This is a world where AI is so seamless and ubiquitous that it factors into everything from rifle sights to logistical management. It is a future where every soldier is a node covered in sensors, and every access point to that network is under constant threat by enemies moving invisibly through the very parts of the electromagnetic spectrum that make networks possible. It is a future where weapons can, on their own, interpret the world, position themselves within it, plot a course of action, and then, in the most extreme situations, follow through.

It is a world of rich battlefield data, hyperfast machines and vulnerable humans. And it is discussed as an inevitability.

“We need AI for the speed at which we believe we will fight future wars,” said Brig. Gen. Matthew Easley, director of the Army AI Task Force. Easley is one of a handful of people with an outsized role shaping how militaries adopt AI.

The past of data future

Before the Army can build the AI it needs, the service needs to collect the data that will fuel and train its machines. In the shortest terms, that means the task force’s first areas of focus will include preventative maintenance and talent management, where the Army is gathering a wealth of data. Processing what is already collected has the potential for an outsized impact on the logistics and business side of administering the Army.

For AI to matter in combat, the Army will need to build a database of what sensor-readable events happen in battle, and then refine that data to ultimately provide useful information to soldiers. And to get there means turning every member of the infantry into a sensor.

“Soldier lethality is fielding the Integrated Visual Augmentation Systems, or our IVAS soldier goggles that each of our infantry soldiers will be wearing,” Easley said. “In the short term, we are looking at fielding nearly 200,000 of these systems.”

The IVAS is built on top of Microsoft’s HoloLens augmented reality tool. That the equipment has been explicitly tied to not just military use, but military use in combat, led to protests from workers at Microsoft who objected to the product of their labor being used with “intent to harm.”

And with IVAS in place, Easley imagines a scenario where IVAS sensors plot fields of fire for every soldier in a squad, up through a platoon and beyond.

“By the time it gets to [a] battalion commander,” Easley said, “they’re able to say where their dead zones are in front of [the] defensive line. They’ll know what their soldiers can touch right now, and they’ll know what they can’t touch right now.”

Easley compared the overall effect to the data collection done by commercial companies through the sensors on smartphones — devices that build detailed pictures of the individuals carrying them.

Fitting sensors to infantry, vehicles or drones can help build the data the Army needs to power AI. Another path involves creating synthetic data. While the Army has largely fought the same type of enemy for the past 18 years, preparing for the future means designing systems that can handle the full range of vehicles and weapons of a professional military.

With insurgents unlikely to field tanks or attack helicopters at scale anytime soon, the Army may need to generate synthetic data to train an AI to fight a near-peer adversary.

Faster, stronger, better, more autonomous

“I want to proof the threat,” said Bruce Jette, the Army’s assistant secretary for acquisition, logistics and technology, while speaking at a C4ISRNET event on artificial intelligence at AUSA. Jette then set out the kind of capability he wants AI to provide, starting from the perspective of a tank turret.

“Flip the switch on, it hunts for targets, it finds targets, it classifies targets. That’s a Volkswagen, that’s a BTR [Russian-origin armored personnel carrier], that’s a BMP [Russian-origin infantry fighting vehicle]. It determines whether a target is a threat or not. The Volkswagen’s not a threat, the BTR is probably a threat, the BMP is a threat, and it prioritizes them. BMP is probably more dangerous than the BTR. And then it classifies which one’s [an] imminent threat, one’s pointing towards you, one’s driving away, those type of things, and then it does a firing solution to the target, which one’s going to fire first, then it has all the firing solutions and shoots it.”

Enter Jette’s ideal end state for AI: an armed machine that senses the world around it, interprets that data, plots a course of action and then fires a weapon. It is the observe–orient–decide–act cycle without a human in the loop, and Jette was explicit on that point.

“Did you hear me anywhere in there say ‘man in the loop?,’ ” Jette said. “Of course, I have people throwing their hands up about ‘Terminator,’ I did this for a reason. If you break it into little pieces and then try to assemble it, there’ll be 1,000 interface problems. I tell you to do it once through, and then I put the interface in for any safety concerns we want. It’s much more fluid.”

In Jette’s end state, the AI of the vehicle is designed to be fully lethal and autonomous, and then the safety features are added in later — a precautionary stop, a deliberate calming intrusion into an already complete system.

Jette was light on the details of how to get from the present to the thinking tanks of tomorrow’s wars. But it is a process that will, by necessity, involve buy-in and collaboration with industry to deliver the tools, whether it comes as a gestalt whole or in a thousand little pieces.

Learning machines, fighting machines

Autonomous kill decisions, with or without humans in the loop, are a matter of still-debated international legal and ethical concern. That likely means that Jette’s thought experiment tank is part of a more distant future than a host of other weapons. The existence of small and cheap battlefield robots, however, means that we are likely to see AI used against drones in the more immediate future.

Before robots fight people, robots will fight robots. Before that, AI will mostly manage spreadsheets and maintenance requests.

“There are systems now that can take down a UAS pretty quickly with little collateral damage,” Easley said. “I can imagine those systems becoming much more autonomous in the short term than many of our other systems.”

Autonomous systems designed to counter other fast, autonomous systems without people on board are already in place. The aptly named Counter Rocket, Artillery, and Mortar, or C-RAM, systems use autonomous sensing and reaction to specifically destroy projectiles pointed at humans. Likewise, autonomy exists on the battlefield in systems like loitering munitions designed to search for and then destroy anti-air radar defense systems.

Iterating AI will mean finding a new space of what is acceptable risk for machines sent into combat.

“From a testing and evaluation perspective, we want a risk knob. I want the commander to be able to go maximum risk, minimum risk,” said Brian Sadler, a senior research scientist at the Army Research Laboratory. “When he’s willing to take that risk, that’s OK. He knows his current rules of engagement, he knows where he’s operating, he knows if he uses some platforms; he’s willing to make that sacrifice.

In his work at the Vehicle Technology Directorate of the Army Combat Capabilities Development Command, Sadler is tasked with catching up the science of AI to the engineered reality of it. It is not enough to get AI to work; it has to be understood.

“If people don’t trust AI, people won’t use it,” Tim Barton, chief technology officer at Leidos, said at the C4ISRNET event.

Building that trust is an effort that industry and the Army have to tackle from multiple angles. Part of it involves iterating the design of AI tools with the people in the field who will use them so that the information analyzed and the product produced has immediate value.

“AI should be introduced to soldiers as an augmentation system,” said Lt. Col. Chris Lowrance, a project manager in the Army’s AI Task Force. “The system needs to enhance capability and reduce cognitive load.”

Away from but adjacent to the battlefield, Sadler pointed to tools that can provide immediate value even as they’re iterated upon.

“If it’s not a safety of life mission, I can interact with that analyst continuously over time in some kind of spiral development cycle for that product, which I can slowly whittle down to something better and better, and even in the get-go we’re helping the analyst quite a bit,” Sadler said.

“I think Project Maven is the poster child for this,” he added, referring to the Google-started tool that identifies objects from drone footage.

Project Maven is the rare intelligence tool that found its way into the public consciousness. It was built on top of open-source tools, and workers at Google circulated a petition objecting to the role of their labor in creating something that could “lead to potentially lethal outcomes.” The worker protest led the Silicon Valley giant to outline new principles for its own use of AI.

Ultimately, the experience of engineering AI is vastly different than the end user, where AI fades seamlessly into the background, becoming just an ambient part of modern life.

If the future plays out as described, AI will move from a hyped feature, to a normal component of software, to an invisible processor that runs all the time.

“Once we succeed in AI,” said Danielle Tarraf, a senior information scientist at the think tank Rand, “it will become invisible like control systems, noticed only in failure.”

“At approximately 10 a.m. local time, the amphibious ship USS Boxer was in international waters conducting a planned inbound transit of the Strait of Hormuz,” read the statement from Jonathan Hoffman, the chief Pentagon spokesperson. “A fixed wing unmanned aerial system (UAS) approached [USS] Boxer and closed within a threatening range. The ship took defensive action against the UAS to ensure the safety of the ship and its crew”

The Pentagon’s statement differs in language from the wording used by President Donald Trump, who claimed that “the drone was immediately destroyed” after receiving multiple calls to stand down. According to CNN, U.S. defense officials claim that the drone was disabled not by bullets or missiles (“kinetics,” in the jargon), but rather by jamming.

Specifically, it was almost certainly jamming via MRZR LMADIS, or a Polaris MRZR vehicle sporting a Light Marine Air Defense Integrated System. While a Corps official said as early as May that the deployment of the system to the Middle East was winding down, observers online noted that a MRZR LMADIS system was visible on the deck of the USS Boxer, an amphibious assault ship, for its transit through the Strait of Hormuz — a presence revealed in pictures uploaded earlier that day.

The incident is just 28 days after Iran shot down a Global Hawk over the Strait of Hormuz. While the drone jammed by the Boxer has yet to be identified, Iran has drone bases in the area (which is, again, a narrow body of water that borders Iran, and over one side of which Iran claims sovereignty). Non-state actors have also operated drones in the surrounding area, sometimes supplied by regional powers. The downing of the Global Hawk almost risked escalation, though the uncrewed nature of drones versus the certainty of human casualties in the event of a retaliation appears to have calmed tensions.

Instead, the recent exchange of attacks on drones hearkens back to an earlier era of tension in the Strait, invoking the attacks on commercial vessels during the Iran-Iraq war which ultimately involved US naval patrols and is recorded in history as the Tanker War. Jamming drones, in theory, poses less of a risk to other commercial or otherwise peopled aircraft, but the likely consequence of the exchange of drone destruction in the summer of 2019 is that commercial aircraft will steer clear of the area. After all, the greatest tragedy of the Tanker War involved a U.S. cruiser mistaking a civilian Iranian airliner for an attacking jet fighter, leading to the deaths of 290 people.

It is also worth noting that the immediate answer to a drone threat to ships appears to be simply parking a ground vehicle carrying a counterdrone system on the deck. The counterdrone field is full of possible solutions, but most have focused on either facilities or dismounted patrol protection, looking at handheld devices or larger installations at fixed points at bases. There is likely an underserved market in counterdrone solutions for ships, especially aimed at stopping mid- to low-end fixed-wing craft.

Modern life is millennia removed from proto-ethical debates over the dangers of collaborating on hunting technology with people who may someday turn it to violence, but dual-use tools are at the center of a major inter- and intra-national debate. The U.S.-China Economic and Security Review Commission held a hearing June 7 about China and technology, specifically the ways in which developments in the civilian sector could be exploited and weaponized by China’s military.

“China has been hyped as an AI superpower poised to overtake the U.S. in the strategic technology domain of AI,” said Jeffrey Ding, China lead for the Center for the Governance of AI, Future of Humanity Institute, University of Oxford; D.Phil. Candidate, University of Oxford.

“Much of the research supporting this claim suffers from the ‘AI abstraction problem,’” Ding continued, “the concept of AI, which encompasses anything from fuzzy mathematics to drone swarms, becomes so slippery that it is no longer analytically coherent or useful.”

Into the fuzziness of that debate around AI, the commissioners probed and the witnesses testified, occasionally going into the weeds of specific data but largely moving back to questions of intent and capability. The big questions underlying the hearing were these: can China leapfrog development of AI to create useful military tools, and can the United States marshal an industrial policy to maintain a lead in AI without the same kind of integrated state apparatus that China has? Also, what will China do with AI once it develops it?

The degree to which China can expand on and leapfrog U.S. AI development hinges on everything from the respective countries immigration policies, a willingness of multinational corporations to share research, direct and passive funding, and the extent to which things like counter-intelligence operations can yield results or chill collaboration. It also depends on what purpose, exactly, the AI is being trained to do.

“AI appeals to the [People’s Liberation Army] in part because it has fewer legacy systems,” said Elsa Kania, adjunct senior fellow, Technology and National Security Program at the Center for a New American Security and research fellow at CSET. Building systems for the first time with AI in mind is a different and distinct proposition from adapting existing systems to draw on AI tools.

Looking for a hard metric in the recent past, Ding cited an unpublished manuscript by Jon Schmid, a doctoral candidate at Georgia Tech, that looked at military patents to see what was being developed.

“It’s not a perfect indicator because a lot of military hardware isn’t going to be patented open source,” said Ding, “but a crucial caveat I’ll add to that is a lot of these advanced military systems source components that are found in patents, so it’s a good indicator.”

Looking specifically at the abstracts of patents for military hardware or hardware components that cited autonomous or unmanned, the research found that from 2003 to 2015 the United States had a lead in cumulative military patents seven times that of China.

“We can think of AI as next wave of software improvements,” suggested Helen Toner, director of strategy at Georgetown University’s Center for Security and Emerging Technology. Without a clear inflection point for when AI transitions from capable software to a unique capability, many of the changes will in nature and implementation resemble software upgrades.

AI can be trickier to quantify, because while end-products may make note of features, like autonomy, that are enabled by AI, AI itself is a process done to data and doesn’t always transfer easily or at all to other applications. Also, processes are limited to being only as good at the quality of data that goes into them.

“It’s not quite as simple as ‘data is the new oil,’ but the value of data is really application dependent, so we have seen strength in particular applications where massive data is an advantage,” said Kania. “The nature of AI is a general purpose technology that is enhancing and augmenting weapon systems across a vast array of weapon systems, drive dynamics hard to evaluate, make safety and stability.”

Ultimately, what matters most in AI is less about any specific development, and more about how that AI facilities and enables existing choices people were already prepared to make. Multiple members of the U.S.-China Economic and Security Review Commission asked specifically about the role of AI in China’s repressive policy towards the Uighur people of Xinjiang. That specific concern was cited by Sens. Martin Heinrich, D-N.M., and Rob Portman, R-Ohio, in introducing a bill to enhance U.S. funding of AI research.

“The reason Xinjiang is happening is not AI, it is that the government of China is willing to make it happen,” testified Toner, “and therefore our response, if we respond, should condemn or otherwise sanction that action, of which tech is only a small part.”

The extent to which tech is especially responsible for state-led repression was contested by the panel, with Kania testifying that surveillance technologies are at the heart of repression at Xinjiang.

It is hard for the technology sector to, on its own or through U.S. government encouragement, try to change the behavior of a government. There was somewhat more consensus on policy suggestions for companies and government to end relationships building AI tools used for repression in the name of internal security.

Military implications of AI competition are likely downstream from these tangible concerns over AI built for other purposes. An ecosystem built on top of open-source tools and massive collections of data could be rebuilt if major participants stopped collaborating with each other, but it would likely take a national initiative to coordinate such a break. In the meantime, an active Cold War in AI will remain a near future possibility, rather than an immediate course of action.

DARPA, the Department of Defense’s blue-sky agency, launched April 29 a program to use artificial intelligence to best match interventions for individuals. It is called “Teaching AI to Leverage Overlooked Residuals,” or TAILOR.

Specifically, DARPA is looking for submissions about how to use AI for “Human Performance Optimization,” or HPO. Crucially, DARPA is looking for alternatives to one-size-fits-all approaches, because universal recommendations based on group averages can work at cross-purposes to individual need.

“This approach frequently (mis)characterizes individual variance as statistical ‘noise,’ ‘residuals,’ or ‘error,’” reads the solicitation. “The resulting interventions (e.g., diet, physical training regimen, brain stimulation) are at best suboptimal and at worst deleterious for each person.”

Diet, physical training, and brain stimulation aren’t the flashiest parts of the military, but they’re fundamental to how everything else operates. DARPA specifically cites an interest from Special Operations Command’s “Close Combat Lethality Task Force” in getting this optimization right, tailoring interventions to individuals and teams into an advantage.

To get there, DARPA is asking proposers to come up with “third wave AI approaches,” to demonstrate contextual reasoning and transfer learning, meaning a solution is capable of adapting to changed circumstances, environments, and can use related knowledge for abstraction. DARPA also wants teams to move away from traditional AI that trains on large data sets, has opaque processes, and are hard to adapt to new contexts. Proposers will be expected to focus on at least on area of human performance, with DARPA aiming to have a full portfolio of research on physical cognitive, and social performance data.

It’s a lot of technical build-up, but the final outcome is relatively straightforward: after given the data and goal for a specific individual or team, the tool needs to evaluate how much that individual or team would benefit from a given intervention (such as a change in diet or exercise or brain stimulation.) The systems will also be evaluated on how well they can explain or accommodate counterfactuals. Phase II is much the same process, but with datasets from other teams, and with evaluation from subject matter experts in government.

Should the research prove fruitful, the military will be one step closer to specific responses for every individual, a personalized tool that’s general issue.

Formally a “scalable effects net warhead,” the net grenade could finally provide a countermeasure to cheap drones that’s almost as inexpensive as the drones themselves.

Ensnaring a robot in a net is perhaps the opposite of lethality, but here that’s a selling point — stopping the drone means immediately disabling it and possibly doing a forensic investigation on the drone’s innards afterwards. Bullets can stop drones, but it’s a hard task even at sport shooting competitions and in a real-life application bullets still have to fall somewhere, risking injury to friendly forces and bystanders. Anti-air missiles like the Patriot can also intercept drones, but drones can be as cheap as a few hundred dollars and missiles like the Patriot can cost a few million dollars. Both more-kinetic options can ruin the drone’s circuitry, obliterating any useful clues as to who may have launched the drone.

Nets also hold an advantage over directional jammers in that they only have to hit the drone once to work. Directional jammers, while often portable and rifle-sized, have to stay focused on the target drone until the drone is brought down, or else risk the drone being able to receive signals from its remote pilot and detonate or fly away.

Nets are so popular a counterdrone tool that we’ve seen existing net-guns used to stop wildlife re-purposed to catch UAVs, drones carrying nets, drones carrying net-guns, and custom dedicated net-launching bazooka-like weapons. All of these require dedicated training of varying degrees, especially in the case of piloting drones as counterdrone weapons. A net-containing package that fits into a launcher already familiar to soldiers could provide a simpler, easier to adopt way to shoot down drones.

This counterdrone net grenade would open when sensors indicate it is close to a target, and then the net inside the grenade would be launched onto the drone.

“The results of initial testing show that the warhead of this invention can be launched (currently in a 40 mm configuration) and can successfully engage a UAS threat,” reads the patent. “The performance of this invention goes further than any previous system proposed which merely launches a net directly at a UAS.”

In addition to stopping drones, the patent bills the launched nets as useful against boats, boat propellers, moving land vehicles and stationary land vehicles. If a net could conceivably stop it, then a grenade-launched net is a way to make that happen faster.

With cheap drones comes a great opportunity for countering cheap drones. On the battlefield of the future, the answer to drones may just be net-slingers.

Specifically, the parade will feature two ground robots, the Uran-9 combat robot, the Uran-6 mine-clearing robot, and Korsar drones, according to Russian defense minister Sergei Shoigu. As the National Security world again turns its attention to possible conflict with a near-peer competitor, the robots that competitor showcases will have implications beyond simple counter-insurgency curios.

“Unmanned aerial vehicles have seen extensive use in Russian operations. A growing number of unarmed ground vehicles handle de-mining and surveillance missions,” writes Samuel Bendett, a research analyst at the Center for Naval Analyses. Bendett continues, “That’s why Russia’s decision to display these particular unmanned systems is so interesting. Of the three vehicles Shoigu named, only the unarmed Uran-6 has seen actual operational use, most notably in Syria.”

Why display the robots in the parade now, and those robots in particular? Bendett suggests the inclusion of the Uran-9 may be because of its conventional appearance: it looks like a tank in miniature. With a squat body that’s longer than it is wide, a visible set of tracks on each side, and a turret mounting a large gun on top, Uran-9 is as familiar as it is alien, a constant form easing the viewer an acceptance of the robot. Sure, there’s no person inside directing the vehicle, but people roughly know what a tank does.

What does the Uran-9 do? That’s harder to say. Promotional video shows it driving through walls and rings of fire. It is controlled remotely, which implies some degree of human input into how the little robot tank operates, but the degree of that input is unclear. Is the Uran-9 aiming its weapons automatically? Is it selecting targets? Is it tracking targets and then waiting for a human to give the go-ahead to shoot, or is the human monitoring it while the robot makes those decisions on its own?

“The director of the company that makes Uran unmanned ground vehicles recently stated that humans will have final decision on when and how to fire weapons,” Bendett wrote in 2017, “thereby preventing “robots rebelling against operators due to programming errors.”

Autonomy may not be on display in the parade; it is, after all, hard to show code working under the hood, and given the problems unarmed self-driving vehicles have had in the civilian world, safe to bet that Uran-9s on parade will be remotely piloted. But that autonomy could very well be part of the capability suggested, and eventually deployed in the vehicle. When the Uran-9 rolls down the route, it will be a reminder that the questions of autonomous weapon systems, the place of the human in the decision process and the degrees of autonomy, are hardly questions for the Pentagon alone.

A new report published today by the Center for the Study of the Drone at Bard University found that in the president’s new budget request, the Department of Defense is asking for three times as many uncrewed vehicles for 2019 as it did in 2018.

That’s 3,447 new drones, to be exact, but don’t expect the skies to go dark with Reapers anytime soon. Despite the numbers requested, the drone budget itself is up by only 26 percent. The Pentagon isn’t just buying more drones, it’s acquiring a whole range of new systems, for everything from undersea surveillance to cheap scouting quadcopters to lasers designed to shoot down the cheap quadcopters of adversaries. The drone century is only just beginning.

“This is the biggest we’ve seen in years that we’ve tracked it,” said Dan Gettinger. Gettinger is co-director of the Center for the Study of the Drone, and its report on drone spending, published today, tracked everything unmanned in the Pentagon budget, as the center has done since 2013. This year, adding up programs across services, the Center found that the Pentagon is asking for $9.39 billion in drone spending. “We’ve seen budget hover in the 4-6 billion annual range since fiscal year 2013,” Gettinger said.“A budget for just over 9 billion for unmanned systems, that’s a pretty substantial increase.”

That $9.39 billion breaks down into $2.6 billion for the Air Force, $3.7 billion for the Navy and the Marines, $1.7 billion for the Army, and almost $1.3 billion across the rest of the Pentagon.

“This year the Navy has just skyrocketed past the Air Force,” said Gettinger. Part of that is a $982 million request for maritime systems, though last year Congress delivered over $200 million less on sea drones than the Navy asked for. “Congress has taken a dim view of unmanned maritime projects in the past and has cut funding for some of those.“

The rise of the underwater drone

Part of the shift in spending from Air Force to Navy is the nature of the drones purchased. When it comes to the iconic drones of the last administration, long-endurance machines like the MQ-9 Reaper and the RQ-4 Global Hawk, the Air Force is simply buying fewer than it used it, and what units it does buy are mostly replacements for aging or lost models. These legacy systems still dominate the budget: maintaining and operating existing machines still costs a pretty penny. In the margins around those big-ticket items, there’s a quiet shift taking place: a new emphasis on cheap, small drones.

Quadcopters show up in every service except the Air Force, as well as Special Operations Command and the generic overall Pentagon budget. There’s $140,000 to buy 100 quadcopters for CTEF, or the Counter-ISIS Train and Equip Fund. The Navy and Marine Corps is asking for 200 InstantEye quadcopters, likely part of a “quads for squads” program. SOCOM wants 50 quadcopters listed as just “quadcopter,” as well as over 500 NANO VTOL drones (which are likely to be quadcopters) and 160 Micro VTOL drones (also almost certainly quadcopters). And the Army’s asking for 1084 drones as part of the Soldier-Borne Sensor program, which wants to put palm-sized quadcopters at the disposal of infantry. Altogether, that’s over 2,000 quadcopters of various models. Excluding the ones requested by SOCOM, which are grouped together with multiple varieties of larger drones, the Pentagon is asking to spend about $30 million on small 1,400 drones, for about the same price as two MQ-9 Reapers.

“There’s not a lot of quadcopter action in prior budgets,” Gettinger said. “Last year was the first year we saw some substantial movement on that front, with some funding for quadcopters for CTEF, but it was nothing compared to what we see in FY 19.”

Besides putting small drones into the sky, the Pentagon is also looking to spend more on tools to shoot drones down. In this space, the Navy is also looking to fund multiple counter-drone laser projects, but somehow real-life lasers aren’t even the biggest ticket item. The Department of Defense is asking for $1.07 billion on counter-drone tools in this budget, up from $453.9 million last year Much of that increase is in the Army’s “Low-slow-small Integrated Defense System” (LIDS), which appear to be some form of guided missile.

“The military is taking a lot of different approaches to solving counter-drone issue,” Gettinger said. “Some of that involves outfitting existing defense systems with [counter-drone] capability and some of it involves thinking about how UAS threat can evolve in the future.”

Speaking of guided missiles, the Center report notes that the Army and Navy are asking for a combined total of 1,618 Switchblade loitering munitions. Related to both cruise missiles and drones, they don’t quite fit in either category. Gettinger noted that technically the Switchblades are included in the budget for missiles, making them closer to Hellfires than Reapers. Complicating it further, the Navy’s submarine-launched Blackwing drone is based on the Switchblade body, though it’s formally billed as an ISR platform, rather than a weapon.

“There’s new funding for Army combat ground vehicle program,” says Gettinger, “It’s not a huge amount of funding but it’s definitely part of the project that we’re going to keep an eye on in the future. They’re going to field test a system, remotely operated M119 armored personnel carrier.”

Specifically, that’s $40 million under the “Robotic Combat Vehicle Experimental Unit Prototypes project,” which wants to see robots accompany human-containing vehicles into battle.

It’s hard to say how much of this request will make it through Congress. Yet as a statement of where the Pentagon wants to go, it’s an invaluable guide. By piecing together the whole of the drone budget, the Center finds a pivotal moment, where drones are smaller and more numerous and better dispersed, and distributed too among boats and in submarines and driving on the ground and carried in backpacks. Drones are a big part of how every service sees war in the future playing out, and from cheap scouts in the field to elaborate lasers built to shoot down hostile drones, the notion that drone war is a separable part of warfighting can largely be laid to rest. Drones are an evergreen part of war, now.

Begun, the drone wars have.

Paratrooper jumps stick in the popular imagination as a fixture of past war, from a messy, if successful, use as part of D-Day to a messy and less successful attempt in Operation Market Garden, but we’ve seen airborne jumps in the 21st century, with jumps into both Afghanistan and Iraq taking place early in the respective wars, and continuing as a feature of some special operations forces missions.

With parachute jumps continuing right up to the present day, it should then be a little unsurprising that there’s now an app for paratroopers.

But is it an essential download?

Here’s how research firm Draper describes their app for parachutists:

The system operates as a plug-in to a smartphone — the first version is for the Android platform. Parachutists can use the app to see the terrain below them, the location of the jump team around them and the designated landing point. The app can also track the parachutists by sensing the moment they leave the plane. The app automatically switches navigation modes at that point, leaving the parachutist free to focus on maneuvering their parachute rather than adjusting the app.

It is, in a way, a Waze for paratroopers, tracking movement by GPS and noticing the changed states from “sitting in a plane” to “freefall” to “under a parachute.” As designed, it works with the gloves worn by the parachutist, and it can accept new data from the person in charge of the map. The research was funded by the U.S. Army, and will likely find a home there.

Will an app guarantee a future for parachute troops? Military observers and commentators periodically debate if paratroopers are a capability worth keeping, noting the rarity of large-scale jumps since World War II, highlighting the strategic rather than tactical utility of forces jumping from planes rather than carried by helicopter, and decrying the lack of a suitable air-dropped armored vehicle to really live up to airborne’s potential. While an app can’t solve the problem of a lack of armor, it can mitigate one of the greatest risks from air-dropping troops: landing zone dispersal, where a potent fighting force is instead scattered over a vast area, and able to be stopped piecemeal.

If there is a future for the airborne, it is likely a future with apps. The surprise gained is invaluable, provided, of course, that no jogging apps give the jumpers away.

Today, the blog of the Army’s Mad Scientist Laboratory (part of U.S. Army Training and Doctrine Command) is showcasing an entry on how AI will shape the future of the Army itself, down to the electro-mechanical organs of individual soldiers. In his short story “Sine Pari,” senior concept developer Howard R. Simkin of the U.S. Army Special Operations Command imagines a typical day recruiting for Special Operations in the middle of the 21st century.

From “Sine Pari”:

“My uncle was in Special Operations during ‘the Big One.’ Next to my dad, he is the coolest person I ever met, so …” He searched for words, “So I decided to come and check it out.”

“Okay.” I began. “This isn’t your uncle’s Special Operations. Since the Big One, we’ve made quite a few” – I caught myself before saying changes – “upgrades.” I paused, “Roberto, before we take the enhanced reality tour, I’d like to know what augments you have had – if any.”

“Sure.” Roberto paused for a moment,“ Let’s see…I’ve got Daystrom Model 40B ER corneal implants, a Neuralink BCI jack, and a Samsung cognitive enhancement implant. That’s about it.”

The essence of “Sine Pari,” is one of hackable bodies and hackable systems. The young recruit has already augmented his body, and has childhood experience hacking the robots and household AIs he grew up with. We don’t know the kinds of wars prospective recruit Roberto Preciado will fight, or even the nature of The Big One fought before this time. Instead, we get a portrait of a highly advanced scanning system, helpful AIs in the place of aides, and a social comfort with biomechanical body enhancements.

What is missing from this portrait, yet implied by this world, is the massive amount of cybersecurity back-end needed to secure not just the devices a person uses, but the devices people put into their bodies. To take this to one logical end, we need only remember how, two weeks ago, a popular jogging app made headlines because of the paths it revealed around military bases. Jogging apps that log the GPS position of a user, and then upload it later, create maps of some value, and are a good way to think about the vulnerabilities inherent in aggregate data.

In “Sine Pari,” we get a recruit with three augmentations: electronic eyes, a brain input link, and a brain enhancement. Notably, these are also all assumed to be from major brands, ones where it’s entirely possible the security flaws can be studied and exploited for profit. Now, it’s possible that after recruiting, our new Special Operator swaps out commercial parts for models built to military specifications, which would be a tidy way to close that potential plot hole. It’s also possible, following the logic of this world, that when Roberto Preciado joins the force, his cognitive enhancement contains malicious code, his eyes record everything he sees, and his brain-link transmits that information to an interested third party, who suddenly has eyes on the inside a Special Operations unit.

When we think of the potential the future brings, we have to think of the risk as well. Electronic eyeballs are one compromise eye from picture-perfect spy cameras. Brain uplinks and cognitive enhancements may greatly reduce training times and allow the rapid learning of complex skills, but they could also be a pathway to compromise or hijack the brain of the person in question. As the tools of war change, the adversarial nature of war, the danger of technologies exploited against their users, remain.

Fortunately, both for the fictional protagonist here and for TRADOC’s Soldier 2050 concept more broadly, this is not a stand-alone project. On March 8 and 9, TRADOC is co-sponsoring a Bio Convergence and Soldier 2050 Conference in Menlo Park, California.

With IEDs set on the side of the road, or attacks springing suddenly from concealed attackers in ambush, being first is a risky proposition. Which means it’s an ideal job for a robot, immune from such fleshy concerns as panic or mortality.

Last month, U.S. Army Tank Automotive Research, Development and Engineering Center (TARDEC) and the U.S. Army Armaments Research, Development and Engineering Center (ARDEC) collaborated to see if a robot Humvee could do the same course as human crews.

That course was Scout Gunnery Table VI, which the Army uses to certify crews for combat vehicles. The course tests the vehicle’s ability to move and shoot and communicate, engage stationary and moving targets. Those targets range from infantry cut-outs to armored vehicle silhouettes. For testing a robotic Humvee, the Army will send it alongside a human-driven command-and-control vehicle, as a sort of wingman team. The robot Humvee will operate without people inside, using three different autonomous systems:

First is the TARDEC-developed Robotic Technology Kernel (RTK), the autonomy system for planning and controlling the vehicle’s mobility. RTK contains driving cameras for remote operation, LIDAR (light detection and ranging) sensors for object classification, stereo cameras for terrain classification, computers for computation, radios for communication, and all the essential hardware, cables and mounts. The system can be manually driven through teleoperation or autonomously driven through waypoint navigation.

In addition to the autonomy system, the robotic vehicle has a Picatinny Lightweight Remote Weapon System that can mount either a minigun or a machine gun. That means that this is an armed robot, though one with a human-in-the-loop, as we’ll get to in just a moment. The robot Humvee, with its autonomy system and remote weapon system, also uses the Autonomous Remote Engagement System (ARES), which, according to the Army can, uses a vision-based system to both track targets on its own and follow targets designated by a human user.

So, this is a Humvee that can be remotely controlled or navigate autonomously to waypoints, that mounts a weapon, and that can watch and track targets. Crucially, it takes a human to press the trigger. In this case, that human is one of the five people in the wingman command-and-control vehicle. There’s a commander, a driver and then, in the back, there’s a gunner and a remote driver (piloting the robot) and a remote weapons operator (controlling the robot’s gun). The hatch gunner can also use a designator to mark targets for the robot.

The autonomy we see here is a sort of limited, directed autonomy: the robot can go where it’s sent, and point a gun at a target it’s told to follow, but this is not a machine operating entirely independently, given a mission it then executes on its own. Instead, it is a robot tag-along, a vehicle crewed remotely.

As robotics move more and more into the battlefield and become a standard part of war, it will look a lot like this: an aging military machine, retrofitted into a robot, taking point on patrol and firing back while a human, inside a follow-on vehicle, tells the robot what to shoot.