As an exponentially growing industry, Artificial Intelligence (AI) has become an essential part of our lives in the different forms such as virtual assistants, chatbots, and self-driven cars. While humanity witnesses the unstoppable growth of the sector, repetitive discussions about whether machines can replace human labor have also gained momentum along with this transformative technology one more time. However, there is an important detail that gets lost in the heat of these discussions is that the artificial intelligence industry needs not only high-quality engineers to design algorithms. Human labor that produces, improves, and categorizes data at a more basic level is also an indispensable part of the process. Microworkers, as workers who meet this basic level need of the AI industry, are workers who generally work remotely and perform tasks such as data labeling and detecting inappropriate content during the AI training process. Those workers are often associated with poorly paid, precarious, and lacking job security with intensive and sometimes toxic working conditions. ChatGPT (Chat Generative Pre-trained Transformer) by OpenAI is the most famous large language model-based chatbot that requires intensive microworker labor in the field. Despite the rapid growth of this dynamic and promising sector, authorities and academics are lagging behind in addressing the problems possessed by this relatively new sector. This thesis conducts a comprehensive examination of the exploitative aspects embedded in microwork, with a specific focus on ethical considerations in data collection of microworkers. The study aims to explore the complex dynamics of microwork, highlighting ethical concerns surrounding AI-driven data collection. Finally, this research aims to enhance the attractiveness of the sector by contributing to the discourse on creating ethical frameworks that prioritize and protect the rights of those involved in micro-tasks within the field of artificial intelligence.
As an exponentially growing industry, Artificial Intelligence (AI) has become an essential part of our lives in the different forms such as virtual assistants, chatbots, and self-driven cars. While humanity witnesses the unstoppable growth of the sector, repetitive discussions about whether machines can replace human labor have also gained momentum along with this transformative technology one more time. However, there is an important detail that gets lost in the heat of these discussions is that the artificial intelligence industry needs not only high-quality engineers to design algorithms. Human labor that produces, improves, and categorizes data at a more basic level is also an indispensable part of the process. Microworkers, as workers who meet this basic level need of the AI industry, are workers who generally work remotely and perform tasks such as data labeling and detecting inappropriate content during the AI training process. Those workers are often associated with poorly paid, precarious, and lacking job security with intensive and sometimes toxic working conditions. ChatGPT (Chat Generative Pre-trained Transformer) by OpenAI is the most famous large language model-based chatbot that requires intensive microworker labor in the field. Despite the rapid growth of this dynamic and promising sector, authorities and academics are lagging behind in addressing the problems possessed by this relatively new sector. This thesis conducts a comprehensive examination of the exploitative aspects embedded in microwork, with a specific focus on ethical considerations in data collection of microworkers. The study aims to explore the complex dynamics of microwork, highlighting ethical concerns surrounding AI-driven data collection. Finally, this research aims to enhance the attractiveness of the sector by contributing to the discourse on creating ethical frameworks that prioritize and protect the rights of those involved in micro-tasks within the field of artificial intelligence.
A Comprehensive Analysis of The Exploitative Nature of Microwork in the field of Generative Artificial Intelligence the case of OpenAi and the Issues Related to data protection of Microworkers
OZDEMIR, BARANCAN
2023/2024
Abstract
As an exponentially growing industry, Artificial Intelligence (AI) has become an essential part of our lives in the different forms such as virtual assistants, chatbots, and self-driven cars. While humanity witnesses the unstoppable growth of the sector, repetitive discussions about whether machines can replace human labor have also gained momentum along with this transformative technology one more time. However, there is an important detail that gets lost in the heat of these discussions is that the artificial intelligence industry needs not only high-quality engineers to design algorithms. Human labor that produces, improves, and categorizes data at a more basic level is also an indispensable part of the process. Microworkers, as workers who meet this basic level need of the AI industry, are workers who generally work remotely and perform tasks such as data labeling and detecting inappropriate content during the AI training process. Those workers are often associated with poorly paid, precarious, and lacking job security with intensive and sometimes toxic working conditions. ChatGPT (Chat Generative Pre-trained Transformer) by OpenAI is the most famous large language model-based chatbot that requires intensive microworker labor in the field. Despite the rapid growth of this dynamic and promising sector, authorities and academics are lagging behind in addressing the problems possessed by this relatively new sector. This thesis conducts a comprehensive examination of the exploitative aspects embedded in microwork, with a specific focus on ethical considerations in data collection of microworkers. The study aims to explore the complex dynamics of microwork, highlighting ethical concerns surrounding AI-driven data collection. Finally, this research aims to enhance the attractiveness of the sector by contributing to the discourse on creating ethical frameworks that prioritize and protect the rights of those involved in micro-tasks within the field of artificial intelligence.File | Dimensione | Formato | |
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https://hdl.handle.net/20.500.12608/62244