Knowledge-Integrated Informed AI for National Security
Abstract
The state of artificial intelligence technology has a rich history that dates back decades and includes two fall-outs before the explosive resurgence of today, which is credited largely to data driven techniques. While AI technology has and continues to become increasingly mainstream with impact across domains and industries, its not without several drawbacks, weaknesses, and potential to cause undesired effects. AI techniques are numerous with many approaches and variants, but they can be classified simply based on the degree of knowledge they capture and how much data they require; two broad categories emerge as prominent across AI to date: (1) techniques that are primarily, and often solely, data-driven while leveraging little to no knowledge and (2) techniques that primarily leverage knowledge and depend less on data. Now, a third category is starting to emerge that leverages both data and knowledge, that some refer to as informed AI. This third category can be a game changer within the national security domain where there is ample scientific and domain-specific knowledge that stands ready to be leveraged, and where purely data-driven AI can lead to serious unwanted consequences.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jan 27, 2022
- Accession Number
- AD1159436
Entities
People
- Anu K. Myne
- Kevin Leahy
- Ryan J. Soklaski
Organizations
- Massachusetts Institute of Technology