AI and Suicide Prevention
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Suicide is one of the most preventable causes of the death. There are a number of measures that can be taken at population, sub-population and individual levels to prevent suicide and suicide attempts. In the recent years, artificial intelligence and machine learning have emerged as ways to improve the detection of suicide risks, to help diagnose patients more accurately, improve clinical decision making, and determine the effects of risk and protective factors on suicide.
Although there is substantial evidence indicating that machine learning models’ can predict potential suicidal behaviors and thoughts, there are still many questions concerning the ethical issues and practical challenges in using these technologies. For instance, the news of a Belgian man dying by suicide following unsettling exchanges with an AI-powered chatbot raised serious concerns all over Europe early this year.
This webinar will explore three complementary questions First, how can AI help front line workers in suicide prevention and aid in the development of mental health promotion strategies? Second, what ethical issues must be addressed in when using existing technologies in suicide prevention and detection of persons at risk, and in the development of new technologies.? Third, how can we ensure that these technologies remain safe and effective for both mental health workers and suicidal individuals?
This session is organized in partnership with CLAIRE Brussels.
This live event includes a 30-minute networking event hosted on the AI for Good Neural Network. This is your opportunity to ask questions, interact with the panelists and participants and build connections with the AI for Good community.