10 Technology QuarterlyDefence technology The Economist January 29th 2022
look for. “You’ll be amazed at the patterns it picks up when you put
bulk data together from different sources and run aialgorithms
across them,” says an official familiar with Odyssey, a cloudcom
puting system being developed by the British armed forces.
Fusion is not just about adding things up; subtraction matters
too. In a presentation last year, BrigadierGeneral Paul Murray put
on screen the radar picture available to the North American Aero
space Defence Command (norad) on the afternoon of April 15th2015. It looked like a canvas at which someone had hurled a bucket
of blue paint. Somewhere within the mess was the flight path of
Doug Hughes, a postman from Florida who had taken it on himself
to deliver letters of protest to America’s Congress by flying his gy
rocopter from Gettysburg to the lawn of the Capitol. Whatever im
pact this may have had on the legislature, his ability to cross high
ly restricted airspace unnoticed alarmed norad.
Mr Jones’s approach was not entirely undetected. But it was
captured only intermittently, and amid everything else going on a
human looking at the data at the time concluded that it was innoc
uous. When a system called Pathfinder fused the relevant data
from more than 300 sensors and used aito remove the clutter,
though, the errant aircraft’s path stood out clearly.
To rule them all
Pathfinder’s decluttering uses commercial flight plans and weath
er reports to help sort things out; the integration of such open
source data is crucial to a lot of intelligence and surveillance. Last
year America’s National Security Commission on ai, chaired by
Eric Schmidt, a former ceoof Google, said that the country’s intel
ligence agencies would need to build “a continuous pipeline of
allsource intelligence analysis” into “continually learning ana
lytic engines”. The results, it hoped, would be insights “beyond the
current limits of unaided human cognition”. Call it Omniscient
Neuralnet Engineering for Reconnaissance, Intelligence and Na
tional Goalachievement, or oneringfor short.
Some workers at tech companies do not like the idea of being
involved in such things. In 2017 thousands of Google employees
signed a letter outlining their unhappiness with the company’s
role in the Maven project. Microsoft’s bid for the jedicontract
faced internal opposition on similar grounds. Many others will al
so have concerns about data fusion on such a scale, for military or
any other purposes.
They might take some comfort, at least for the time being, from
the fact that seamlessness is much more easily wished for and in
vested in than achieved. Different military services and agencies
contracting with different companies to build their own clouds
and ai systems just the way they want them will be likely to pro
duce the digital equivalent of Babel after God smote it. Military or
ganisations, accustomed to laying out their requirements years in
advance and in excruciating detail, are illequipped for a world in
which computing power has become a subscription service and in
which new software can transform the hardware it is running on.
The oldschool defence contractors who tend to get tasked with
integrating the data are “shockingly bad and wildly insecure”, ac
cording to Oliver Lewis of Rebellion Defence, an aiprovider. “They
often use an industrialera approach designed for building tanks
and aircraft that makes it impossible for them to write great soft
ware.” Interoperability often requires a level of commercial and
technical finesse rarely seen in the management of government
contracts. “Defence procurement,” says one aiexecutive, “is cur
rently fundamentally incompatible with this new model.”
It is not just that the technology is changing, the business envi
ronment unfamiliar and largescale systems integration always
hard—particularly so, it often seems, for governments. The sys
tems which fuse and interpret large amounts of data from dispa
rate farflung sources have to be robust not just in everyday oper
ation but when adversaries are trying very hard to break them
down. When it comes to the crunch, the enemy gets a say, too. nAdapt and survive
T
here arefour ways for those who would hide to fight back
against those trying to find them: destruction, deafening, dis
appearance and deception. Technological approaches to all of
those options will be used to counter the advantages that bringing
more sensors to the battlespace offers. As with the sensors, what
those technologies achieve will depend on the tactics used.
Destruction is straightforward: blow up the sensor. Missiles
which home in on the emissions from radars are central to estab
lishing air superiority; one of the benefits of stealth, be it that of an
f-35or a Harop drone, lies in getting close enough to do so reliably.
Radar has to reveal itself to work, though. Passive systems can
be both trickier to sniff out and cheaper to replace. Theatrelevel
airdefence systems are not designed to spot small drones carry
ing highresolution smartphone cameras, and would be an ex
traordinarily expensive way of blowing them up.
But the ease with which American drones wandered the skies
above Iraq, Afghanistan and other post9/11 war zones has left a
mistaken impression about the survivability of uavs. Most West
ern armies have not had to worry about things attacking them
from the sky since the Korean war ended in 1953. Now that they do,
they are investing in shortrange air defences. Azerbaijan’s suc
cess in NagornoKarabakh was in part down to the Armenians not
being up to snuff in this regard. Armed forces without many
drones—which is still most of them—will find their stocks quickly
depleted if used against a seasoned, wellequipped force.
Stocks will surely increase if it becomes possible to field moreNetworked sensors mean tactical evolution
is certain—and revolution possibleFierce contests