When Reality Isn’t Real: The Rising Threat of Multimodal AI
Multimodal AI — systems capable of processing and generating text, images, audio, and video in combination — is redefining the boundaries of human–machine interaction. While these capabilities promise transformative applications in healthcare, education, and creative industries, they also introduce an unprecedented spectrum of risks that traditional safeguards are struggling to address.
Why Multimodal AI Is Harder to Regulate
Unlike single-mode AI (e.g., text-only chatbots or image generators), multimodal systems can blend formats to create complex, highly convincing outputs. This makes abuse detection exponentially harder. A piece of fake news may now include not just fabricated text, but also synthetic video, forged audio, and realistic images — all reinforcing each other’s credibility.
The Growing Threat to Creators
One of the most urgent issues is the inability of existing art and copyright protection tools to fully shield creators in a multimodal environment. In Japan, the rapid proliferation of sexually explicit deepfakes demonstrates how quickly abuse can scale when technical safeguards lag behind creative possibilities. Globally, non-consensual synthetic content is spreading at a pace regulators can’t match.
These abuses aren’t just about reputation or privacy — they’re also about undermining trust in what is real. In a multimodal world, the lines between original and synthetic content blur so much that the creator’s rights, identity, and livelihood can be compromised.
Financial and Informational Risks
The dangers aren’t limited to the creative sector. In finance and media, multimodal narrative attacks — which blend real and synthetic personas, stories, and data — could destabilize markets and erode public trust. Imagine a coordinated attack where fake corporate announcements, realistic “witness” interviews, and fabricated economic data all appear simultaneously. Detecting such a campaign would be challenging, especially in fast-moving information ecosystems.
If these risks go unaddressed, we may face systemic failures in key domains:
- Creative — loss of artistic integrity and monetization channels.
- Financial — manipulation of stock prices, commodities, or cryptocurrency markets.
- Informational — erosion of trust in journalism, academic research, and public communication.
The Urgent Need for Action
Addressing multimodal AI risks will require a combination of:
- Advanced detection tools capable of working across formats.
- Legal frameworks that keep pace with technological evolution.
- Cross-industry collaboration to share intelligence and responses in real time.
The stakes are high. The technology is evolving faster than the guardrails around it, and the next major incident may not just be a viral deepfake — it could be a full-scale synthetic event with real-world economic and political consequences.
This analysis is based on just one of the many in-depth insights featured in the latest Supertrends SmartScans Quarterly Report on GenAI (section Regulation Risks and Cybersecurity), your window into the technologies, risks, and opportunities shaping the future.
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