Misinformation, Paradox, and Heuristics: An Algorithmic Nudge to Counter Misinformation

No one is completely immune to misinformation because of how human cognition is built and how misinformation takes advantage of it. Often, using nudges to help steer users into fact-checking the information is much more effective than detecting misinformation. This chapter presents empirical work on the design of nudge interventions in the context of misinformation. Applying the nudge principle to misinformation, it suggests that different cognitive biases that humans are vulnerable to can be leveraged for the design of algorithmic interventions that reduce the consumption and spread of misinformation. The findings from an experiment revealed significant main and interaction effects, indicating that algorithmic source effects are present in the process of nudge sensemaking. Misinformation sharing intention was largely lower for nonalgorithmic news than for algorithm-based news, but there was a greater drop in algorithmic news when nudging was employed. Moderation from algorithmic trust was found, and users’ trust in algorithmic media amplified the nudge effect only for news from algorithmic media and not nonalgorithmic online media sources. The results of our study confirm previous literature that underlined the role of nudging in influencing news sharing. Source credibility has an impact on misinformation sharing on social media, and nudge credibility encourages discerning and acknowledging misinformation. The findings contribute to the design implications of nudging interventions in the context of misinformation, as well as prototyping a range of nudging mechanisms with the goal of evaluating their proximal effects on human behavior in AI.