Hey everyone, welcome back to My Weird Prompts. I am Corn, and I am sitting here in our living room in Jerusalem with my brother.
Herman Poppleberry, at your service. It is a beautiful evening outside, but we are keeping it pretty serious in here today. Our housemate Daniel sent us a voice note that really gets into the weeds of digital identity and the high stakes of modern whistleblowing.
Yeah, Daniel has been on a bit of a roll lately with these investigative themes. If you heard a recent episode, we were talking about covert evidence gathering. Today, we are looking at the flip side of that coin. How do you tell the truth without getting caught?
It is the art of obfuscation. And specifically, how artificial intelligence is changing the game for people who need to stay anonymous. We are talking about journalists, whistleblowers, and even regular people in places with very strict defamation laws.
It is interesting because when we think about AI and identity, we usually think about deepfakes being used for scams or misinformation. But Daniel is pointing us toward a much more noble, if technically complex, use case. Using AI as a shield rather than a sword.
Exactly. Traditionally, if you were a whistleblower appearing on a news program like Sixty Minutes, the techniques were pretty crude. You would sit in a dark room, backlit so you were just a silhouette. Maybe you would wear a wig or a hat. And then they would use a voice modulator that made you sound like a robot or a witness protection program stereotype.
Right, and the problem with those traditional methods is that they are actually quite distracting. As a viewer, you lose all the human connection. You cannot see the person's eyes, you cannot see their facial expressions, and the distorted voice makes it hard to feel the emotion or the urgency of what they are saying. It creates a barrier between the source and the audience.
Not only that, but those old methods are surprisingly easy to reverse-engineer now. If the lighting is not perfect, modern image processing can sometimes pull details out of the shadows. And voice modulation? There are algorithms now that can strip away those pitch-shifting filters and reconstruct a significant portion of the original vocal characteristics. It is no longer a safe way to hide.
So that is where AI comes in. Instead of just hiding the person, we are talking about replacing them with a synthetic version of themselves.
Precisely. We are seeing the rise of what you might call synthetic personas. Imagine a whistleblower who wants to expose corporate corruption. Instead of the silhouette in the dark room, they use a high-fidelity AI avatar. This avatar can mimic their exact facial expressions, their micro-movements, and the cadence of their speech, but the face itself is entirely generated. It is a person who does not exist, but who is expressing the very real emotions of the source.
That is a massive shift. You are essentially decoupling the message from the physical identity while keeping the humanity intact. I can see why Daniel is so excited about this. It feels like a way to level the playing field. But Herman, how does this actually work under the hood? How do you ensure that the AI persona does not accidentally leak the original person's features?
That is the technical challenge. It usually involves a process called facial re-enactment or neural head avatars, often using technologies like Gaussian Splatting or Neural Radiance Fields. The system maps the source's facial landmarks, things like the corners of the mouth, the position of the eyelids, and the bridge of the nose. It then applies those movements to a completely different latent representation of a face.
So it is like a digital puppet?
In a way, yes. But a very sophisticated one. The key is to ensure that the skeletal structure of the face, the underlying geometry, is changed enough so that biometric software cannot match it back to the original person. If you just skin a new face over the old bone structure, some advanced recognition systems might still find a match based on the distance between the eyes or the shape of the jawline. You have to literally reshape the digital skull.
That makes sense. And what about the voice? Because Daniel mentioned voice modulation in his prompt as well.
Voice is actually even more fascinating. Instead of just shifting the pitch, AI can perform what is called speech-to-speech synthesis. The whistleblower speaks into a microphone, and the AI analyzes the linguistic content and the prosody, which is the rhythm and intonation. Then, it re-synthesizes that exact speech using a completely different vocal profile. It is not a filter; it is a brand new voice speaking the same words with the same feeling.
So you could have a middle-aged man in London speaking, but the output sounds like a young woman from New York, and it would sound completely natural. No robotic artifacts, no weird humming in the background.
Exactly. And that is crucial for trust. If a whistleblower sounds like a human, their story carries more weight. But this brings us to the second part of what Daniel was asking about, and this is where it gets really thorny. The issue of watermarking.
Right. We have seen a lot of push lately from companies like OpenAI, Google, and Meta to include digital watermarks in AI-generated content. There are also regulatory efforts to mandate transparency in AI-generated media. The idea is to prevent misinformation by making it clear when something is made by a machine. But for a whistleblower using an AI persona to hide from a powerful government, that watermark could be a death sentence, couldn't it?
That is the fear. There are two main types of watermarking we are seeing right now. There is metadata-based watermarking, which is like the C two P A standard, where the file itself contains a record of its origin. That is relatively easy to strip away if you know what you are doing. But then there is invisible, pixel-level watermarking, like Google's SynthID.
Those are the ones that are embedded directly into the image or the audio, right? Even if you crop it or compress it, the watermark remains.
Precisely. These watermarks are often hidden in the frequency domain of the image or the audio. To a human, it looks or sounds perfect. But to a detector, there is a specific pattern that says, this was generated by model X on date Y. Now, if you are a whistleblower, you might think you are safe because you are using a fake face. But if that fake face carries a hidden serial number that can be traced back to your specific account or your specific session with the AI service, your anonymity is gone.
Wow. So the very tool meant to protect you becomes a beacon for anyone trying to find you. If a government gets a subpoena for the logs associated with that specific watermark, they can see exactly who generated that video.
Exactly. It creates a massive paradox. We want watermarking to protect society from deepfake scams, but that same technology could dismantle the safety of people who are using AI for legitimate, life-saving obfuscation. It is a classic case of a technology having unintended second-order effects. The E U AI Act also mandates this kind of transparency, which makes it very difficult to find a legal, un-watermarked tool.
It reminds me of the early days of the internet when people thought P G P encryption was only for criminals. Eventually, we realized that everyone needs privacy. But here, the stakes feel even higher because the technology is so much more pervasive.
And Daniel mentioned something very specific to our neck of the woods here in Jerusalem. He talked about defamation laws. In some jurisdictions, including Israel, the laws around defamation can be quite strict. Under the Prohibition of Defamation Law, the truth is not always an absolute defense. You often have to prove that there was also a public interest in the publication. The legal costs of defending yourself against a wealthy individual or a corporation can be ruinous.
I have noticed that too. People here are sometimes hesitant to even leave a negative review on a business because they are afraid of getting slapped with a lawsuit. It has a real chilling effect on free speech.
It really does. So if you are a whistleblower in a country with those kinds of laws, you are not just worried about physical safety; you are worried about financial annihilation. Using an AI persona to tell your story might be the only way you feel safe enough to speak up. But if the AI companies are forced by law to include traceable watermarks, that safety is an illusion.
So what is the solution? Is there a way to have ethical AI obfuscation that does not leave a trail?
That is the billion-dollar question. Some researchers are looking into what they call adversarial watermarking or watermark removal. It is an arms race. One AI puts the watermark in, and another AI tries to find it and scrub it out using techniques like diffusion-based reconstruction without destroying the quality of the video.
That sounds like it could lead to a lot of digital noise.
It can. But there is also a move toward open-source models. If you run an AI model locally on your own hardware, you can, in theory, disable the watermarking features. This is why the debate over open-source AI is so important. If the only AI we have access to is controlled by a few large corporations who are integrated with government surveillance, then the potential for using AI as a tool for freedom is severely limited.
That is a great point. We talked about this in a previous episode about the agentic mesh. If these AI agents are all talking to each other and reporting back to a central hub, privacy becomes almost impossible.
Exactly. And let's look at the actual techniques of obfuscation beyond just the face and voice. There is also linguistic obfuscation. Even if you hide your face and change your voice, the way you use language can give you away. We all have a linguistic fingerprint, certain words we use, the way we structure our sentences, our common typos.
I remember reading about that. Stylometry, right? They used it to identify the Unabomber and even to suggest who might have written the Federalist Papers.
Precisely. And modern AI is incredibly good at stylometry. But it is also incredibly good at the opposite: style transfer. A whistleblower can take their written statement and ask an AI to rewrite it in the style of, say, a technical manual or a different dialect. This strips away those linguistic fingerprints.
So you are obfuscating at every layer. The visual, the auditory, and the conceptual. It is like building a multi-layered fortress around your identity.
It is. But every layer has a potential leak. For example, even if you change the style of the text, the specific facts you mention might only be known to a handful of people. That is what we call operational security, or op-sec. No amount of AI can save you if you mention a detail that only three people in the world know.
Right, that is the human element. You can have the best digital mask in the world, but if you leave a trail of breadcrumbs in the content of your message, you are still in trouble.
And that is where the intersection of AI and journalism gets really interesting. Investigative journalists have to be experts at protecting their sources. They are now having to learn how to use these AI tools to help their sources stay safe. It is not just about a hidden camera anymore; it is about managing the digital metadata of the entire interaction.
It feels like we are moving into a world where reality itself is becoming negotiable. If we can create these perfect synthetic personas for good reasons, how do we tell them apart from the ones created for bad reasons?
That is the core of the watermarking debate. If we allow whistleblowers to use un-watermarked AI, then we are also allowing bad actors to use it. It is the same old trade-off between security and liberty. But in this case, the lack of a watermark might be the only thing keeping a brave person out of prison.
I want to go back to something Daniel said in his prompt. He mentioned that sunshine is the best disinfectant. He believes in the power of journalism to bring wrongdoing to light. But he also acknowledged that he is an idealist. Do you think AI is ultimately going to make it easier or harder to bring those truths to light?
I think in the short term, it makes it easier. The tools to hide your identity are becoming more accessible and more effective than they have ever been. But in the long term, I worry about the erosion of trust. If every video of a whistleblower could be a synthetic creation, people might start to dismiss even the most important revelations as fake news.
The liar's dividend. We have talked about that before. The idea that once we know deepfakes exist, actual criminals can claim that real evidence against them is fake.
Exactly. It creates this fog of war where nobody knows what to believe. And that environment actually favors the powerful. If you are a big corporation or a corrupt government, you do not necessarily need to prove you are innocent. You just need to create enough doubt so that the public stops caring.
So the whistleblower uses AI to protect themselves, but the very use of that AI gives the target an excuse to say the whole thing is a fabrication. It is a really difficult spot to be in.
It is. And that is why the role of the journalist is more important than ever. The journalist provides the verification. They are the ones who can say, I have met this person in real life, I have verified their documents, and I am using this AI persona to protect them, but I vouch for the truth of their story.
So the human connection is still the foundation, even if the delivery is synthetic.
Exactly. You cannot remove the human from the loop. If you do, the whole thing falls apart.
Let's talk about some practical takeaways for people who might be interested in this. Not necessarily because they are whistleblowers, but because they care about their digital privacy. What can the average person do to understand how their identity is being tracked or obfuscated?
Well, the first thing is to be aware of metadata. Every photo you take with your phone has a ton of hidden information: the G P S coordinates, the time, the type of phone, even the settings of the camera. Before you share anything sensitive, you should use a tool to strip that metadata.
That is a basic one, but so many people forget it. What about the AI side of things?
If you are using AI tools, read the terms of service. I know, nobody does that. But you need to know if the company is watermarking your output and if they are keeping logs of your prompts. If you are looking for true privacy, you might want to look into running models locally on your own hardware, as I mentioned. There are some great open-source projects like Llama or Stable Diffusion that you can run on a decent home computer.
And what about the legal side? If someone is in a place like Israel or somewhere else with strict defamation laws, what should they be thinking about?
They should be thinking about the concept of anonymous speech as a right. But they should also be aware that anonymity is very hard to maintain against a determined adversary with a legal team. If you are going to speak out, do it through established channels. Talk to a journalist who has a history of protecting sources. Do not just post it on a random forum and hope for the best.
That is solid advice. It is about being smart about the tools you use and the people you trust.
Precisely. And I think we are going to see a lot more development in this area. There is a new field emerging called privacy-preserving machine learning. It is all about how to train and use AI models without ever seeing the raw, private data. Things like federated learning and differential privacy.
Differential privacy is an interesting one. That is where you add a specific amount of mathematical noise to a dataset so that you can extract general patterns without being able to identify any specific individual, right?
Exactly. Apple and Google already use this for things like predicting what you are going to type next or identifying popular emojis. It is a way to get the benefits of big data without the privacy nightmares. Imagine applying that to video. Adding just enough noise to a face so that a human can recognize it, but a computer cannot.
That sounds like a much more sophisticated version of the old pixelated face.
It is. It is pixelation with a P h D.
I like that. So, looking ahead, where do you see this going in the next few years? We are in early twenty twenty-six now. What does twenty twenty-eight look like for a whistleblower?
I think we will see the first major news story where the primary source is a fully synthetic AI persona, and it will be accepted as a normal part of journalism. We might even see specialized agencies that provide these synthetic identities to people in need. Almost like a digital version of the underground railroad.
That is a powerful image. But I can also see the dark side. Governments using that same technology to create fake whistleblowers to entrap people or to spread disinformation.
Oh, absolutely. The tools of liberation are always the tools of oppression in the wrong hands. It is the eternal struggle. But that is why we have to keep talking about it. That is why prompts like Daniel's are so important. We cannot let these technologies develop in the dark.
Well said, Herman. I think we have covered a lot of ground today. From the crude silhouettes of the past to the high-fidelity AI personas of the future, and the complicated, invisible world of digital watermarking.
It is a lot to take in, but it is the world we are living in. If you are listening to this and you found it interesting, or if you have your own thoughts on AI and privacy, we would love to hear from you.
Yeah, and if you have been enjoying My Weird Prompts, please take a moment to leave us a review on your podcast app or on Spotify. It really does help other people find the show. We have been doing this for a while now, and it is the support of our listeners that keeps us going.
It really does. And don't forget to check out our website at myweirdprompts.com. You can find all our past episodes there and a contact form if you want to send us your own weird prompt.
Thanks to Daniel for sending this one in. It definitely gave us a lot to chew on.
It did indeed. Alright, I think that is a wrap for today.
Thanks for listening, everyone. We will be back next week with another deep dive. Until then, stay curious.
And stay safe. This has been My Weird Prompts. Bye for now!
Bye!
