Getting on With It: Shaping an AI Eco System for High-End Operational Platforms
In a new book by George Galdorisi and Sam Tangredi, they focus on the coming impact of artificial intelligence on warfare. The book is entitled Algorithms of Armageddon which recognizes how a general scientific fiction quality to AI has come to dominate the public mind and those of many timid decision makers.
The subtitle is the impact of artificial intelligence on future wars which is to suggest this is a book about future possibilities. But it isn’t.
The future has already arrived. It is just a question of whether you want to leverage what we can do or regulate against future science fiction threats from machines like a 1950s sci fi movie made in Japan.
The book provides a first-rate treatment of the issues revolving around AI and the military but I want to emphasize two core points, one they make in detail in the book and one which is there but as a subordinate theme.
The first is that the United States and its allies are not calling the shots in the AI dynamic. Commercial sectors are dominant and adversaries like China and Russia are prioritizing it without regard to Western debates about the ethics of AI. It is not simply a project development race: it is a use race and here the U.S. military is certainly not leading the way.
The Ukrainians have made more use of maritime autonomous systems than the U.S. Navy. My latest book on The Coming of Maritime Autonomous Systems focuses on how the extant systems can and should be used now.
In a recent piece I wrote:
The threats to maritime security in shipping in the Gulf and the littoral regions including the Red Sea are significant and deadly. There is a baseline interest the nations who ship through these waters have in terms of maintaining maritime security. And the Houthi attacks only underscore the need for a comprehensive international monitoring and defense capability to be put in place for the long term.
Fifth Fleet is uniquely positioned to lead a way forward. It is double hatted as a CENTCOM component and as command of the Combined Maritime Forces headquartered in Bahrain.
Fifth Fleet has also has led the U.S. Navy’s efforts in working maritime autonomous systems through Task Force 59. And in those exercises, maritime autonomous systems have successfully contributed not only ISR payloads but have been able to test the use of weapons launched from a MARTAC USV.
It is now prime time to establish an ISR USV enabled grid in the region which the Combined Maritime Forces command can leverage to enforce maritime security operations against threats to shipping. The command can use the unmanned platforms to deploy a variety of ISR payloads contributed by the member nations to create a common ISR data space which can leverage the kinds of actions deemed necessary and appropriate.
Putting high value U.S. Navy manned assets in harm’s way makes absolutely no sense. The future is now not in some distant force redesign future.
The future is now and particularly because these are software enabled AI systems whose use drives the question of code rewriting.
And that gets at the second issue.
I have spent two decades working on the issues of software enabled air platforms, notably with the USMC: Ospreys, F-35s and CH-53Ks. These software rich programs generate significant data concerning their operations or in the case of the F-35 significant ISR and C2 information for other platforms working together.
To get best use out of these systems, shaping an AI eco system to manage the data to identify findings for action is critical. If the U..S and its allies are to get best use out of the most advanced fighter flying today, where is the AI eco system to manage the data flow from the F-35 global enterprise for the coalition force?
And by the way, how do you think the flying machines pass information to each other?
If we are to prevail leverging the assets we ALREADY have, the future better be now when it comes to AI ecosystem development and operation.
In the book they provide a case study of how this could be done with the Navy’s Triton, P-8 and related systems. Instead of stove-piped reading of data, how about creating an interactive AI enabled system managing the data pooled from these systems?
The authors identify the opportunity as follows:
While there are many examples that we could propose, one target of opportunity that seems evident in the fourth of the building blocks described above is advanced human-machine combat teaming. This consists of cooperative operations between humans and unmanned systems.
Two potential examples are the operation of the Navy’s P-8A Poseidon with an MQ-4C Triton and the MH-60S Knighthawk aircraft with an MQ-8C Fire Scout. The fact that these systems are identified as leading candidates for manned-unmanned teaming in the DoD strategy would lead one to assume that significant effort has been made to apply MUMT.
However, these air assets currently operate in a manner that does not begin to approach manned-unmanned teaming. The MQ-4C Triton and MQ-8C Fire Scout are unmanned aerial vehicles that are currently in operation and forward-deployed in key areas around the globe but are not yet “loyal wingmen” to their manned counterparts.
They then characterize the situation for Triton now and what it could be with the appropriate AI enabled ecosystem working with the combat cluster with which it is teamed:
Prior to Triton’s launch, the commander can determine the acceptable level of risk of communications intercept, as well as the danger of giving away the presence of the strike group. Armed with this commander’s intent, and using big data, artificial intelligence, and machine learning, the Triton can assess the electronic environment, select from multiple communications paths, and determine which path offers the least vulnerability to intercept.
If the Triton determines that this vulnerability is too high, it can fly back toward the flagship and communicate via line-of-sight ultra-high frequency.
Given the size and growth potential of the Triton, it could even carry a smaller UAS and launch it back toward the force to deliver this surveillance information. Aboard the flagship, the commander must make sense of the data his sensors have collected and then make a number of time-critical decisions.
Should he continue forward, wait, or retreat?
Should he scout directly ahead or in a different direction?
Should he call on other forces, or are his organic assets sufficient to successfully complete the mission without undue risk to his forces?
This is where big data, artificial intelligence, and machine learning can contribute to helping the commander make critical decisions by processing the data it collects onboard the Triton rather than sending unprocessed terabytes of raw data down the link.
They go on to lay out how this could be done NOW.
And that is the point: it is not about the future of warfare it is about prevailing today in a multi-polar authoritarian world of states and movements with significant military capability.
If we continue to simply plan for new platforms and to someday introduce AI, we will have lost for this generation our ability to defend our way of life.