back to top
HomeTechAI Was Used to Recreate the Voices of Dead Pilots. The NTSB...

AI Was Used to Recreate the Voices of Dead Pilots. The NTSB Responded by Locking Down Its Database.

- Advertisement -

Last year, a UPS cargo plane went down in Louisville, Kentucky. The crew didn’t survive. The NTSB opened an investigation, as it does with every major crash, and added the case files to its public docket system, as it also does. Transcripts, data, findings, all of it accessible to anyone who wanted to look.

What nobody thought about was the spectrogram.

A spectrogram is a visual representation of sound. It takes audio signals, breaks them down into frequencies, and renders them as an image. The NTSB included one in the Flight 2976 docket because federal law prohibits it from releasing actual cockpit voice recordings. The spectrogram felt like a reasonable middle ground, you could see that audio existed without being able to hear it.

Then Scott Manley, a YouTuber with a background in physics, pointed out on X that spectrograms encode enough data to work backwards from. The image wasn’t just a picture of sound. It contained the sound.

People ran with it. Using AI tools, they took the spectrogram and the publicly available transcript and reconstructed approximations of what the cockpit voice recorder actually captured. The voices of two pilots who died in that crash started circulating online.

The NTSB shut its entire public docket system down.

The gap nobody thought to close

What makes this situation unsettling is that nobody appears to have hacked or leaked anything.

The docket was public because NTSB investigations are supposed to be transparent. The spectrogram was included because it technically was not an audio recording. The transcript was already public. And the AI tools used to stitch everything together are the same kinds of tools millions of people use every day.

Nobody broke into a system or stole cockpit audio from a server. People simply realized that the boundary between image and audio no longer means much once modern AI tools enter the picture.

The NTSB’s response and what it reveals

The agency’s move was immediate. Shut the whole docket system down. Then restore it, but keep 42 investigations closed pending review, including Flight 2976.

That response is telling. The NTSB didn’t have a surgical fix ready because there wasn’t one. You can’t un-include a spectrogram from a filing that’s already been public. You can’t retroactively make the transcript harder to find. The only lever available was access, so they pulled it.

What that means practically is that researchers, journalists, aviation safety advocates, and family members of crash victims lost access to investigation data they had every right to see. A transparency system built around openness suddenly collided with tools that changed what public data can mean.

And this probably will not be the last time something like this happens.

A lot of institutional rules were written for a world where formats stayed in their lanes. Images were images. Audio was audio. Text was text. AI systems increasingly blur those boundaries, and organizations are finding out in real time that policies built around older assumptions do not always hold up anymore.

You May Like: Anthropic’s Mythos Just Helped Find macOS vulnerability That Could Break Apple’s Security Protections

Who’s responsible when nobody meant for this to happen?

The person who pointed out the spectrogram could be reconstructed wasn’t trying to harm anyone. The people who ran the reconstruction were curious, or technically showing off, or both. The NTSB published the spectrogram in good faith under rules that made sense when they were written. The AI tools involved are general purpose and widely used.

There’s no villain here. There’s just a collision between old policy and new capability, and two people who didn’t survive a crash whose voices approximations ended up on the internet without anyone’s permission,

That is what makes this situation harder to process. There is no obvious breach point where everything clearly went wrong. Just a chain of reasonable decisions that ended somewhere nobody expected.

And yet two pilots who died in a crash had of their voices circulating online without their families ever consenting to it.

Grief doesn’t care about intent. The federal rule banning the release of cockpit recordings existed for a reason. The problem is that the policy assumed a spectrogram and an audio file were different things. AI tools made that distinction a lot weaker than regulators realized.

Someone will close it now. But it took this to make that obvious.

Someone will probably rewrite those rules now. But stories like this keep revealing the same pattern: technology moves first, and institutions only discover the gaps after something uncomfortable slips through them.

Don’t miss any Tech Story

Subscribe To Firethering NewsLetter

You Can Unsubscribe Anytime! Read more in our privacy policy

LEAVE A REPLY

Please enter your comment!
Please enter your name here

YOU MAY ALSO LIKE
Google Built Gemma 4 12B Without Multimodal Encoders

Google Built Gemma 4 12B Without Multimodal Encoders

0
Every multimodal model you've used has the same basic system. Text goes in one way, images go through a vision encoder first, audio goes through an audio encoder first, and then everything gets handed off to the language model in a form it can work with. The encoders are load-bearing and you don't just remove them.Google actually removed them.Gemma 4 12B takes raw image patches and raw audio waveforms and projects them directly into the same embedding space as text tokens. There is no vision encoder or audio encoder. One decoder handling everything.
MiniMax M3 Shows What Happens When AI Stops Thinking in Turns

MiniMax M3 Shows What Happens When AI Stops Thinking in Turns

0
Most models quit around submission 30 because they stop finding improvement and exit on their own. That's what happened when MiniMax ran a CUDA kernel optimization task against a field of frontier models. Every model except two called it done within the first 30 submissions. M3's best result came on submission 145. After 24 hours. After multiple plateaus where the numbers stopped moving and a reasonable model would have concluded there was nothing left to find. That's the thing MiniMax released yesterday. An AI model with a 1M token context window, native multimodality, and apparently a problem with knowing when to stop.
Anthropic Files for an IPO. AI Is Entering Its Public Company Era

Anthropic Files for an IPO. AI Is Entering Its Public Company Era.

0
Anthropic has officially taken its first step toward becoming a public company. In a brief announcement on Monday, the company said it had confidentially submitted a draft S-1 registration statement to the U.S. Securities and Exchange Commission for a proposed initial public offering. The filing doesn't reveal a share price, a fundraising target, or even a timeline. For now, it simply gives Anthropic the option to go public once the SEC review process is complete. Just a few years ago, Anthropic was a small group of former OpenAI researchers trying to build an alternative vision for advanced AI. Today, it sits among the handful of companies shaping the industry's future and that's why this filing matters. It's one of the world's most influential AI labs beginning the transition from a privately funded research company to a business that may eventually answer to public shareholders. For most of the AI boom, the biggest bets were made behind closed doors. Venture firms, sovereign wealth funds, and tech giants supplied the capital while the public watched from the outside. Anthropic's filing suggests that era may be starting to change.