / Enterprise unions and the Shuntō (Spring Offensive) today lesson6　The AI Revolution and Industry 4.0 / Digital Transformation (DX) and Industry 4.0 / The rise of Agentic AI and changes in the industrial ecosystem [Practical Exercise] Draft and compare business proposals using multiple LLMs (GPT, Claude, Gemini) Sociological Question: What design philosophies of each platform company are reflected in the differences among LLM-generated proposals? What kinds of intellectual labour can AI substitute? Can this be explained through Braverman’s deskilling thesis? Note: All AI tools used in this session are free versions. lesson7　Platform Labour and Algorithmic Management Labour control structures in delivery platforms such as Uber Eats / Algorithmic management vs. bureaucratic management Sociological Question: How does algorithmic management differ from—and resemble—Taylor’s scientific management? How should we analyse the gap between the discourse of "flexible work" and the reality? lesson8　Telework and the Spatial Reorganisation of Labour Changes in working practices since the COVID-19 pandemic / Possibilities and limitations of location-independent work lesson9　AI and Visual Communication Changes in the visual media industry and the cutting edge of generative video (Sora, Veo, Kling) [Practical Exercise] Produce a one-minute industry introduction video using AI video-creation tools Sociological Question: How does AI video-generation technology transform the labour process in the film/media industry? How should we understand the changing status of professionals in the age of "everyone is a creator"? Note: AI tools other than Sora, Veo, and Kling may also be used. lesson10　International Division of Labour and Logistics The structure of global supply chains / Digitalisation of logistics and working conditions lesson11　 Restructuring of the Labour Market and the Digital Divide Contemporary developments in dual labour market theory / Polarisation of employment through AI and the precariat [Practical Exercise] AI-based job-matching experience — Analyse your future occupation with AI Sociological Question: Do the algorithms behind AI-powered job matching reproduce existing social inequalities (educational background, gender, region)? Whose interests does the matching serve? Note: Entering sensitive personal information (full name, contact details, student ID, health data, family circumstances) into AI tools is strictly prohibited. lesson12　AI Ethics, Industrial Safety, and Algorithmic Bias Global trends in AI regulation (EU AI Act, etc.) / Sociological perspectives on discrimination and inclusion Sociological Question: What does "fairness" in algorithms mean? What is the relationship between technological solutions and social solutions? lesson13　Labour Policy and Legal Issues The legal status of platform workers (the question of worker classification) / Challenges for labour law and social security in the AI era lesson14　AI and Career Design Changes in occupational structure in the AI era and individual career strategies [Practical Exercise] Self-analysis and career roadmap creation with AI — Analyse your strengths with AI and apply them to future planning Sociological Question: Does AI-driven "self-analysis" objectively measure individual abilities, or does it function as a device that internalises the value criteria of a particular labour market? Who decides what the "right job" is? Note: Entering sensitive personal information (full name, contact details, student ID, health data, family circumstances) into AI tools is strictly prohibited. lesson15　Conclusion: Industrial Society Past and Future Review of the entire course / Challenges and prospects for industrial sociology in the AI era
Text/Reference Books,etc.	There are no textbooks. The lecturer distributes the materials.
PC or AV used in Class,etc.	Handouts, Visual Materials, Microsoft Forms, moodle
(More Details)
Learning techniques to be incorporated	Discussions, Quizzes/ Quiz format
Suggestions on Preparation and Review	The lecturer recommends students to read related materials and reference literatures.
Requirements
Grading Method	1.Final Report (50%) Assignment: Choose an industry of interest and use AI tools to research and analyse the current state of AI adoption in that industry. Compile your findings into a report. Required elements: (a) Types of AI tools used; (b) At which stages and how each tool was used; (c) How AI outputs were revised and refined; (d) A sociological analysis of how AI is affecting the labour process in the chosen industry. 2.AI Practical Exercise Assignments (30%) Submission of outputs from practical exercises including text generation, video production, job analysis, and self-analysis (4 exercises). Important: Each practical assignment must include a response to the designated "Sociological Question" (minimum 200 characters). Grading will assess not only the technical quality of the output but also the quality of sociological analysis. 3.Reaction Papers (20%) Due after every session. Minimum 300 characters each. ⚠ Note: This course is conducted 100% online. Attendance will be strictly monitored through login records and assignment submissions. Students who fail to participate in six or more sessions will automatically be deemed ineligible for course credit.
Practical Experience
Summary of Practical Experience and Class Contents based on it
Message
Other
Please fill in the class improvement questionnaire which is carried out on all classes. Instructors will reflect on your feedback and utilize the information for improving their teaching.

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