AI and espionage

Episode Transcript

Speaker 1 (00:01):
Espionage has also been now influenced by AI. But how
are they using it. Let's take a look and see
what's going on. Something. The things you can see AI
is helping with is scaling and speeding analysis. Like ocent sigent,
AI rapidly processes huge volumes of open source data that
include social media, foreign news, darknet also signals, intelligence intercepts,

(00:24):
and traffic and imagery immine from satellites and drones that
lets analysts find new leads, track networks and detect changes
far faster than ever. Also, another thing that's been incredible
has been large language and translation models that speed translation
of captured documents, voice intercepts, and help triage which material
is worth deeper human review. So this is probably going

(00:46):
to affect a lot of the jobs that are used
for translation, link analysis, entity resolution, and network detection, where
machine learning uncovers relationships and messy data sets who met, whom,
money flows, and device associations. This is of course central
to counter espionage and tracking clandestine networks. AI also improves
object to person detection and imagery, automates change detection, and

(01:10):
enables persistent monitoring without needing human eyes in every frame.
And finally, AI also assists cyber operators to craft more
convincing phishing, automate reconnaissance, and speed malware development and opphification.
But of course there's a downside. Some of the things
that could hurt intelligence include deep fakes, where audio video
imagery fakes can be weaponized to impersonate officials, fabricate events,

(01:32):
or discredit targets. Detection is an arms race at this point.
Another one is AI generated content. Automated campaigns make it
hard to prove who acted, complicating diplomatic or legal responses.
AI lowers a skill expense barrier for state and non
state actors to run sophisticated cybro and disinformation campaigns. The

(01:53):
same AI tools help both defenders and attackers. Recent reporting
shows multiple adversary states rapidly adopting generative AI for these
particular operations. Over Reliance and bias could also affect those
who are trained on Bias or partial data can mislead analysts,
and finally, adversaries can try to contaminate training data craft

(02:16):
inputs that trick the models. CIA and other agencies operationalizing
AI are saying that the AI has moved beyond pilots
and it's scaling AI into many mission areas now analytics,
cyber finance personnel, often via cloud and vendor partnerships. US
cyber defense organizations and SAY personnel sited using mL to

(02:38):
detect hacking behavior at AI assistant tools to trace adversary activity.
US agencies and homeland security organizations have also published warnings
and guidance about generative AI threats like deep figs so
operational implications for espionage well. AI generated identities and media
increase the burden on human sources and authentication workflows. AI

(03:01):
enables quicker queuing of operations, but faster tempo increases risk
of acting incorrectly. Bottom line, there's pros and cons, and
it could be transformational for modern espionage since it multiplies
what analysts can see him do at a scale and
speed never seen before, but as well, at the same
time multiplies threats. The balance between benefit and harm depends

(03:24):
on a lot of factors, and agencies that pair with
AI with strong validation and governance get the gains while
limitating while limiting strategic risk.