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Practical Insights for Skeptics & Users Alike…in (Roughly) Two Minutes or Less

Deepfake It Till You Make It

In New Hampshire, President Joe Biden voters receive a phone call recorded in his “voice” telling them there was no need to vote in the then-upcoming Primary elections: "Your vote makes a difference in November, not this Tuesday," the voice said.

In March 2022, a video of Ukrainian President, Volodymyr Zelensky, depicted him telling his troops to surrender.

A U.S. company reportedly fell victim to a $10 million scam involving an audio of a CEO requesting a transfer of funds.

These three examples all share a common ancestor: they were generated by AI using deepfake technology—they were simply not real.

The problem, of course, is that this didn’t matter: many people were fooled.

Deepfakes are part of a broader category of synthetic media that uses artificial intelligence/machine learning to create realistic but fake videos, images, audio, and text. To complicate matters even further, the accessibility of deepfake technology is increasing, lowering the barrier for potential misuse.

A classic example that many of seen comes from the @DeepTomCruise account on TikTok.

The scary part? Even if this doesn’t impress you or fool you, note this: these deepfakes are three years old. The technology has come leaps and bounds since then.

What is the “Liar’s Dividend”?

The concept of the "Liar's Dividend" refers to a phenomenon in the current information environment where the widespread awareness of misinformation and deepfakes can be exploited by bad actors to evade accountability.

In other words as people become more aware of the existence of fake news and deepfakes, they may become more likely to doubt authentic evidence.

Subsequently, this allows liars to claim that real evidence against them is fake. The waters are chummed with enough uncertainty to toss reality itself out as tampered evidence.

The liar's dividend poses a significant problem for journalists and fact-checkers. Debunking efforts may inadvertently legitimize debates over the veracity of authentic content; trust in media further erodes and makes it harder for the public to distinguish between real and fake information—or, worse, to care whether something is fake or real in the first place.

Nothing is Real & Everything is Real

The issue isn’t just a purely political one.

For example, what stops companies from claiming "fake news" or manipulated content to deflect negative press or scandals.

What stops a CEO from, say, claiming that leaked internal documents or unfavorable financial reports are fabricated? Or that a recent eco-disaster is overblown?

Hey…Is your product facing safety issues or recalls? Why not claim the the negative test results are part of a larger misinformation campaign?

Small businesses in particular may be vulnerable reputational damage from false claims or negative reviews. The liar's dividend could make it harder for them to defend against fake reviews or false accusations, as their denials might be met with skepticism.

If a small business faces legal issues based on false claims, the liar's dividend could complicate their defense, as even proven innocence might not fully restore their reputation.

There's no single solution to the deepfake problem, but in tomorrow’s newsletter we’ll focus a bit on digital literacy, as well as a study from researchers at Standford University and other institutions who assessed the digital literacy skills of 3,446 high school students nationwide.

The results are sobering and highlight an urgent need for educational reform in the digital age.

Thanks for reading. See you tomorrow.

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