Media bias and news personalization through AI: A systematic review

Since the integration of artificial intelligence (AI) into news production and distribution systems, there has been increase in news consumption. With unparalleled opportunities in personalizing the news content to achieve longer user engagement, the pre-existing social biases have translated to algorithmic bias. This has led to the phenomenon of filter bubbles, echo chamber, and the algorithmic opacity has rendered marked impacts of social, political and cognitive aspects of human society. This paper uses a systematic review to identify the drastic impacts of AI news personalization and provide concise recommendations based on the comprehensive understanding that can help leverage AI’s benefits with securing journalistic integrity.