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Section 7.4 Deepfakes and Disinformation

Harmful lies are nothing new. But the ability to distort reality has taken an exponential leap forward with deepfake technology. This capability makes it possible to create audio and video of real people saying and doing things they never said or did. Machine learning techniques are escalating the technology’s sophistication, making deepfakes ever more realistic and increasingly resistant to detection. Deepfake technology has characteristics that enable rapid and widespread diffusion, putting it into the hands of both sophisticated and unsophisticated actors.
Consequently, while deepfake technology will bring certain benefits, it will also introduce many harms. The marketplace of ideas already suffers from truth decay as our networked information environment interacts in toxic ways with our cognitive biases. Deepfakes will exacerbate this problem significantly. Individuals and businesses will face novel forms of exploitation, intimidation, and personal sabotage. The risks to our democracy and to national security are profound as well.

Subsection 7.4.1 How to Navigate in a World of Synthetic Media

To address these growing threats, responding to the diffusion of generative falsifications requires coordinated measures across multiple sectors. As surveyed by researchers, these include the role of technological solutions; criminal penalties, civil liability, and regulatory action; military and covert-action responses; economic sanctions; and market developments. In practice, navigating this ecosystem effectively requires four foundational pillars:
Technical Solutions: Implementing cryptographic authentication trails and provenance tracking to verify content origins.
Legal & Regulatory Action: Updating civil liability and criminal penalties to prosecute malicious impersonation and fraud.
Platform Governance: Enforcing clear detection protocols and labeling mechanisms across digital sharing platforms.
Educational Literacy: Developing critical evaluation skills, such as learning to always verify facts and citations provided by AI, treating AI as a collaborative tool rather than a substitute for one’s own reasoning, and understanding how AI models can hallucinate or confidently generate false information based on patterns rather than truth.
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