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If the advancement of artificial intelligence (AI) has shown us anything, it’s that nothing is as it seems. It’s difficult to use any kind of social media platform without stumbling across deepfake content at some point or another.
According to Deloitte, deepfake fraud is expected to triple over the next three years and cost the economy $40 billion in damage by 2027.
So why are deepfakes exploding in such a way? Part of the reason for the spread of this content is that the technology to create synthetic voices is more accessible than ever. You can search for convincing deepfakes imitating human voices and public figures in a matter of minutes, usually with no sign-up required.
Exactly what this means for the Internet and society at large is not always easy to define.
What is clear is that we are going to have to learn to live in a world where human-created and synthetic content live side by side.
Key Takeaways
- The ease of use of AI voice generation tools has democratized content creation — but it also increases the risk of misinformation, fraud, and impersonation.
- Identifying voice deepfakes is becoming increasingly difficult, and while detection tools exist, no method is foolproof.
- Current AI regulations face enforcement challenges, and fraud is expected to triple between now and 2027.
- As AI content becomes more sophisticated, we must improve our ability to spot synthetic media, utilize detection tools, and verify information against trusted sources.
Why Voice Deepfakes Are Useful — And a Problem
Voice deepfakes are a problem for the internet because verifying who is saying what at a given time is becoming harder. This is particularly true on social media sites like X or TikTok, where it’s difficult to tell if a video is narrated by a human or synthetic voice.
Ken Miyachi, co-founder of BitMind, told Techopedia:
“Voice deepfakes have become widespread on social media due to the increasing accessibility of AI voice generation technology.
“The tools to create convincing voice imitations are now readily available to anyone, making it easy to produce and rapidly share synergic voice content across platforms.
“It’s significantly easier to create content with an AI-generated voice than to record yourself — and it enables massive amounts of content to be generated.”
At the same time, beyond being used for content creation, deepfakes can also be used to deliberately mislead people into thinking that a public figure endorsed a particular idea or action.
For instance, users can produce AI clips in public figures’ voices, saying things they’d never actually say, as the President Biden Robocall showed when an individual attempted to discourage Democrats from voting.
The Ethical Concerns of Voice Deepfakes
The ethics around voice deepfakes are also extremely complex. While it might be acceptable to use an AI-generated script with a synthetic voice to talk over a video, is it acceptable if that script uses the likeness of a public figure with a disclosure?
Probably not, and the answer to whether it is ok or not would likely come down to whether the individual consents to have their voice deepfaked.
However, that horse has bolted – you can find countless examples online of AI deepfakes being used to imitate the voices of public figures, and it is unlikely to stop any time soon. Case in point, this humorous AI-generated video of Trump’s voice being used as part of a fake orange juice commercial.
Miyachi said. “The ethical concerns surrounding voice deepfakes are significant. They can be used for identity theft, fraud, and malicious impersonation that damages reputations.
“There are also serious issues around consent, copyright infringement, and privacy violations when people’s voices are used without permission. These synthetic voices can erode trust in authentic digital content and potentially impact democratic processes through misinformation.”
Whatever way you slice it, deepfakes have eroded the connection between online audiences and human voices. There is an element of doubt that wasn’t there before, to a level that’s well beyond voice boards and other voice technology. The question now is what is to be done about it.
It’s hard to imagine AI regulations outlawing the production of synthetic content in any meaningful way, not when anyone can use a model to create them in a matter of minutes, and jailbreak models that attempt to skirt laws. After all, regulation hasn’t done much to slow down online piracy.
In the future, we will all need to get much better at spotting AI-generated content the way we’ve had to at navigating phishing scams. Knowing how to spot AI-generated content can help to avoid being misled by misinformation
One imperfect way to identify AI-generated voices is through their monotonous tone. Generally, AI-generated voices will speak in a monotone throughout, without much tonal variation, which is unlike most human dialogue, where the speaker emphasizes different words.
Likewise, the delivery of a voice deepfake will also usually come at a continuous speed. Real people pause to gather their thoughts, sometimes punctuating their sentences with “ums” and “ahs” whereas an AI model will power through a written script.
Given that these signs aren’t foolproof, we also recommend fact-checking information you see on social media against other more reliable sources to make sure it is correct.
There are also deepfake detection tools that you can use to analyze and identify voice deepfakes more reliably. However, it’s important to note that none of these techniques are silver bullets.
The Bottom Line
Voice deepfakes will be something that we just have to get used to. Now that anyone can generate voice clips with an AI model, we will all have to get much better at identifying AI voices.
The problem is that telling apart synthetic voices will steadily become much more difficult as AI continues to evolve. However, the silver lining is that AI-driven deepfake identification will likely improve too.
