Young people find support from AI-generated responses on topics ranging from relationships to physical health. When it comes to sensitive topics, such as suicidal thoughts, however, they prefer human responses, according to a new study.
For decades, social media has increasingly become young people’s main method of peer support exchange. Researchers sought to understand when and how AI can facilitate and assist in such exchanges.
For the study, the researchers analyzed survey responses from 622 people aged 18 to 24 who have experience seeking and giving support online. In the study, participants evaluated blinded human- and AI-generated responses to help-seeking messages (meaning they did not know who wrote the responses).
The human responses reflected various types of human support young people may encounter, including peers, adult mentors, and therapists.
The findings showed that participants responded positively to the AI-generated responses about relationships, self-expression, and physical health, noting that they seemed caring and offered actionable suggestions.
However, they strongly preferred the human-generated response to help-seeking messages about a sensitive topic like suicidal thoughts.
“This type of research is important to understand how AI can help young people in a safe and effective way,” says Jordyn Young, a doctoral student at the University of Michigan School of Information and lead author of the study.
“It’s not just what the model says, but also how. Being honest about the limitations of AI’s help-giving capabilities is good, but we need to phrase it carefully—especially in response to sensitive disclosures.”
Since young people access the internet daily, having different ways to share their thoughts—especially with AI-generated responses—could be beneficial for the long term, the researchers say.
“Our research suggests that AI-powered tools may help youth peers support each other during challenging times by helping them figure out what to say,” Young says.
The researchers presented the study at the Conference on Human Factors in Computing Systems in Hawaii.
Additional coauthors are from Drexel University.
Source: University of Michigan
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Previously Published on futurity.org with Creative Commons License
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