The Economist January 29th 2022 Technology Quarterly Defence technology 9Headsinthe clouds
“Y
ou couldput forward a thesis that Afghanistan was the
most densely surveilled battlespace in the history of hu
mankind,” says Mick Ryan, until recently the head of Australia’s
defence college. “And that didn’t seem to help us.” For an informa
tion advantage to change the course of a war you need more than
just a cornucopia of sensors; you need ways to combine their data
into information that can be acted on at speed.
Take radar, a technology which changed the course of the war
in which it made its debut more than any other new sensor in his
tory. It had applications from the finding of submarines (via their
snorkels) to the proximity fuses which made artillery and antiair
craft rounds more lethal. As its developers used to grumble when
nuclear physicists were lauded for their godlike power, “Radar
won the war; nuclear weapons just ended it.”
But radar’s capabilities had to be built into systems that made
use of them. The canonical example is the airdefence system
used during the Battle of Britain. Its radars were linked to a net
work of radio receivers, barrage balloons, fighter planes and hu
man spotters through a network of phone lines. The resulting re
ports were plotted on a map and used to guide fighter planes to
their targets with spectacular success.
Over the past decade efforts to embody similar feats of collec
tive intelligence in aisystems have made real progress. In a recent
exercise in Poland, the British Army experimented with a com
mand and control system built over eight weeks in collaboration
with Anduril, a Californiabased company which provides both
sensors and systems to fuse their data. The system did not just
spot targets; it also worked out the closest suitable aircraft that
could be used to attack them and presented its results to the for
ce’s commanders in the form of clearly delineated options.
This far outperformed the old way of doing things; options for
hitting targets were delivered 30 minutes quicker, according to an
officer involved in the experiment. And it required a team of just
five people, rather than the 25 it used to take. The officer compares
the improvement to that offered by satellite navigation with real
time traffic updates. “It’s like going from an AZ...to Waze. You’re
operating at a ridiculously different speed.”
Joseph Votel, a recently retired head of the Pentagon’s Central
Command, said last year he was struck by how Israeli forces
mounting strikes on Gaza in May had been integrating ai into
their operations and by “the impact that is having on their target
ing cycles”. He says Israel is using aito generate a large range of
potential targets for surveillance to whittle down. This lets its
forces “disrupt enemy attacks without the need for a lengthy de
velopment period or a longer campaign.”
America’s armed forces, helped by Palantir
(an aicompany which, like Anduril, takes its
name from “The Lord of the Rings”) and other
contractors, is trying to build such technology
into a system which can narrow down a huge
range of potential targets and pass informa
tion about them freely to where it is most
needed. Given the finite capacity of commu
nication systems, not to mention the vulnera
bility, this requires that an increasing amount
of processing be done “on the edge”—that is,
on the platform carrying the sensor. In 2016 a Pentagon project called Maven started trying to ad
dress the “lots of surveillance but not much to show for it” pro
blem identified by General Ryan. The idea was to automate the
identification of people and objects in the petabytes of video foot
age sent back by surveillance drones. It ended up producing soft
ware efficient enough to run on the drones themselves. In Scarlet
Dragon, a recentaifocused American exercise in which a wide
range of systems were used to comb a large area for a small target,
things were greatly speeded up by allowing satellites to provide
estimates of where a target might be in a compact format readable
by another sensor or a targeting system, rather than transmitting
highdefinition pictures of the sort humans look at.
In a world where bandwidth is often the biggest constraint
such parsimony is a boon.It speeds up kill chains while reducing
vulnerability to jamming. At the same time, it puts a greater bur
den on the automated parts of the system to provide reliable syn
opses of what they see, which is a worry for people keen to ensure
that fully informed and responsible human beings stay on top of
all decisions about where and when to blow things up. Reforging the shards
However much edge processing may whittle down individual
flows, though, the ability for sensors to proliferate and the hunger
for more knowledge elsewhere in the system will still mean that
command systems need a greater capacity for handling data in
bulk. That is why armed forces are spending heavily on cloud
computing services provided by big tech companies to increase
their datahandling capacity. In 2019 the Pentagon awarded Micro
soft a $10bn contract for its Joint Enterprise
Defence Infrastructure (jedi). Last year Ama
zon, which has been supplying the ciawith
such services since 2013, got the contract an
nulled. A new tender issued in November will
probably see the work shared among a num
ber of firms. There will be more than enough
to go around.
Clouds offer advantages in speed, scale and
flexibility. They also help with “data fusion”—
combining different pieces of information to
reveal things that one source cannot capture,
including things no human would think toThe difficulties of dealing with lots of dataSignals from noise “ You’ll be amazed
at the patterns
it picks up when
you put bulk
data together”