DARPA In the Moment


On July 6, 2023, Parallax Advanced Research was awarded a $4.067 million grant from the Defense Advanced Research Projects Agency (DARPA) for the In the Moment (ITM) initiative. This research aims to develop trustworthy artificial intelligence (AI) systems capable of making complex decisions in high-stakes scenarios where traditional solutions are not readily applicable. Parallax, in collaboration with Drexel University and Knexus Research Corporation, is focused on advancing human-aligned decision-making technologies for challenging environments, specifically in medical triage and mass casualty care.

Project Timeline


November 18, 2022:

Launch of DRIVE Consortium and opening of membership applications.


Phase 1:

Development of algorithmic decision-makers that align with human decision-making variability.


Phase 2:

Enhancement of the AI system to align with specific individual decision-makers.


Future:

Integration of the Trustworthy Algorithmic Delegate (TAD) into battlefield medical care and small-unit triage situations.

Our Impact

  • “Doing research for DARPA is one of several ways to achieve our goal of advancing the nation's innovation advantage. DARPA is the right space for us to apply our research and innovation potential.” – Dr. Viktoria Greanya, Chief Scientist at Parallax
  • The TAD system is anticipated to significantly enhance decision-making processes in emergency medical care, providing crucial support in emergency medical situations, potentially transforming how care is administered in both battlefield and civilian contexts.

Core Capabilities

  • The ITM award enables Parallax to explore human-aligned decision-making in medical emergencies, focusing on AI systems that adapt to various decision-makers and enhance trust and reliability in high-pressure environments.  
  • Advanced research into AI and machine learning technologies that improve decision-making processes under resource constraints and time pressure.  
  • Creation of decision-support systems that enhance the reliability and trustworthiness of AI in critical decision-making roles.


Key Contributors