Misinformation and Diversity: Nudging Away from Misinformation Nudging Toward Diversity

This chapter introduces the principle of diversity-aware AI and discusses the need to develop recommendation models to embed AI with diversity awareness to mitigate misinformation. Free and plural ideas are key to addressing misinformation and informing users. A key indicator of the healthy online ecosystem is the existence of diversity of ideas and others’ perspectives. Exposure to diverse sources of news promotes tolerance, social cohesion, and harmonious accord of different ideologies, perspectives, and cultures. Diversity in news recommender systems (NRS) is perceived as a major issue for the preservation of a healthy democratic discourse. In this light of importance, this chapter proposes a conceptual framework for personalized recommendation nudges that can promote diverse news consumption on online platforms. It empirically tests the effects of algorithmic nudges by examining how users make sense of algorithmic nudges and how nudges influence users’ views on personalization and attitudes toward news diversity. The findings show that algorithmic nudges play a key role in understanding normative values in NRS, which then influence the user’s intention to consume diverse news. The findings imply the personalization paradox that personalized news recommendations can enhance and decrease user engagement with the systems. This paradox provides conceptual and operational bases for diversity-aware NRS design, enhancing the diversity and personalization of news recommendations. It proposes a conceptual framework of algorithmic nudges and news diversity, and from there, we develop theoretically grounded paths for facilitating diversity and inclusion in NRS.