Why the Department of Defense Should Create an AI Red Team

What is adversarial machine learning (AML)? AML is the purposeful manipulation of data or code to cause a machine learning (ML) algorithm to misfunction or present false predictions. A popular example of AML is from a team at Google that carried out an experiment on GoogLeNet, a convolutional neural network architecture that won the ImageNet Large Scale Visual Recognition Challenge in 2014. Adding noise to an image of a panda and digitally changing its characteristic led the program to more highly predict that the image was a gibbon. This type of manipulation is relatively easy to execute with just a few bits of code inserted into the original algorithm.

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AF DCGS Next Generation: Transformation for Great Power Competition

Abstract: The AF DCGS is in the midst of the most significant transformation it has seen since its inception in the mid-1990s. Primarily driven by the need to find a way to more efficiently process the glut of data now available to the intelligence community, the AF DCGS transformation to the problem-centric model of analysis is already paying major dividends in the Enterprise’s ability to provide enhanced intelligence to its customers. This article discusses the transformation and describes in detail how the AF DCGS is now oriented to prepare the air component for great power competition.

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The Role of the Human in Systems of Systems: Example of the French Future Combat Air System

France is committed to design a Future Combat Air System (FCAS) relying on an architecture of networks, meshing inhabited and unmanned platforms within a System of Systems and fitting fully into the Man-Unmanned Aircraft teaming paradigm. Artificial intelligence (AI), Big Data Analytics, cloud computing and cyber-security are the four digital technologies at the heart of the digital transformation of our Air Force. All of this raises the question of the role of the Human in such a complex System of Systems.

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Intelligence for Quantum Age Learning: Data Visualization & Inquiry of the Information Environment

Data visualization solutions for maintaining a learning advantage in a quantum age of technological & information expansion.

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How the Air Force Should Test Autonomous Vehicles Part 2

Part 2 of the conclusion to a series on training and developing autonomous wingmen for future aerial combat.

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How the Air Force should Test Autonomous Vehicles Part 1 of 2

In part 1 of a 2-part series conclusion, Nick Helms discusses foundations and processes for testing and training autonomous air vehicles.

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Duelling Algorithms: Using Artificial Intelligence in Warfighting

Examining the dichotomy of AI employment in warfare-“Do things better?” or “Do better things?”-and other implementation challenges.

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