Experiences with the Introduction of AI-based Tools for Moderation Automation of Voice-based Participatory Media Forums

TL;DR

This paper presents a case study on implementing AI tools for moderating voice-based discussion forums in India, demonstrating time and cost savings and assessing moderator acceptance.

Contribution

It introduces AI-based moderation tools for voice forums, evaluates their effectiveness, and discusses moderator feedback in a developing country context.

Findings

Significant reduction in moderation time and costs.

Positive moderator feedback on AI automation.

Potential for scaling AI moderation in similar settings.

Abstract

Voice-based discussion forums where users can record audio messages which are then published for other users to listen and comment, are often moderated to ensure that the published audios are of good quality, relevant, and adhere to editorial guidelines of the forum. There is room for the introduction of AI-based tools in the moderation process, such as to identify and filter out blank or noisy audios, use speech recognition to transcribe the voice messages in text, and use natural language processing techniques to extract relevant metadata from the audio transcripts. We design such tools and deploy them within a social enterprise working in India that runs several voice-based discussion forums. We present our findings in terms of the time and cost-savings made through the introduction of these tools, and describe the feedback of the moderators towards the acceptability of AI-based automation in their workflow. Our work forms a case-study in the use of AI for automation of several routine tasks, and can be especially relevant for other researchers and practitioners involved with the use of voice-based technologies in developing regions of the world.