Code and Credibility: Content Analysis of AI-Driven Journalism in India

Abstract

This research study looks at Artificial Intelligence (AI) and robotic journalism in the Indian media ecosystem by adopting a secondary data analysis method in various reports and publications from the Reuters Institute, WAN-IFRA, NITI Aayog, UNESCO, and scholarly journals. The research noted that AI technologies were being adopted across content types or categories, and in categories, we note as traditional journalism; it was likely more than a novelty. Using comparative content analysis of samples of news articles generated by AI and the social implications of automation in journalism, the degree of impact it may have on the credibility of journalism as a product and process will be examined. Some visual data are presented as bar graphs where we note the reach of AI across content categories for the products we sampled (i.e. sports, weather, finance, politics, entertainment, and health). The study concludes that Indian newsrooms apply AI in fairly structured, data-heavy content types (where the audience generally expects to see data), such as sports and weather. While opinion journalism and political reporting exhibited more caution, before their journalistic philosophy of truthfulness and trust, they expressed caution in newsroom policy out of ethics, trust and credibility issues. The study also suggested introducing ethical frameworks, training regimes for newsrooms, and policies for responsibly adopting AI technology in journalism.