Deepfake Rules Tighten as Elections Loom

A fast clampdown on AI deception

Governments and technology companies are moving to curb AI-driven deception as national and local elections unfold around the world. The focus is on deepfakes and other synthetic media that mimic real people’s voices and faces. The tools have become cheaper and easier to use. The stakes are rising.

In early 2024, a widely reported robocall used an AI-cloned voice that sounded like President Joe Biden ahead of the New Hampshire primary. Election officials and telecom regulators reacted quickly. Similar incidents have surfaced in other countries. The concern is simple: bad actors can use AI to erode trust, suppress votes, or stoke conflict at scale.

A wave of rules and pledges in 2024

Several measures arrived this year, spanning laws, regulatory rulings, and platform policies:

• United States: In February 2024, the Federal Communications Commission (FCC) declared AI-generated voice cloning in robocalls illegal under the Telephone Consumer Protection Act. Chairwoman Jessica Rosenworcel said, “We’re putting the fraudsters behind these robocalls on notice.”
• European Union: The EU’s landmark AI Act entered into force in mid-2024, with phased obligations. Some prohibitions take effect six months later. The law restricts or bans certain uses of biometric and emotion-recognition systems and sets transparency duties for general-purpose AI. Thierry Breton, the EU internal market commissioner, called the measure “much more than a rulebook — it’s a launchpad for EU startups and researchers.”
• Platforms: Major social networks have added or expanded labels for AI-generated content. YouTube now requires creators to disclose when realistic content is synthetic. Meta and others have introduced “Made with AI” labels in some contexts and tightened rules for political ads that use generative tools.
• Provenance tech: Industry groups advanced tools to prove content origin. The Coalition for Content Provenance and Authenticity (C2PA) expanded use of Content Credentials, a cryptographic “receipt” embedded in files. Google DeepMind extended SynthID, a watermarking technology for images and audio in some products. Several AI labs say they embed metadata into generated images to help detection.
• States and local authorities: In the U.S., more than a dozen states enacted or updated deepfake rules related to elections, defamation, or intimate imagery. Election agencies issued guidance on how to handle suspected synthetic content.

These steps share a goal: make abuse harder and accountability easier while preserving legitimate uses of AI, from accessibility tools to entertainment.

Why now: a confluence of risk

The timing reflects a convergence of factors. Generative AI systems have made high-quality voice and video synthesis available to the public. Disinformation networks are active in multiple regions. And trust in institutions is fragile. Regulators say traditional defenses have not kept up with the new speed and scale.

The FCC’s move followed reports of voters receiving synthetic calls that impersonated public figures. Rosenworcel said the agency’s action makes clear that callers cannot hide behind a machine to skirt the rules. Telecom providers were told to block traffic linked to illegal campaigns.

In Europe, lawmakers completed a multi-year process to shape the AI Act, the first broad AI law of its kind. The law pairs restrictions with sandbox programs to help developers test systems with oversight. It also creates an AI Office inside the European Commission to coordinate enforcement, especially for powerful general-purpose models.

What the new rules cover

While details differ, three themes appear again and again:

• Transparency: Policies push for clear disclosures when content is AI-generated. Platforms are rolling out visible labels and back-end metadata. Some ads and political content must carry notices when synthetic media is used.
• Prohibited or restricted uses: The EU bans certain biometric categorization based on sensitive traits and limits emotion recognition in workplaces and schools. The FCC bans AI voice cloning in robocalls without consent. Several states prohibit deepfake election content close to voting days, with narrow exceptions.
• Accountability and testing: Developers of high-risk systems face risk assessments, documentation, and incident reporting in the EU. In the U.S., agencies are piloting red-teaming and safety evaluations under federal guidance.

Experts say clear boundaries help legitimate actors plan. But they warn that enforcement will be tested. Deepfakes can be generated abroad and spread quickly across borders. Smaller platforms and messaging apps present additional challenges for detection and takedown.

The limits of labels and watermarks

Technical provenance is advancing. Yet it is not foolproof. Watermarks can be stripped or degraded. Metadata can be lost during editing or platform re-uploads. Not all generators use the same standards, and open-source tools complicate uniform adoption. Audio and video pose unique difficulties because compression can erode signals.

That is why authorities pair provenance with behavioral and legal deterrents. For example, mandatory robocall disclosures are backed by fines and carrier blocking. Platforms can suspend repeat violators. Civil remedies and criminal penalties apply in some state laws for malicious deepfakes.

Media literacy is part of the response. Election offices and newsrooms have raised public awareness. Voters are told to slow down, check sources, and be skeptical of sensational clips appearing close to voting deadlines. Fact-checkers are building rapid-response teams to examine viral content.

Industry tools, broader consequences

Generative AI is also reshaping creative work, software, and customer service. Chipmakers and cloud providers are racing to meet demand. At the World Economic Forum in January 2024, NVIDIA chief executive Jensen Huang said, “Everyone can be a programmer now — you just have to say something to the computer.” That optimism is shared by many startups building productivity tools.

But the same ease of use worries policymakers. They fear mass manipulation and microtargeted propaganda. Civil liberties groups caution against overbroad rules that could chill satire, art, or legitimate political speech. Legislators are trying to balance urgency with safeguards for free expression.

Copyright disputes add another layer. News organizations, artists, and publishers have sued some AI developers over the use of copyrighted works to train models. Outcomes could influence how provenance signals and licensing frameworks evolve for political content too.

What to watch next

Enforcement capacity will be decisive. The EU is standing up its AI Office and coordinating with national regulators. In the U.S., the FCC and state attorneys general are increasing pressure on illegal robocall operations. The Federal Election Commission has considered petitions to clarify rules around deceptive AI in campaign advertising.

Technology will also move. Expect broader adoption of common provenance standards, more robust watermarking for audio and video, and improved detection models. Platforms are likely to refine their labels and appeal processes after early misfires.

For organizations preparing for the next election cycle, experts recommend:

• Policy updates: Set clear internal rules for synthetic media in marketing, outreach, and customer contact.
• Disclosure workflows: Build in content labels and metadata for AI-generated assets.
• Vendor checks: Assess whether tools support Content Credentials or other provenance standards.
• Incident playbooks: Define how to respond to a viral deepfake about your brand or candidate.
• Training: Teach staff to recognize likely signs of manipulated media and to verify before sharing.

The central fact remains: AI makes it easier to create persuasive content at scale. Rules adopted this year aim to slow abuse, raise the cost of deception, and inform the public. Their success will depend on cross-border cooperation, steady enforcement, and continued innovation in transparency tools. In a tense information environment, even incremental steps can help build trust.