The Day AI Becomes an "Asymmetric Amplifier" — AI Itself Is Not a Weapon, But "Weaponization" Has Become Surprisingly Easy

The "Asymmetric Megaphone" Handed Over by the Democratization of AI

An article published on MarketBeat on December 14, 2025 (sourced from AP) strongly indicated the potential for escalating risks as extremist groups are in the "beginning to experiment" stage with AI. The point is simple: AI not only works to "make strong organizations stronger" but also allows the "weaker side to have a certain level of influence." If groups with limited funds and manpower acquire "visually appealing content" and "multilingual, mass dissemination" through generative AI, propaganda can compete not on "production capability" but on "distribution design." MarketBeat

The AP article also mentions posts in pro-IS online spaces encouraging the incorporation of AI into activities. The frightening aspect here is that AI is discussed not as "advanced military technology" but as a "tool" akin to a smartphone. In other words, the lowering of entry barriers broadens the scope of threats. AP News

The Ongoing "Experiment": Deepfakes, Translation, and Cyber

The central concern raised in the article is that generative AI can mass-produce "plausible images, videos, and audio," which can be used for recruitment and disruption. In fact, there have been instances in the context of past conflicts and terrorist incidents where AI-generated content has been circulated to incite anger and division, obscuring real-world tragedies. The key point here is that fakes do not need to be of "completely believable quality." Simply filling the early timeline and capturing the "first impression" is enough to be effective. AP News

Moreover, there are indications that extremists are using AI to synthesize voices and rapidly translate messages into multiple languages. Translation is subtle but effective. When the natural friction of the "language barrier" disappears, propaganda can spread across borders simultaneously. AP News

And on the cyber front. The article also touches on how generative AI can facilitate the partial automation of phishing (impersonation) and malicious code creation. Generative AI shortcuts the "skill of attack" and reduces the effort of the task. Especially the "authenticity" achieved through synthetic voice and video is often used to undermine approval processes within organizations. AP News

"Not Yet Sophisticated"—Why the Danger Still Increases

The AP article suggests that such AI usage is currently not as advanced as that of state-level actors (such as China, Russia, Iran), and "more sophisticated applications remain 'aspirational' for the time being." However, it also states that as AI becomes cheaper and more powerful, the danger will increase to an unavoidable level. AP News

This "two-pronged approach" is realistic. Even if today's threats seem "immature," tomorrow's threats might be "well-executed." AI is more of an engine for dissemination, persuasion, and automation than a weapon itself. Once operational know-how is shared and templated, imitation accelerates rapidly.

Indeed, the research community has long discussed the potential for generative AI to be misused for violent extremism (propaganda, training, planning support, etc.) and the issue of "backdoors" in models. The movements reported by AP can be read as signs of approaching "real-world operations" along that trajectory. Combating Terrorism Center at West Point

On the other hand, observations from platform providers suggest that "AI is useful but not necessarily a 'decisive game-changer.'" For example, Google's threat intelligence analyzes the use of AI by state-related threat actors while indicating that, although AI can be helpful, exaggeration should be avoided. Therefore, rather than inciting fear, there is a need for a mindset of "preparing where it works." Google Cloud

Policy and Corporate Collaboration: Catching Up with "Operation" Rather Than "Technology"

The AP article discusses proposals in the US Congress, such as a bill mandating annual assessments by homeland security authorities and the need for frameworks that make it easier for AI development companies to share "signs of misuse." In short, the focus is on institutional design to detect and collaboratively block signals of misuse, not just "making AI models smarter." AP News

The difficulty here is that it involves freedom of speech and expression, concerns about increased surveillance, trade secrets, and differences in international jurisdictions. Therefore, creating a "universal regulation" is challenging. The realistic solution will likely be a patchwork of the following.

• Implement detection and labeling of synthetic content as UI/UX

• Suppress large-scale misuse patterns (mass generation, mass posting, bot collaboration) based on behavior

• Increase circuits for sharing misuse observation data among researchers, companies, and governments

• Above all, create a system for quickly verifying during crises
  
  
  

SNS Reactions: Notable Points in LinkedIn's Comment Section

In the social media space where this article was shared, it was striking that attention was focused on **"where friction disappears"** rather than the broad subject of "AI's dangers."

• Translation is Underestimated
  Comments were seen to the effect that "when the natural friction of the language barrier disappears, the speed of radicalization changes." Technically subtle, but socially effective—this intuition resonates. LinkedIn

• Vulnerability Lies More in "Governance Lag" Than Model Performance
  Multiple responses indicated that "the risk lies more in the inability to keep up with operation and governance than in the capability itself." The concern is how to prevent moments when the speed of dissemination outpaces "correctness." LinkedIn

• "Calm-Toned Fakes" Hit During Crises
  There were also voices pointing out the fear of plausible narration guiding people during chaos. The moment images or voices take on an "authoritative tone," emotions move ahead of verification. LinkedIn

What should be emphasized here is that many reactions on social media are not about "AI being entirely bad," but rather focus on **"the design of verification and display" and "the etiquette of information dissemination during crises."** This is closer to specific countermeasures than fear.

What Individuals Can Do: A "Minimizing Damage" Checklist for the Age of Dissemination

Finally, let's organize effective countermeasures for readers. Not flashy, but effective, especially during crises.

• Do not trust images or videos that come in breaking news for the first five minutes (hold off initially)

• Look for "Where is the primary information?" (official announcements, multiple reliable media)

• Assume clipped videos lack context before and after when viewing

• Be skeptical of "plausible voices" (the cost of synthetic voices is decreasing) AP News

• Take a deep breath before spreading posts that incite anger or fear (emotions are the fuel for dissemination)
  
  
  

Conclusion: The "Misuse" of AI is a Technological Issue and Simultaneously a Social Operational Issue

What the MarketBeat/AP article indicated is not a simple narrative of "extremists suddenly gaining superpowers with AI." Rather, it is about the danger of the distortion in the information environment where effort is reduced, dissemination is accelerated, and verification is left behind due to AI. AP News

And the key to correcting that distortion lies not only in the performance competition of models but in "mundane operations" such as labeling, sharing, verification, and education. As AI has deeply entered society, whether we can shift to a design that does not assume "goodwill only" will be the turning point beyond 2026. Combating Terrorism Center at West Point