Automatically highlighting the most deliberative comments, while beneficial for enhancing discussion quality, may lead to several potential drawbacks. One significant concern is the reinforcement of echo chambers, where only certain viewpoints are elevated, potentially marginalizing dissenting opinions or less popular perspectives. This could discourage users from expressing their views if they feel their contributions are unlikely to be recognized or valued.
Another unintended consequence could be the over-reliance on AI assessments, where users may assume that highlighted comments are inherently superior or more valid, leading to a diminished critical engagement with the content. This could stifle diverse opinions and reduce the richness of the discussion.
To mitigate these issues, it is crucial to implement a diversity algorithm that ensures a range of perspectives are highlighted, not just the most deliberative ones. This could involve setting thresholds for the representation of different viewpoints in the highlighted comments. Additionally, providing users with context about how comments are evaluated and the criteria for deliberative quality can foster a more critical engagement with the highlighted content. Transparency in the AI's decision-making process, such as displaying the AQuA scores alongside comments, can help users understand the rationale behind the highlights and encourage them to explore a wider array of opinions.