A recent study documented a participant using an AI model to simulate a conversation with her late grandmother. According to her report, the experience offered a sense of closure that she had not experienced before.
This interaction was one of sixteen documented in a study published in the Proceedings of the 2026 ACM Designing Interactive Systems Conference. The research provides some of the first empirical data on how individuals respond to the opportunity to communicate with AI representations of deceased loved ones.
Researchers at the University of Colorado Boulder call these AI agents ‘generative ghosts.’ These systems use data such as writing, voice recordings, or photographs from the deceased to create simulated conversations. Some platforms, such as Project December and Séance AI, generate text-based versions of journal entries and messages. Others, such as HereAfterAI, include voice and images. A few companies have also developed virtual reality experiences that let users interact with holographic representations of loved ones.
Jack Manning, the PhD candidate in Information Science who led the study, expected the sessions to feel unsettling. “We originally thought it might feel very Black Mirror creepy to people and make them uncomfortable,” he said. “I ended up being completely wrong. People thought it was amazing.”
How To Build a Ghost
The study included 16 participants, aged 22 to 50, each of whom joined a Zoom interview about a deceased relative or friend. During the session, a facilitator led the conversation while another researcher entered details into a large language model, generating an AI representation of the deceased in real time.
Each participant interacted with two versions of the AI model for about twenty minutes each. One version spoke as the deceased, using the first person, while the other described the person in the third person. A facilitator stayed present to offer support if the conversation became emotionally difficult.
The results indicated a clear preference for the version that spoke as the deceased individual, rather than about them. Researchers described this as a preference for ‘reincarnation’ over ‘representation.’
What People Will and Won’t Forgive
Participants tended to overlook factual mistakes or made-up details from the AI. What mattered more was whether the AI captured the right tone and language. If the model used words or phrases that felt out of character, people were more likely to disconnect from the experience. The study found that getting the voice and manner right was more important than perfect factual accuracy.
How the AI communicated also shaped the experience. Participants preferred short, to-the-point sentences and even the use of emojis, rather than the longer, more formal responses that AI models often produce. This suggests that future versions of these systems should pay close attention to conversational style.
A Technology Both Wanted, and Feared
All sixteen participants indicated that they would be willing to use the technology again. However, most also expressed concerns about the potential risks of individuals in grief accessing these AI systems without supervision.
Lead researcher Jack Manning said his own experiences with loss have shaped his view of the risks and benefits of AI grief tools. He acknowledged that negative outcomes are possible but also noted that the technology could help some users find a sense of closure and peace.
Jed Brubaker, the study’s senior author and an associate professor of Information Science, said the lab took on the work precisely because the field had outpaced the research. “To our knowledge, we are conducting the first user experience studies of simulated AI ghosts,” he said.
The research team intends to involve mental health professionals in future studies. The next phase will evaluate the psychological risks and benefits of prolonged use of AI grief tools to ensure that empirical research guides product development.
Generative ghost technology is already available through commercial platforms, and people are actively using these systems. The study highlights that voice, tone, and pacing are often more important to users than factual accuracy. As the technology develops, researchers are working to address the challenges of providing appropriate safeguards and responsible design.
Austin Burgess is a writer and researcher with a background in sales, marketing, and data analytics. He holds an MBA, a Bachelor of Science in Business Administration, and a data analytics certification. His work focuses on breaking scientific developments, with an emphasis on emerging biology, cognitive neuroscience, and archaeological discoveries.