The proposed AI-powered modules, namely the Comment Recommendation Module and the Deliberative Quality Module, can be further extended and combined to tackle challenges like information overload and biased participation. One potential extension is the development of an Information Filtering Module that utilizes natural language processing (NLP) techniques to categorize and summarize discussions. This module could analyze the volume of comments and provide users with a digest of key points, trends, and diverse perspectives, thereby reducing the cognitive load associated with information overload.
Additionally, integrating a Bias Detection and Correction Module could help identify and mitigate biased participation. This module could analyze user comments for patterns of bias, such as overrepresentation of certain viewpoints or demographic groups. By providing feedback to users about their participation patterns and suggesting underrepresented perspectives, the platform could encourage a more balanced discourse.
Combining these modules with the existing AI tools could create a comprehensive system that not only enhances deliberation quality but also ensures that discussions remain inclusive and manageable. For instance, the Information Filtering Module could work in tandem with the Comment Recommendation Module to suggest comments that not only oppose a user's stance but also represent underrepresented viewpoints, fostering a more holistic discussion environment.