Responsible AI for Suicide Prevention

Suicide remains one of the leading causes of death for people aged under 34 worldwide and whilst numbers have declined in many countries overall, they continue to rise in the USA. Pre-existing mental health conditions are often cited as the main contributing factor to suicide risk, however recent research has found that non-clinical factors, such as a person’s social, economic, political and physical circumstances (known as social determinants of health) are also significant contributors and are a driving force behind adverse health outcomes and inequalities. At the same time, recent years have seen a rise in the development of AI tools for detecting suicidal ideation, intent and suicide prevention. These technologies are wide ranging, from language models used in chatbot applications for therapy or triaging to clinical models that are used to predict suicide risk.

In this talk, Annika will give an overview of how AI has been used in suicide research in the past.
She will highlight current approaches to extracting social determinants of health for suicide using AI NLP to better understand non-clinical factors that drive mental health inequalities. Finally, she will discuss ethical concerns and considerations that should be taken into account when using AI for suicide prevention.