Why This Matters More Than You Think#

Right, let me start with something that’ll probably make you uncomfortable. Remember when you could trust what you saw on the telly? When a video of a politician saying something ridiculous actually meant they said it? Those days are gone, I’m afraid, and they’re not coming back.

We’re living in an era where artificial intelligence can make anyone appear to say or do anything. Videos that look absolutely real. Audio recordings that sound exactly like your boss, your prime minister, or your own grandmother. And here’s the really unsettling bit, you won’t be able to tell the difference just by looking or listening. This deepfake technology is reshaping our relationship with truth itself, and it’s happening right now, not in some distant sci-fi future.

The stakes couldn’t be higher. In 2024’s elections across the globe, we got a preview of what’s coming, and honestly, it was terrifying. We saw fake audio recordings of politicians released just days before crucial votes. We saw manipulated videos spread faster than fact-checkers could debunk them. This isn’t about robots taking over, it’s about whether you’ll be able to trust a video of a political candidate the night before an election, whether a phone call from your bank manager is actually from your bank manager, and whether reality is, well, real.

What Deepfakes Are Actually Used For (And What They’re Not)#

Let me paint you a picture of the legitimate uses first, because believe it or not, this technology isn’t inherently evil. It’s like a hammer, really useful for building a bookshelf, potentially deadly if you’re a villain in a crime drama.

Film studios use this technology to de-age actors for flashback scenes. Remember how they made Samuel L. Jackson look younger in those Marvel films? Medical researchers use it to create training simulations. It’s rather clever when used responsibly.

But here’s where things get dark. The overwhelming majority of deepfakes, about 96% according to some estimates, are used for nonconsensual intimate imagery. People, mostly women, having their faces placed onto explicit content without their permission. It’s horrifying, and it’s the most common application of this AI-generated content.

Then there’s the election interference. Bad actors use deepfakes to spread false information about politicians, creating videos of candidates saying racist things they never said. The goal isn’t even always to convince everyone, sometimes it’s just to create enough confusion that people don’t know what to believe anymore.

Financial fraud is exploding. Criminals use deepfake technology to impersonate executives and authorise fraudulent wire transfers. Imagine getting a video call from your company’s CEO asking you to urgently transfer £500,000. You can see their face, hear their voice, even recognise their mannerisms. Except it’s not really them, and that money is gone forever.

Before Deepfakes: A Brief History of Fakery#

Humans have been faking things since we learned to draw on cave walls, but the methods we had before were rubbish by comparison. Back in the day, if you wanted to manipulate a photo, you needed a dark room, steady hands, and hours of painstaking work. Stalin famously had people airbrushed out of photographs, but you needed actual artistic skill to pull it off.

When video came along, the bar got even higher. Film editing required expensive equipment and left obvious traces. In the 1990s, computer-generated imagery started making waves. Films like Forrest Gump famously inserted Tom Hanks into historical footage with President Kennedy, but it took months of work and cost millions.

The crucial difference was this: faking video content was expensive, time-consuming, and required specialised skills. That protective barrier has now completely collapsed.

The Evolution of Deepfakes: From Clunky to Terrifying#

The term “deepfake” first appeared on Reddit in late 2017, and those early attempts were pretty unconvincing. But here’s what made it revolutionary: the creator wasn’t using expensive Hollywood software. They used open-source artificial intelligence tools that anyone could download for free. Suddenly, creating fake videos wasn’t just for professionals anymore.

By 2019, things had improved dramatically. The faces started looking more natural, and apps appeared that could swap faces in real-time during video calls. Audio deepfakes emerged, particularly nasty because creating a convincing fake of someone’s voice became possible with just a few minutes of audio samples. Security experts started developing deepfake detection tools, playing a cat-and-mouse game with the creators.

Between 2021 and 2023, deepfakes became truly scary. The technology improved to the point where casual viewers couldn’t spot the fakes anymore. A deepfake video of Ukrainian President Zelenskyy appeared to show him surrendering to Russia during the invasion. Commercial applications exploded, but the same technology was being used to create increasingly sophisticated scams.

We’re now in what I’d call the “oh bloody hell” phase. Modern deepfakes are created using the same artificial intelligence systems that power ChatGPT. These newer systems don’t just swap faces, they can generate entirely synthetic people who never existed. Real-time deepfakes are now possible during live video calls. Detection has become incredibly difficult because modern systems specifically learn to avoid the mistakes that detection tools look for. It’s an arms race, and frankly, the creators are winning.

How Deepfakes Actually Work: The Step-by-Step Process#

Right, let me explain this in a way that won’t make your eyes glaze over. Imagine you’re trying to teach someone to forge your signature. But instead of a person, you’ve got two artificial intelligence programs, and instead of your signature, they’re learning to fake entire videos.

First, the system needs data, lots and lots of data. Hours of video footage from different angles, different lighting conditions, different expressions. This is why public figures are particularly vulnerable, there are thousands of hours of footage available online. But increasingly, even private individuals are at risk. Those hundreds of photos and videos you’ve posted on social media? That’s potentially enough training data.

The system uses something called Generative Adversarial Networks, or GANs. Think of it like two art students, one trying to forge a Rembrandt painting, the other trying to spot forgeries. The first creates a fake. The second tries to identify it. When the fake is spotted, they explain what gave it away. The first then creates a new, improved fake. This process repeats thousands of times. Eventually, the fakes become so good that the detector can’t tell the difference anymore.

Modern systems create a three-dimensional map of facial features, tracking everything down to tiny muscle movements. They replace faces frame by frame, making sure everything matches: the angle, the lighting, the movement, even the way the hair moves. Current systems add layers of refinement, adjusting skin texture, colour blending, and even adding natural imperfections that real videos have. They synchronise audio perfectly, creating entirely synthetic recordings that look and sound completely authentic.

The Future: Where This Is All Heading#

Buckle up, because this is where things get properly dystopian. Deepfakes are going to become utterly commonplace. We’re already seeing predictions that by 2026, a third of enterprises will have to abandon facial recognition systems because deepfakes have made them too unreliable. Biometric security, the thing we thought would replace passwords, is being rendered obsolete before it’s even fully rolled out.

We’re heading towards a world where every piece of digital media is suspect by default. That video your friend shared? Probably fake. That audio clip on the news? Could be synthetic. The election interference is going to get worse, much worse. Fake videos could be released hours before polls open, spreading on social media faster than they can be verified.

Detection technology will improve, but so will creation technology. We’re going to see an escalating battle, like antivirus software and computer viruses. Governments will step in with regulations, but enforcement will be nearly impossible. The technology is open-source and operates across international borders.

I hate to be melodramatic, but we might be heading towards a world where video evidence becomes legally inadmissible. If any video could plausibly be a deepfake, how can courts rely on it? How can journalism function? The optimistic view is that we’ll adapt, as humans always have. The pessimistic view is that the damage to social trust will be irreparable.

Security and Vulnerabilities: Why You Should Worry#

Let me be crystal clear about something: you’re vulnerable to this. Not just politicians and celebrities, you. Traditional identity theft involves someone stealing your details. Deepfake identity theft is infinitely worse. Criminals can create videos of “you” authorising payments or even confessing to crimes you didn’t commit.

I know someone whose business partner was targeted last year. The criminals created a fake video call from their company’s CEO, instructing a junior accountant to wire £200,000. The video quality was perfect, the voice was right, even the background showed the CEO’s actual office. The money was gone before anyone realised it was fake.

Here’s a vulnerability most people don’t consider: the mere existence of deepfakes gives people plausible deniability for real scandals. If a genuine video emerges of a politician doing something awful, they can simply claim it’s a deepfake. This creates a paradoxical situation where real evidence can be dismissed as fake, while fake evidence can be believed as real.

Criminals are using deepfake voice calls to trick people into revealing passwords, transferring money, or granting access to secure systems. The financial sector is particularly vulnerable, with fake videos and audio being used to manipulate stock markets.

What You Can Actually Do#

Right, enough doom and gloom. Here’s some practical advice. First, become sceptical of everything you see online, especially if it’s designed to make you angry or afraid. For video calls involving money or sensitive information, establish a verification protocol. Have a code word, ask a question only the real person would know, or use a secondary communication channel to confirm.

Keep your social media presence locked down. The less footage of you available online, the harder it is for someone to create a convincing deepfake. Stay informed about deepfakes circulating in your area, especially around election time. Follow reputable fact-checking organisations.

And perhaps most importantly, educate your family and friends, especially older relatives who might be more vulnerable to these scams. Awareness is your first line of defence.

If you work for a company, push for deepfake awareness training. Many organisations are woefully unprepared. Multi-factor authentication helps, but it’s not enough. Deepfakes can defeat biometric security like facial recognition and voice recognition. Traditional security measures were designed for a world where you could trust your senses. We’re not in that world anymore.

Wrapping This Up: Where We Go From Here#

So here we are. We’ve invented a technology that can make anyone appear to say or do anything, we’ve made it accessible to virtually everyone with an internet connection, and we’re only just beginning to grapple with the consequences.

The deepfake crisis isn’t coming, it’s here. We’re watching election interference happen in real-time. We’re seeing financial fraud explode. We’re witnessing the erosion of trust in digital media that took decades to build.

I wish I could end this on a cheerful note, but I’d be lying. The truth is, we’re entering uncharted territory. Previous generations had to learn that photos could be doctored and that you shouldn’t believe everything you read in the papers. We’re having to learn that seeing and hearing aren’t believing anymore, that reality itself requires verification.

But humans are adaptable creatures. We survived the printing press causing information chaos, we survived the internet democratising access to knowledge, and we’ll survive this too. It won’t be easy, and it’ll require us to fundamentally rethink how we verify truth. But we’ll manage.

The key is staying informed, staying sceptical, and staying engaged. Don’t let the technology intimidate you into giving up on truth altogether. That’s what the bad actors want. Instead, demand transparency, support detection efforts, and be willing to do the hard work of verification.

We’re all in this together, navigating a world where the digital truth is under assault from AI-generated content. It’s messy, it’s complicated, and it’s a bit terrifying if I’m honest. But awareness is the first step towards defence, and you’re now aware.

The battle for digital truth in 2025 and beyond isn’t going to be won by technology alone. It’ll be won by people, ordinary people, choosing to prioritise truth over convenience, verification over viral content, and reality over the comforting fiction that everything on their screens is real.

Stay sharp out there.

Walter