The emergence of AI-generated synthetic media—images, videos, voices, and text created by artificial intelligence—has unlocked transformative potential in fields like entertainment, marketing, education, and more. From deepfake videos that mimic real people to photorealistic avatars and synthetic voices used in films or audiobooks, generative AI is reshaping how content is created and consumed.
Yet alongside its innovations lie substantial risks. Misuse of synthetic media can deceive, manipulate, defame, or harm. As generative AI tools become more accessible and sophisticated, it’s essential for individuals, businesses, and regulators to understand and address the associated dangers.
In this blog, we explore the key risks of AI-generated synthetic media and strategies for navigating this evolving landscape responsibly.
What is Synthetic Media?
Synthetic media refers to any content—text, audio, image, or video—that is created or modified using artificial intelligence, often to simulate or mimic human behavior and appearance. This includes:
- Deepfakes: Videos that convincingly swap faces or voices.
- Text-to-image generation: Tools like Midjourney and DALL·E that produce realistic images from prompts.
- Synthetic voices: AI systems that replicate human speech with precise emotional tone and accent.
- Virtual avatars or influencers: Fully AI-generated characters with online personas.
These tools have immense creative and commercial value. However, they can also be exploited for malicious purposes.
Key Risks of AI-Generated Synthetic Media
1. Misinformation and Disinformation
The most urgent risk is the use of synthetic media to spread false or misleading information. Deepfake videos or fabricated audio clips can impersonate politicians, celebrities, or ordinary individuals to:
- Mislead voters during elections.
- Create false testimonies or confessions.
- Promote propaganda or incite violence.
In a world already battling fake news, synthetic media escalates the challenge by making falsehoods more visually and audibly convincing.
Example: In 2020, a deepfake video of Ukrainian President Volodymyr Zelenskyy was circulated, falsely claiming he was surrendering to Russia—a blatant attempt to demoralize and confuse citizens during war.
2. Defamation and Identity Theft
Generative AI can impersonate real people with startling accuracy, raising serious concerns about personal rights and reputation. Individuals can be targeted with:
- Fake pornographic videos featuring their likeness.
- Videos or audio of them saying or doing things they never did.
- Synthetic images used for fraud, scams, or blackmail.
The psychological and reputational toll on victims can be devastating.
3. Erosion of Trust in Authentic Media
As synthetic media becomes more widespread, the public may begin to question the authenticity of all media, even when it’s real.
This leads to what’s known as the “liar’s dividend”—a situation where genuine evidence is dismissed as fake simply because deepfakes exist.
In courtrooms, political discourse, and journalism, the ability to verify media authenticity becomes crucial to maintaining trust in facts and institutions.
4. Manipulation and Influence Operations
Authoritarian regimes, foreign actors, or interest groups can exploit synthetic media for psychological operations (psyops), targeting societies with tailored disinformation campaigns.
AI allows for:
- Language-specific fake videos.
- Culturally adapted content to maximize emotional response.
- Fake personas that engage with real people online.
This poses national security risks, especially in democracies where public opinion shapes policy and elections.
5. Legal and Regulatory Grey Areas
Most countries lack clear, up-to-date laws governing synthetic media. Questions abound:
- Who owns AI-generated content?
- Can you sue someone for using your likeness in a deepfake?
- Are platforms liable for hosting synthetic media?
The legal vacuum enables abusers to act with impunity while victims struggle for redress.
6. Bias and Stereotyping
Synthetic media can reinforce harmful stereotypes if training data includes biased portrayals of gender, race, or culture. Image-generation tools have already been shown to:
- Generate more men for prompts like “CEO” or “scientist.”
- Misrepresent non-Western cultures.
- Exclude people with disabilities or underrepresented features.
Unchecked, this can perpetuate discrimination under the guise of neutrality.
7. Psychological Impact and Social Consequences
The rise of hyper-realistic AI avatars and influencers may:
- Distort body image expectations.
- Lead to parasocial relationships with non-human entities.
- Confuse users about what is real, affecting mental health and decision-making.
This is particularly concerning for children and teens, who may be more susceptible to manipulation.
Strategies for Navigating the Risks
1. Watermarking and Content Authentication
AI companies and researchers are working on technical solutions to distinguish synthetic content:
- Invisible watermarks in images or videos.
- Metadata tagging to show if AI was used.
- Content authenticity initiatives like Adobe’s Content Credentials and Coalition for Content Provenance and Authenticity (C2PA).
These tools can help viewers and platforms verify the origin and integrity of media.
2. Public Awareness and Education
Critical media literacy is now more important than ever. Individuals must learn:
- How to spot signs of manipulation.
- To verify content before sharing.
- To approach viral media with skepticism.
Schools, workplaces, and digital platforms should invest in awareness campaigns and digital literacy programs.
3. Platform Responsibility
Social media companies and content hosts should:
- Develop policies for detecting and labeling synthetic media.
- Use AI-detection tools to flag potentially harmful content.
- Provide users with context about the source and nature of suspicious content.
Some platforms like TikTok and YouTube have begun implementing such guidelines—but enforcement remains inconsistent.
4. Legal and Policy Frameworks
Governments must act decisively to regulate the use of generative AI:
- Enact laws protecting individuals from unauthorized synthetic depictions.
- Penalize malicious use of synthetic media in fraud, defamation, or election interference.
- Mandate transparency from AI developers regarding training data and model capabilities.
Some jurisdictions are taking early steps:
- EU AI Act: Classifies deepfakes as high-risk content requiring disclosure.
- China: Requires synthetic content to carry visible watermarks.
- U.S.: Some states, like California, ban deepfakes during elections.
However, global coordination is needed for lasting impact.
5. Ethical Development Practices
AI companies must take responsibility for how their tools are used by:
- Implementing usage restrictions for harmful content.
- Giving creators tools to opt out of training datasets.
- Auditing models for bias and harmful capabilities.
OpenAI, for example, places restrictions on using its models for adult content, impersonation, and political manipulation.
Looking Ahead: A Balanced Approach
Synthetic media is here to stay. The goal shouldn’t be to ban it outright, but to build a framework where its creative and practical benefits can flourish safely—without sacrificing truth, rights, or trust.
This requires:
- Transparent AI development.
- Vigilant public discourse.
- Cross-sector collaboration between technologists, policymakers, educators, and civil society.
When used ethically, AI-generated media can inspire innovation and inclusion. But when left unchecked, it can fracture societies, manipulate realities, and erode democratic foundations.
As we navigate the age of AI-generated synthetic media, the challenge is not just technological—it is societal, ethical, and philosophical. We must ask not just what AI can generate, but what we should allow it to generate, and under what circumstances.
The responsibility lies with all of us: creators, consumers, developers, and regulators. Together, we can chart a course that embraces innovation without losing sight of truth, consent, and humanity.