Exploring AI's Impact on Podcast Production

Abstract

This research paper explores the deployment of Artificial Intelligence (AI) technologies in podcast production and distribution. The use of AI and machine learning in different phases of podcast creation – from automating postproduction tasks to personalizing episode content – is analyzed. The focus is on how podcast making is improved through processes that are either deprecated or enhanced by AI and what does content quality mean in the context of AI intervention.

The democratization of content creation tools and distribution channels has encouraged people to produce their own media content since the inception of the web. Recent advancements in AI have seen computational machines become powerful tools in producing and analysing content as well. The media and entertainment industries are expected to be one of the key first adopters of AI technology in the forthcoming years.

Like all other forms of media, many podcasts are being produced globally, however very few podcasts find an audience to communicate those ideas to. With AI being adapted there is an opening to improved quality of production and targeted promotion. This essay is an attempt to explore AI's role in streamlining processes and potentially improve content quality similar to film production. At a time, film postproduction took weeks, involved many people and cost a fortune – today’s software has streamlined this into a one-person, few-hours task; or aviation, which has been automated to the point where most commercial airliners can takeoff, autopilot and land without need of human input. On the other hand, mediation is a very human task, subjective and interpretive – what kind of audio content will humans evolve to ‘feel’ as made by a machine?

Keywords AI, podcast production, machine learning, content quality, automation, media democratization, targeted promotion, content creation.