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CHIPS Articles: Understanding Complex Real-World Phenomena with AI

Understanding Complex Real-World Phenomena with AI
By CHIPS Magazine - January 7, 2019
Rapid comprehension of complex world events is critical to understanding their impact on national security efforts. Significant changes in the natural world or human society can upend global or regional stability on their own, or as part of a causal chain that sparks broader impact. Many events are not simple isolated occurrences but a coming together of complex phenomena – from actors to timelines. “The growing volume of unstructured, multimedia information available, however, hampers uncovering and understanding these events and their underlying elements,” according to the Defense Advanced Projects Agency.

“The process of uncovering relevant connections across mountains of information and the static elements that they underlie requires temporal information and event patterns, which can be difficult to capture at scale with currently available tools and systems,” said Dr. Boyan Onyshkevych, a program manager in DARPA’s Information Innovation Office (I2O).

The use of schemas to help draw correlations across information isn’t a new concept. First defined by cognitive scientist Jean Piaget in 1923, schemas are units of knowledge that humans reference to make sense of events by organizing them into commonly occurring narrative structures, DARPA explained. For example, mapping the process of making coffee can include an electric coffee maker, measuring and grinding coffee beans, using a coffee filter and measuring a sufficient amount of water to produce a topnotch pot of hot coffee.

To help uncover complex events found in multimedia information and bring them to the attention of system users, DARPA created the Knowledge-directed Artificial Intelligence Reasoning Over Schemas (KAIROS) program. KAIROS aims to create a schema-based AI capability to enable contextual and temporal reasoning about complex real-world events to generate actionable understanding of these events and predict how they will unfold. The program looks to develop a semi-automated system capable of identifying and drawing correlations between seemingly unrelated events or data, helping to inform or create broad narratives about the world around us, DARPA explained.

KAIROS’ research objectives will be approached in two stages. DARPA said the first stage will focus on creating schemas from large volumes of data by detecting, classifying and clustering sub-events based on linguistic inference and common sense reasoning. Researchers taking on this challenge will apply generalization, composition and specialization processes to help design schemas that describe both simple and complex events, sequence multiple schemas together to understand key contextual elements like roles and timelines, and apply domain-specific knowledge to tailor the analysis for a particular need.

The second stage of the program will focus on applying the library of schemas created during stage one to multimedia, multilingual information to reveal and extract complex events. This stage will require identifying events and entities, as well as relationships among them to help construct and extend a knowledge base.

DARPA will hold a Proposers Day on January 9, 2019 from 10:00am to 2:30pm (EST) at the Holiday Inn at Ballston, 4610 N. Fairfax Drive, Arlington, Virginia 22203 to provide more information about KAIROS and answer questions from potential proposers. For details of the event, including registration requirements, visit https://www.schafertmd.com/darpa/i2o/KAIROS/pd/.

A Broad Agency Announcement that fully describes the program structure and objectives can be found here.

To help uncover complex events found in multimedia information and bring them to the attention of system users, DARPA created the Knowledge-directed Artificial Intelligence Reasoning Over Schemas (KAIROS) program. DARPA image
To help uncover complex events found in multimedia information and bring them to the attention of system users, DARPA created the Knowledge-directed Artificial Intelligence Reasoning Over Schemas (KAIROS) program. DARPA image

This image outlines the two stages of the KAIROS program. The first stage will focus on creating a library of schemas from large volumes of data by detecting, classifying and clustering sub-events based on linguistic inference and common sense reasoning. The second stage will apply those schemas to new information to uncover and extract complex events, as well as relationships among them, to help construct and extend a knowledge base. DARPA image
This image outlines the two stages of the KAIROS program. The first stage will focus on creating a library of schemas from large volumes of data by detecting, classifying and clustering sub-events based on linguistic inference and common sense reasoning. The second stage will apply those schemas to new information to uncover and extract complex events, as well as relationships among them, to help construct and extend a knowledge base. DARPA image
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