AI Tech for Suicide Prevention: How It Works, Why It Matters

AI Tech for suicide prevention is a field that uses artificial intelligence (AI) and machine learning (ML) to analyze various data sources and identify patterns of information and behavior that indicate suicide risk among individuals, especially military veterans.

Suicide is a major public health problem that claims the lives of more than 800,000 people every year worldwide, according to the World Health Organization.

In the U.S., suicide is the 10th leading cause of death, and among military veterans, the rate is 1.5 times higher than the general population.

However, suicide is also preventable, if the risk factors and warning signs are detected and addressed in time. This is where artificial intelligence (AI) and machine learning (ML) can play a vital role.

In this article, you will learn:

– What are AI and ML and how they can help prevent suicide

– What are some examples of AI and ML for suicide prevention

– What are some ethical challenges of AI and ML for suicide prevention

– How to access AI and ML for suicide prevention

What are AI and ML and How They Can Help Prevent Suicide

AI and ML are technologies that can analyze large amounts of data and learn from patterns and trends. They can be used to identify individuals who are at high risk of suicide by using various data sources, such as social media posts, medical records, and financial records.

AI and ML can potentially improve suicide prevention by:

Outperforming traditional models of suicide risk assessment, which rely on self-reporting or clinical judgment.

These models can be inaccurate or unreliable, as some people may not disclose their suicidal thoughts or intentions, or may not seek help due to stigma or lack of access.

Providing early warning signs of suicide risk before it becomes too late. AI and ML can detect subtle changes in behavior, mood, or language that may indicate suicidal ideation or intent.

Enabling proactive interventions by connecting people with the appropriate resources and support. AI and ML can alert health professionals, family members, or support groups when someone is struggling and provide personalized recommendations for treatment or care.

What Are Some Examples Of AI and ML For Suicide Prevention

Some examples of AI and ML for suicide prevention are:

ClearForce: an AI platform that aims to identify the risk of suicide among veterans before it’s too late. The platform uses data from decades of research on the leading indicators of suicide risk, such as mental health conditions, substance abuse, financial difficulties, and social isolation.

It also uses machine learning to monitor changes in behavior and alert health professionals, family members, or support groups when someone is struggling.

Col. Michael Hudson, vice president at ClearForce and a former Marine of 30 years, told Fox News Digital that they are using AI “for good” by incorporating a “human into the conversation” instead of relying on generative AI.

He said that they are “focused on the veteran, working inside the active-duty space to look at the current model and find ways— using technology we’ve developed — to have better outcomes related to reducing suicide.”¹

Bob Filbin, the chief data scientist at ClearForce, told Vox that they have around “10 active rescues per day, where we actually send out emergency services to intervene in an active suicide attempt.” He said that they use machine learning to “figure out who’s at risk and when to intervene.”²

REACH VET: a research project that uses AI to analyze data from electronic health records of veterans who receive care from the Veterans Health Administration.

The project uses an algorithm that assigns a risk score to each veteran based on factors such as diagnoses, medications, hospitalizations, and prior suicide attempts. The algorithm then flags the veterans who are most likely to die by suicide in the next year and notifies their clinicians for follow-up care.

Dr. John Torous, director of the digital psychiatry division at Beth Israel Deaconess Medical Center and an instructor at Harvard Medical School, wrote in JAMA Psychiatry that AI and ML can “outperform traditional models of suicide risk assessment” which rely on self-reporting or clinical judgment.

He said that these models can be inaccurate or unreliable, as some people may not disclose their suicidal thoughts or intentions, or may not seek help due to stigma or lack of access.³

Dr. Rheeda Walker, an associate professor of psychology at the University of Houston, co-authored the JAMA Psychiatry article with Dr. Torous.

She said that addressing gaps in the current suicide prevention efforts can be achieved by “systematically identifying those at risk and using smart technology toward risk assessment, safety planning and building support outside of clinical care.”³

Crisis Text Line: a text messaging-based crisis counseling hotline that uses machine learning to figure out who’s at risk and when to intervene.

The hotline collects a massive amount of data on the 30 million texts it has exchanged with users and uses it to identify the words and emojis that can signal a person at higher risk of suicide ideation or self-harm. The computer then tells the human staff who on hold needs to jump to the front of the line to be helped.

Brian Resnick, a science and health editor at Vox, wrote that the Crisis Text Line does something radical for a crisis counseling service: It collects data on despair.

He said that the data has turned up all kinds of interesting insights on mental health, such as Wednesday being the most anxiety-provoking day of the week and crises involving self-harm often happening in the darkest hours of the night.²

Anyone in the United States can text the number “741741” and be connected with a crisis counselor for free, confidential crisis counseling.

What Are Some Ethical Challenges of AI and ML for Suicide Prevention

AI and ML for suicide prevention also face some ethical challenges, such as:

Protecting privacy and consent of individuals whose data is used or shared by AI systems. AI systems should respect the confidentiality and autonomy of individuals and obtain their informed consent before collecting or disclosing their personal information.

Ensuring accuracy and fairness of their predictions and avoiding biases or errors that could harm individuals or groups. AI systems should ensure accuracy and fairness of their predictions and avoid biases or errors that could harm individuals or groups.

Balancing beneficence and non-maleficence of individuals who may not want to receive help or disclose their suicidal thoughts. AI systems should respect their wishes and preferences, but also consider their best interests and safety.

How To Access Ai And Ml For Suicide Prevention

If you are interested in accessing AI and ML for suicide prevention, here are some ways you can do so:

If you are a veteran or know someone who is, you can check out ClearForce or REACH VET for more information on how they can help you or your loved one.

If you are feeling suicidal or know someone who is, you can text CRISIS to 741741 for free, confidential crisis counseling from the Crisis Text Line. You can also call the National Suicide Prevention Lifeline at 1-800-273-8255 or the Trevor Project at 1-866-488-7386.

If you are a researcher or a clinician interested in using AI and ML for suicide prevention, you can explore some of the resources available from the National Action Alliance for Suicide Prevention, such as their Artificial Intelligence/Machine Learning Prioritized Research Agenda.

AI and ML for suicide prevention are promising technologies that can save lives by predicting suicide risk and facilitating timely interventions. However, they also require careful ethical considerations and human oversight to ensure their responsible and beneficial use.

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