New research conducted by Keisha Cutright, a marketing professor at Duke University’s Fuqua School of Business, suggests that people are more likely to trust recommendations from artificial intelligence (AI) when they are actively thinking about God. The study, published in the Proceedings of the National Academy of Sciences, found that thinking about God promotes acceptance of AI recommendations in various contexts, such as choosing movies, financial products, dental treatments, and romantic partners.

In a series of eight experiments, Cutright and co-author Mustafa Karataş exposed participants to tasks and experiences designed to make them think about God. This included asking them to write about what God meant to them, as well as using subtle religious cues like playing religious music in a dental clinic waiting room. The results showed that when people had God on their minds, they were less averse to AI recommendations and more willing to consider them.

Cutright noted that the findings did not completely reverse people’s preference for human recommendations, but they did diminish the advantage humans typically have over AI. She emphasized that the preference for humans is still strong, but when thoughts of God are evoked, the preference becomes closer to a 50/50 split between humans and AI.

Interestingly, the researchers also found that religious individuals generally preferred AI recommendations more than non-religious individuals. Cutright suggested that companies should take these findings into account when targeting specific markets, and businesses using AI should incorporate subtle reminders of the smallness of mankind to enhance consumers’ openness to AI-based recommendations.

Overall, this research highlights the influence of religious thoughts on decision-making processes and sheds light on the complex relationship between humans, AI, and faith.

Source: Mustafa Karataş et al, “Thinking about God Increases Acceptance of artificial intelligence in decision-making,” Proceedings of the National Academy of Sciences (2023). DOI: 10.1073/pnas.2218961120

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