For most of human history, evidence for us was simple and basically if you saw something with your own eyes, it meant it was probably real.
If you heard a familiar voice, it belonged to a real person.
If a video existed, it meant that moment happened, and so on.
The internet we first saw just inherited those assumptions. Cameras didn’t just capture reality, but they validated it, recording was proof, screenshots settled arguments, video calls built trust…Well, today we can safely say that era is over.
Not gradually and not hypothetically. It’s just already gone forever.
And the most uncomfortable part is that technology didn’t break the internet but did something more: it broke reality verification itself.
The quiet collapse of “proof”
Deepfakes didn’t arrive with a bang. They didn’t need to.
At first, they were clumsy, bad lip syncing, uncanny eyes, artifacts everywhere…We laughed at them, shared them as curiosities, dismissed them as toys. It was just fun!
But in our tech world, tools improved faster than social instincts, and today, voice cloning takes seconds and a short audioclip is enough to reproduce tone, cadence or even emotional nuance. Video generation no longer needs Hollywood budgets. Real time face substitution during live calls is no longer science fiction but a basic feature.
The result isn’t chaos but something much worse called uncertainty.
Because the real danger of deepfakes is not that people will believe everything. It’s that they won’t know what to believe at all.
When evidence becomes ambiguous
Imagine receiving a video of your CEO announcing layoffs, a call from a family of yours asking for urgent financial help, or a leaked recording that perfectly matches someone’s voice and mannerisms.
Just around ten years ago, verification was straightforward but it’s quite scary that today even experts sometimes hesitate.
This creates a new default state for the internet that means plausible deniability is simply everywhere.
Real videos can be dismissed as fake. Fake ones can pass as real. Truth becomes negotiable, contextual, tribal. Evidence stops being decisive and starts being political.
And this shift doesn’t require malicious intent at scale. It only requires enough believable noise.
Why this is a developer problem (whether we like it or not)
It is actually tempting to frame deepfakes as a policy problem, or a media literacy problem, or a “bad actors” problem, but deepfakes are fundamentally a software problem.
They basically exist because we optimized relentlessly for the following things:
*Better models
*Lower latency
*Higher fidelity
*Easier access
*Fewer constraints
All good engineering goals, all rational in isolation, yet combined they produced a world where authenticity is no longer detectable by humans alone.
Most developers didn’t intend this outcome but the truth is that intention doesn’t change impact.
We built systems that are very good at generating reality and almost nonexistent at proving it.
The asymmetry no one talks about
Maybe the part that makes this problem especially dangerous might be that creating a convincing fake is becoming easier every year and on the other hand proving something is real is becoming harder.
That asymmetry matters.
We live in a world where attackers only need to succeed once, defenders need certainty every time, platforms can’t fact check at the speed content is generated, fact checking is also sometimes just not accurate and humans can’t analyze metadata while scrolling.
All this creates a structural advantage for misinformation, fraud, and manipulation of truth even when nobody fully trusts what they’re seeing.
The psychological cost of permanent doubt
There is a hidden human cost to all of this because when people stop trusting evidence they stop trusting institutions, and when they stop trusting institutions, they retreat to tribes and the world becomes much more authentically polarised.
When everything can be fake or only partially true, everything becomes emotional.
You don’t argue facts anymore, you argue identity, and that great erosion doesn’t stay online but spills into courts, elections, private business, markets, and even personal relationships.
The irony here is brutal because while technology is designed to connect us, it ends up isolating us inside belief bubbles reinforced by uncertainty.
Can authenticity be rebuilt?
There are technical responses emerging. Things like cryptographic signatures for media, hardware level provenance, content authenticity frameworks or watermarking. All of them can for sure help but at the same time none of them solve the core issue alone.
Because this is not just a technical gap. It’s a trust gap.
Verification needs to become invisible, automatic, and culturally understood in the same way HTTPS quietly replaced HTTP without users needing to care. Until that happens, deepfakes or damaging partial truths will continue to outpace defenses. And even then, social adaptation will lag behind technical capability as it always does.
The uncomfortable question
At some point developers have to ask this uncomfortable question: Just because we can generate reality indistinguishable from truth, should that be the default?
This is not about stopping progress but about acknowledging that capability without guardrails reshapes society, not always in positive ways or ways we can clearly anticipate.
Deepfakes didn’t just change the internet but they changed how humans decide what is real and what is not. And once that line blurs, it’s very hard to redraw.