Language Models for Veteran Suicide Prevention (LM4VSP)
ID: HR0011SB20254-02Type: BOTH
Overview

Topic

Language Models for Veteran Suicide Prevention (LM4VSP)

Agency

Agency: DODBranch: DARPA

Program

Type: SBIRPhase: BOTH

Topic Link

https://www.dodsbirsttr.mil/topics-app/

Additional Information

https://www.dodsbirsttr.mil/topics-app/
Timeline
    Description

    The Department of Defense, through DARPA, is seeking proposals for the Language Models for Veteran Suicide Prevention (LM4VSP) initiative, which aims to develop a conversational AI clinical co-pilot to assist mental health care professionals in supporting veterans at risk of suicide. The project focuses on leveraging advancements in natural language processing to provide continuous assistance, particularly during critical times when traditional support may be limited, addressing the pressing public health crisis of veteran suicide. This initiative is structured in two phases: Phase I involves feasibility studies and proof-of-concept development, while Phase II aims to create a prototype capable of generating accurate responses and evaluating its efficacy. The solicitation is set to open on December 4, 2024, with proposals due by January 8, 2025, and further details can be found at the provided source link.

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    The Language Models for Veteran Suicide Prevention (LM4VSP) initiative aims to develop a conversational AI clinical co-pilot to support mental health care professionals in assisting veterans at risk of suicide. The project responds to alarming statistics highlighting the stark reality of veteran suicide, stressing the importance of addressing social factors like isolation, trauma, and access to healthcare. LM4VSP seeks to leverage advances in natural language processing, utilizing language models to enable mental health providers to deliver continuous assistance, especially during critical times when traditional support may be scarce. The initiative comprises two phases: Phase I focuses on feasibility studies and proof-of-concept development, requiring collaboration with mental health experts to identify relevant data, response strategies, and high-risk categories for intervention. Phase II shifts towards creating a prototype capable of generating accurate responses and evaluating its efficacy against existing models. Additionally, potential applications extend into both Department of Defense and commercial sectors. The project emphasizes transitioning the developed technology into practical solutions to enhance mental health support for veterans and their families, showcasing a concerted effort by the government to utilize AI in public health crises.
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