AI-Powered Methods in Digital Sociology: Opportunities and Challenges for Researchers

This paper explores the transformative role of AI-Powered Methods in digital sociology, particularly in enhancing the speed and adaptability of social research to pressing social issues. Traditional methods often struggle to keep pace with the rapid changes in digital society.

AI-powered methods, such as automated and enhanced data collection and data analysis through machine learning applications, may allow researchers to quickly collect, process, and interpret different data types, including texts, images, audio, and videos.

These methods may be crucial for addressing pressing social issues and making research more responsive and proactive. However, while these methods offer significant benefits, they also pose challenges related to the technological affordances of AI systems, such as the underlying statistical models and algorithmic processes they are built on.

This paper shows the risks of adopting AI uncritically, which could result in a simplistic view of social research that overlooks crucial methodological and epistemological considerations about data construction and analysis. The article’s results critically examine the effects of AI affordances, emphasising the importance of balancing technological applications with a nuanced understanding of AI’s impact on research practices.