Консерваторы в три раза чаще кликают на рекомендации ИИ, чем либералы: исследование Университета Темпл

New research from Temple’s Fox School of Business and Associate Professor Monica Wadhwa examines how an individual’s political ideology affects the likelihood of them accepting AI-generated recommendations. Photo by Ryan S. Brandenberg Listen to any Spotify playlist, watch any series on Netflix or subscribe to any podcast on Apple and you’re likely to see familiar prompt at the end. It will read something along the lines of “Because you watched” or “Because you listened to” and then be followed with a list of recommended titles. Now, research from Temple University has found that whether or not you accept these recommendations may depend on your political ideology. “These are AI-generated recommendations, and they are one of the first ways most people experience artificial intelligence in their everyday lives,” said Monica Wadhwa, associate professor and Washburn Memorial Research Fellow within the Department of Marketing in Temple University’s Fox School of Business. “These recommendations reflect our data, behaviors and preferences, and they’re consistent with what we know about us. What we found in our study is that individuals who really value consistency are more likely to make use of these AI-generated recommendations. Wadhwa’s research “Swipe right: When and why conservatives are more accepting of AI recommendations,” recently published in the Journal of Consumer Psychology, examined exactly this phenomenon. By conducting six different studies, Wadhwa and her colleagues examined the influence of political ideology on the likelihood of accepting AI-generated recommendations in categories such as movie streaming, music streaming and recipe websites. Across the board, the researchers found that individuals with conservative political leanings are significantly more likely to accept those recommendations than individuals with liberal political leanings. The findings run counter to previous academic research, which documents that conservatives are less accepting of new technology. “While that has proven true in the past, conservatives also value tradition, stability and consistency,” Wadhwa said. “And, these AI recommendations may be a result of new technology, but they are specifically being built on your preferences. These recommendations are not asking conservatives to change—they reflect continuity. Given that, it makes sense that someone who values consistency would be more likely to use these recommendations.” For one of the six studies that informed the research, Wadhwa and her colleagues launched a Facebook ad campaign simultaneously across conservative and liberal geographic regions within the United States. The campaign was a single advertisement for a music app that promised ‘recommendations based on your past.’ An image of the advertisement can be seen below. Photo courtesy of Monica Wadhwa Overall, the ad campaign received a total of 20,902 impressions. However, the response to the ad differed considerably depending on whether the user resided in a conservative or liberal geographic region. It received significantly more engagement in the conservate areas. For liberal counties, the click-through rate was 0.13%. But for conservative counties, the click-through rate was 0.33%—nearly three times higher. Other studies found that this happens because conservatives value consistency. When recommendations are framed as surprising, they are less likely to accept AI-generated recommendations. “One of the biggest takeaways here is that when you market technology, you need to tailor your message to the right audience,” Wadhwa said. “With technology, we love throwing words like ‘new’ or ‘disruptive.’ We think these words make new technology appealing, but those words can push some people away—and political ideology is the key. With AI-generated recommendations, we are marketing something cutting edge like AI, but making it sound familiar rather than something new resonates better with conservative audiences. This has real implications for both marketing segmentation and positioning. The biggest mistake managers make is assuming everyone wants novelty. Our research shows that for a huge chunk of your market, the standout feature isn’t discovery—it’s consistency.” This research was co-authored by Iman Paul, assistant professor of marketing at the Rutgers School of Business–Camden; Smaraki Mohanty, the Doherty Emerging Professor of Entrepreneurship and an assistant professor of marketing at the Love School of Business at Elon University; and Jeffrey R. Parker, associate professor in the Department of Marketing at the University of Illinois Chicago.