In a world where avatars and AI-generated content are the norm, how do we tell the difference between fake and real?
With digital twins creating content in seconds and deepfakes spreading at lightning speed, the question is no longer if we’ll encounter fake content—it’s whether we’ll even recognise it when we do.
I grew up in a time when news videos and images felt authentic, untouched by manipulation. But today, a fake video of a politician can be created in minutes and believed by millions, with consequences ranging from misinformation to political unrest.
The bigger problem? Technology is advancing so quickly that even tech-savvy adults struggle to differentiate fact from fiction—let alone children. This leads to a fundamental question: What does “real” even mean?
Oxford Dictionary defines “real” as “existing in fact and not imaginary” or “being what it appears to be and not false.” But these lines blur when we accept minor manipulations as normal. Take food ads, for example—cereal never looks like it does in commercials, but we’ve learned to shrug and move on.
Should we apply the same tolerance to news? A photo of a small protest might be taken from an angle that makes it appear massive. The image isn’t fake, but the context is misleading.
Where, then, is the boundary between manipulation and outright fakery?
“Fake,” by definition, is “not genuine; imitation or counterfeit.” Filters, lens effects, and editing techniques fall into a gray zone—are they real, or are they fake?
As AI continues to generate more of the content we consume, the risk of misinformation grows. Repeated exposure to fake news can erode trust in media altogether.
To avoid this, distinguishing real from fake must be a collective effort across education, technology, and policy.
So, how do we fix this?
Here’s how we can start addressing the issue:
Education:
Teach people how to verify sources, think critically, and cross-check information.
Incorporate media literacy into school curriculums to prepare the next generation.
Technology:
Blockchain-based systems can verify when and where content was created, but they can't confirm if it's genuine.
Develop advanced software to detect fake videos and images.
Policy:
Media organisations should have dedicated teams for AI detection and fact-checking, with clear guidelines for content authentication.
Labelling / watermarking of edited or AI-generated content
Governments need laws addressing deepfakes and penalties for those who create them.
Campaigns using AI-generated content should disclose it transparently.
The question isn’t whether fake content will exist—it’s whether we’ll be able to recognise it.
It’s critical to ask ourselves: What kind of world do we want to build?
The future depends on how we answer these questions.
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