HAYSTAC seeks to proactively monitor and alert citizens
One AI-powered project that Marsh poked fun at is the aptly named HAYSTACo Signal of Hidden Activity and Characterization of Anomalies in the Trajectory.
Its goal is to develop “capabilities that produce large-scale microsimulations so you can discover human motion and create AI reasoning engines capable of identifying abnormal motion trajectories and generating normal trajectories,” Marsh told the symposium audience. In simpler terms, given the explosion of data collected from Internet of Things devices and smart city technology, there is potential to better understand normal and abnormal patterns of human movement. With the help of AI, the government could develop more effective and proactive public safety systems and processes.
“As we go forward, how can you spot things that are happening so we can figure it out ahead of time and create early warning?” Marsh said.
This could be useful during a natural disaster or terrorist attack, for example, when most people flee areas as first responders approach.
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“Disruptions to highways, bridges, or critical infrastructure elements create traffic and cause people to change routes,” according to an IARPA Press release. “An increase in civil unrest changes the pattern of daily life, as health and basic needs are prioritized over work and recreation. Disruptive events themselves are often not directly observable, but understanding surrounding motion anomalies can inform timely response and analysis.”
HAYSTAC is in the Wide period of agency announcements until July 1, during which IARPA solicits research proposals from private sector companies. The program is expected to be a four year effortstarting in October and ending in March 2026.
“While bringing HAYSTAC to fruition will be a multi-year process, once it is complete, we will have reframed how we view activity around the world,” HAYSTAC program manager Jack Cooper said in the press release. “And it won’t be a static concept of where things are on a map, but a dynamic one based on how they move and what’s out of the ordinary.”
HIATUS helps identify and combat disinformation campaigns
While AI is putting itself to work to improve physical security, it is also exploring how to better classify and understand intangible things, such as human expression. by IARPA HIATUS (Human Interpretable Attribution of Text Using Underlying Structure) seeks to “develop new artificial intelligence systems usable by humans to attribute authorship and protect author privacy through the identification and exploitation of explainable linguistics”, helping to solve a problem for intelligence agencies, he said.
Timothy McKinnon, the IARPA program manager leading this work, recently told Nextgov, “Just think if you had 100 different people and asked them to describe something simple, like how to open a door, in two sentences or one sentence. You’ll probably get about 100 different answers, right? And each person has their own idiosyncrasies as an author that are potentially used by author attribution systems.”
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The program aims to identify stylistic features, such as syntax, that can help identify who wrote a given piece of text, much like a fingerprint, McKinnon said.
“The technology could identify that fingerprint against a corpus of other documents and compare them if they are from the same author,” he said. “On the privacy side, the technology would discover ways that the text could be modified, so that it no longer looks like a person’s handwriting.”
The HIATUS effort has the potential to be a game changer in tracking disinformation campaigns and helping combat human trafficking and other malicious activity on online text forums, McKinnon told the outlet.