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Bureau of Global Public Affairs (GPA) CLIPSLAB GPA’s production media collection and analysis system that pulls data from half a dozen different open and commercial media clips services to give an up-to-date global picture of media coverage around the world.
Bureau of Global Public Affairs (GPA) MISSION PRESS DIGEST A prototype system that collects and analyzes the daily media clips reports from about 70 different Embassy Public Affairs Sections.
Bureau of Global Public Affairs (GPA) DIGITAL COMMUNICATIONS DATABASE GPA’s production system for collecting, analyzing, and summarizing the global digital content footprint of the Department.
Bureau of Global Public Affairs (GPA) FACEBOOK AD TEST OPTIMIZATION SYSTEM GPA’s production system for testing potential messages at scale across segmented foreign sub-audiences to determine effective outreach to target audiences.
Bureau of Global Public Affairs (GPA) GLOBAL AUDIENCE SEGMENTATION FRAMEWORK GPA’s prototype framework for predicting how content or messages designed for one audience some place in the world will resonate with other audiences outside the United States.
Bureau of Global Public Affairs (GPA) MACHINE-LEARNING ASSISTED MEASUREMENT AND EVALUATION OF PUBLIC OUTREACH A high-performing classifier capable of measuring the level of six different emotions that a text evokes, including time-series analysis, to help evaluate historical messages and predict successful future public messaging.
Bureau of Global Public Affairs (GPA) GPA TOOLS AND GPAIX AI-enabled analysis package for automating public outreach analysis.
Bureau of Political-Military Affairs (PM) NLP TO PULL KEY INFORMATION FROM UNSTRUCTURED TEXT Use natural language processing to extract information from document text to help summarize and allow for analysis more efficiently than manual methods.
Bureau of Political-Military Affairs (PM) K-MEANS CLUSTERING INTO TIERS Cluster countries into tiers based on data collected from open source and Bureau data using k-means clustering.
Global Engagement Center (GEC) DISINFORMATION TOPIC MODELING Text clustering and topic modeling of documents and social media to determine possible disinformation subjects and topics.
Global Engagement Center (GEC) DEEPFAKE DETECTOR Deep learning model that takes in an image containing a person’s face and classifies the image as either being real (contains a real person’s face) or fake (synthetically generated face, a deepfake often created using Generative Adversarial Networks) to predict disinformation activities.
Global Engagement Center (GEC) TEXT SIMILARITY DETECTION Tool to identify different texts that are identical or nearly identical by calculating cosine similarity between each pair of texts. Texts are then grouped if they share high cosine similarity and then available for analysts to review further.
Global Engagement Center (GEC) IMAGE CLUSTERING FOR DISINFORMATION DETECTION AI solutions and processes to identify similar images in order to analyze how images are used to spread and build traction with disinformation narratives.
Global Engagement Center (GEC) LOUVAIN COMMUNITY DETECTION Uses social network analysis to cluster nodes together into “communities” to detect clusters of accounts possibly spreading disinformation.
Office of U.S. Foreign Assistance Resources (F) NLP FOR FOREIGN ASSISTANCE APPROPRIATIONS ANALYSIS Natural language processing application to automate and streamline the extraction of earmarks and directives from the annual appropriations bill to facilitate the Department’s adherence to congressional direction.
Office of Management Strategy and Solutions (M/SS) DEPARTMENT CABLES ANALYTICS Natural language processing analysis of Department cables reporting to inform multiple areas of Department policy and operations.
CSO Automated Burning Detection The Village Monitoring System program uses AI and machine learning to conduct daily scans of moderate resolution commercial satellite imagery to identify anomalies using the near-infrared band.
CSO Automated Damage Assessments The Conflict Observatory program uses AI and machine learning on moderate and high-resolution commercial satellite imagery to document a variety of war crimes and other abuses in Ukraine, including automated damage assessments of a variety of buildings, including critical infrastructure, hospitals, schools, crop storage facilities.

U.S. Department of State

The Lessons of 1989: Freedom and Our Future