Publications by authors named "Mor Naaman"

People rely on search engines for information in critical contexts, such as public health emergencies-but what makes people trust some search results more than others? Can search engines influence people's levels of trust by controlling how information is presented? And, how does the presence of misinformation influence people's trust? Research has identified both rank and the presence of misinformation as factors impacting people's search behavior. Here, we extend these findings by measuring the effects of these factors, as well as misinformation warning banners, on the perceived trustworthiness of individual search results. We conducted three online experiments (N = 3196) using Covid-19-related queries, and found that although higher-ranked results are clicked more often, they are not more trusted.

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Artificial intelligence (AI) is already widely used in daily communication, but despite concerns about AI's negative effects on society the social consequences of using it to communicate remain largely unexplored. We investigate the social consequences of one of the most pervasive AI applications, algorithmic response suggestions ("smart replies"), which are used to send billions of messages each day. Two randomized experiments provide evidence that these types of algorithmic recommender systems change how people interact with and perceive one another in both pro-social and anti-social ways.

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Human communication is increasingly intermixed with language generated by AI. Across chat, email, and social media, AI systems suggest words, complete sentences, or produce entire conversations. AI-generated language is often not identified as such but presented as language written by humans, raising concerns about novel forms of deception and manipulation.

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