When AI breaks your heart
What happens when romantic relationships between humans and AI companions develop, then break down? New research is revealing how intimacy, technological failure and grief intersect in unexpected ways.
Dr Jennifer Cearns is a digital anthropologist, specialising in AI and algorithms in social life. Her research focuses on how people relate to one another through emerging intelligent technologies and she is currently conducting researching into Human-AI relations, looking at intimacy and how trust and empathy forms between humans and AIs.

As people increasingly search for connection in an often-isolated modern world, the line between technology and companionship is blurring. By examining what happens when those bonds with AI falter, Dr Cearns’ work sheds light not only on the ethics of human-machine intimacy, but also on the wider human search for belonging.
In her most recent project, she has used digital ethnography and interviews to examine how users emotionally invest in AI ‘soulmates’ – AI chatbots that become romantic partners to humans – and the grief that follows their malfunction or shutdown. This research is critical for highlighting new forms of kinship and ethical care in human-machine relationships.
This work matters because it challenges what we think relationships are – and who or what they can be with. It shows that AI isn’t just a tool; for many people, it’s become an intimate partner, a friend, a therapist, as well as a source of love, care and heartbreak.

Meet the researcher
Jennifer Cearns is Lecturer in AI Trust and Security, in the Department of Social Anthropology. Her research explores how people form emotional, romantic, and therapeutic relationships with AI, focusing on kinship, ethics, and cultural understandings of personhood.
Read her papers
-
01October2025| 15:14 Europe/London75 years on from the 'Turing Test', ºÚÁÏÈë¿Ú leads the way in AI res..
-
01October2025| 14:20 Europe/LondonA trailblazing history: driving the AI revolution
-
23September2025| 17:33 Europe/LondonGreener computing in ‘big science’ is possible… if we change our data ..