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AI REMAINS A WILD CARD IN THE WAR AGAINST DISINFORMATIONAI REMAINS A WILD CARD
IN THE WAR AGAINST DISINFORMATION

Digital literacy and protective measures will be key to detecting disinformation
and deepfakes as AI is used to shape public opinion and erode trust in the
democratic processes, as well as identify nefarious content.

Erin Drake, Melissa DeOrio

July 18, 2024

5 Min Read
Source: Enrico01 via Alamy Stock Photo


COMMENTARY

Disinformation — information created and shared to mislead opinion or
understanding — isn't a new phenomenon. However, digital media and the
proliferation of open source generative artificial intelligence (GenAI) tools
like ChatGPT, DALL-E, and DeepSwap, coupled with mass dissemination capabilities
of social media, are exacerbating challenges associated with preventing the
spread of potentially harmful fake content. 

Although in their infancy, these tools have begun shaping how we create digital
content, requiring little in the way of skill or budget to produce convincing
photo and video imitations of individuals or generate believable conspiratorial
narratives. In fact, the World Economic Forum places disinformation amplified by
AI as one of the most severe global risks over the next few years, including the
possibilities for exploitation amid heightened global political and social
tensions, and during critical junctures such as elections. 

In 2024, as more than 2 billion voters across 50 countries have already headed
to the polls or await upcoming elections, disinformation has driven concerns
over its ability to shape public opinion and erode trust in the media and
democratic processes. But while AI-generated content can be leveraged to
manipulate a narrative, there is also potential for these tools to improve our
capabilities to identify and protect against these threats. 


ADDRESSING AI-GENERATED DISINFORMATION

Governments and regulatory authorities have introduced various guidelines and
legislation to protect the public from AI-generated disinformation. In November
2023, 18 countries — including the US and UK — entered into a nonbinding AI
Safety agreement, while in the European Union, an AI Act approved in mid-March
limits various AI applications. The Indian government drafted legislation in
response to a proliferation of deepfakes during elections cycle that
compels social media companies to remove reported deepfakes or lose their
protection from liability for third-party content. 

Nevertheless, authorities have struggled to adapt to the shifting AI landscape,
which often outpaces their ability to develop relevant expertise and reach
consensus across multiple (and often opposing) stakeholders from government,
civil, and commercial spheres. 

Social media companies have also implemented guardrails to protect users,
including increased scanning and removal of fake accounts, and steering users
toward reliable sources of information, particularly around elections.
Amid financial challenges, many platforms have downsized teams dedicated to AI
ethics and online safety, creating uncertainty as to the impact this will have
on platforms' abilities and appetite to effectively stem false content in the
coming years. 

Meanwhile, technical challenges persist around identifying and containing
misleading content. The sheer volume and rate at which information spreads
through social media platforms — often where individuals first encounter
falsified content — seriously complicates detection efforts; harmful posts can
"go viral" within hours as platforms prioritize engagement over accuracy.
Automated moderation has improved capabilities to an extent, but such solutions
have been unable to keep up. For instance, significant gaps remain in automated
attempts to detect certain hashtags, keywords, misspellings and non-English
words.  

Disinformation can be exacerbated when it is unknowingly disseminated by
mainstream media or influencers who have not sufficiently verified its
authenticity. In May 2023, the Irish Times apologized after gaps in its editing
and publication process resulted in the publication of an AI-generated article.
In the same month, while an AI-generated image on Twitter of an explosion at the
Pentagon was quickly debunked by US law enforcement, it nonetheless prompted a
0.26% drop in the stock market. 


WHAT CAN BE DONE?

Not all applications of AI are malicious. Indeed, leaning into AI may help
circumvent some limitations of human content moderation, decreasing reliance on
human moderators to improve efficiency and reduce costs. But there are
limitations. Content moderation using large language models (LLMs) is often
overly sensitive in the absence of sufficient human oversight to interpret
context and sentiment, blurring the line between preventing the spread of
harmful content and suppressing alternative views. Continued challenges with
biased training data and algorithms and AI hallucinations (occurring most
commonly in image recognition tasks) have also contributed to difficulties in
employing AI technology as a protective measure. 

A further potential solution, already in use in China, involves "watermarking"
AI-generated content to help identification. Though the differences between AI
and human-generated content are often imperceptible to us, deep-learning models
and algorithms within existing solutions can easily detect these variations. The
dynamic nature of AI-generated content poses a unique challenge for digital
forensic investigators, who need to develop increasingly sophisticated methods
to counter adaptive techniques from malicious actors leveraging these
technologies. While existing watermark technology is a step in the right
direction, diversifying solutions will ensure continued innovation which can
outpace, or at least keep up with, adversarial uses. 


BOOSTING DIGITAL LITERACY

Combating disinformation also requires addressing users' ability to critically
engage with AI-generated content, particularly during election cycles. This
requires improved vigilance in identifying and reporting misleading or harmful
content. However, research shows that our understanding of what AI can do and
our ability to spot fake content remains limited. Although skepticism is often
taught from an early age in the consumption of written content, technological
innovations now necessitate the extension of this practice to audio and visual
media to develop a more discerning audience. 


TESTING GROUND

As adversarial actors adapt and evolve their use of AI to create and spread
disinformation, 2024 and its multitude of elections will be a testing ground for
how effectively companies, governments, and consumers are able to combat this
threat. Not only will authorities need to double down on ensuring sufficient
protective measures to guard people, institutions, and political processes
against AI-driven disinformation, but it will also become increasingly critical
to ensure that communities are equipped with the digital literacy and vigilance
needed to protect themselves where other measures may fail.




ABOUT THE AUTHOR(S)

Erin Drake

Associate, Strategic Intelligence, S-RM

Erin Drake is an associate in S-RM’s Strategic Intelligence team, where she
leads on case management of regular and bespoke consulting projects. She joined
the firm in 2017 and has worked on a variety of projects ranging from threat
assessments to security risk assessments across several markets. This often
entails the development of client-specific approach and methodological framework
for high-level and detailed bespoke projects, to support clients in
understanding and monitoring the security, political, regulatory, reputational,
geopolitical, and macroeconomic threats present in their operating environment.
Erin’s expertise includes global maritime security issues, political stability
concerns in the commercial sector, and conflict analysis. Erin holds a master's
degree in international relations with a focus on global security issues like
nuclear proliferation and multilateral diplomacy.

See more from Erin Drake

Melissa DeOrio

Global Cyber Threat Intelligence Lead, S-RM

Melissa DeOrio is Global Cyber Threat Intelligence Lead at S-RM, supporting
clients on a variety of proactive cyber and cyber-threat intelligence services.
Before joining S-RM, Melissa worked on US Federal Law Enforcement cyber
investigations as a cyber targeter. In this role, Melissa utilized numerous
cyber-investigative techniques and methodologies to investigate cyber threat
actors and groups including open source intelligence techniques, cryptocurrency
asset tracing as well as identifying and mapping threat actor tactics,
techniques, and procedures (TTPs) to provide tactical and strategic intelligence
reports. Melissa began her career in corporate intelligence, where she
specialized in Turkish regional investigations, managed a global team of
researchers, and played a role in the development and implementation of a new
compliance program at a leading management consulting firm. 

See more from Melissa DeOrio
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