| Project/Area Number |
22K01898
|
|---|
| Research Category |
Grant-in-Aid for Scientific Research (C)
|
| Allocation Type | Multi-year Fund |
|---|
| Section | 一般 |
|---|
| Review Section |
Basic Section 08010:Sociology-related
|
|---|
| Research Institution | Saitama University |
|---|
Principal Investigator |
Noh SungChul 埼玉大学, 人文社会科学研究科, 准教授 (90758492)
|
|---|
| Project Period (FY) |
2022-04-01 – 2025-03-31
|
| Project Status |
Granted (Fiscal Year 2023)
|
| Budget Amount *help |
¥4,160,000 (Direct Cost: ¥3,200,000、Indirect Cost: ¥960,000)
Fiscal Year 2024: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2023: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
Fiscal Year 2022: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
|
|---|
| Keywords | Platform labor / Online gig work / Algorithmic control / Young workers / Remote work / Data labeling / Artificial intelligence / Precarious employment / Data Labeling / Machine learning / Generative AI / Nonstandard employment / Youth labor market / New way of work |
|---|
| Outline of Research at the Start |
This project explores i) how digital platform companies manage its young workforce , ii) how platform workers experience the new form of work in the context of Japanese and Korean youth labor markets, and iii) how national policy shapes the relationship between platform and its crowd workers.
|
| Outline of Annual Research Achievements |
1. Data collection on online gig workers: Over the past five years, I've conducted interviews with online gig workers consistently. The longitudinal dataset I've compiled holds significant value, particularly since many previous studies in this area have been cross-sectional. For example, this interview data can be utilized to examine how and why the attitudes, behaviors, and performance of the rapidly growing population of online gig workers evolve over time.
2. Publication of findings: I publishing several papers in academic journals derived from the analysis of data collected in the project's early stages. Additionally, I have presented my preliminary findings at prominent management and labor relations conferences abroad.
|
| Current Status of Research Progress |
Current Status of Research Progress
1: Research has progressed more than it was originally planned.
Reason
The rapid advancement of generative AI, such as ChatGPT, introduced a compelling variable to my research project. This is particularly noteworthy as the development of generative AI relies heavily on extensive data labeling labor. The precarious labor conditions associated with this process have garnered significant media attention.
In this context, I attempted to recruit online gig workers who engaged in the training of Generative AI. My interviews with them provided an opportunity to theorize about the evolving nature of human labor in response to technological advancements.
I was also able to interview not only online gig workers, but also full-time workers for the platform companies that manage them. This gave me a better understanding of algorithmic control.
|
| Strategy for Future Research Activity |
This year marks the final year of my research project, during which my primary focus will be on analyzing the data collected and publishing the findings in leading international journals.
To kickstart this process, I will present some of our key findings at the upcoming annual meeting of the American Sociological Association this summer. The feedback received during the presentation will help me refine the manuscript further and submit it to the journals in the field of labor sociology and employment relations later this year.
Additionally, I am laying the groundwork for the continuation of this research project in the years to come. I am currently assembling a research team comprising researchers for a comparative study of online gig work in Japan, Korea, and China.
|
