Practical · Adult-facing · Defensive habits

Spot the fake. And the call. And the email.

AI now lets bad actors fake faces, voices, video calls, and writing styles convincingly enough to move money, harvest credentials, and start "relationships." Most attacks use the same playbook. The defense is a small set of habits.

A person at a desk holding a magnifying glass over a phone, examining a video-call portrait

This used to be a movie-studio problem. Now it's a phone-call problem.

Two years ago, faking a voice took specialist software and a long sample. Today an open tool clones a voice from three seconds of audio. Faking a face on a live video call is similarly cheap. The fraud reports have caught up.

Real case · Hong Kong, Feb 2024

$25 million wired after a deepfake video call.

An employee at a multinational firm joined a video conference with the "CFO" and other "colleagues." Every face was a deepfake; the employee was the only real person there. They authorized 15 transfers totaling about HK$200M (~US$25M) before the firm realized none of those people had actually been on the call.

Coverage: CNN · South China Morning Post.

Voice cloning · FBI advisory

"Your kid is in trouble" calls are mainstream.

The FBI's Internet Crime Complaint Center (IC3) has issued repeated alerts about voice-cloning scams: a parent receives a call that sounds exactly like their child or grandchild, in distress, asking for bail / accident / hospital money. The voice is real-cloned from a few seconds of social-media audio.

FBI public alerts: PSA 2024 · FBI San Francisco.

The good news: a small set of habits — the same ones IT teams drill into staff for phishing — defend against most of it. You don't have to spot the fake to be safe. You just have to slow down.

Four flavors of AI fake. Where each one slips up.

The tells differ by flavor. The cross-cutting defenses (covered below) are the same.

01

Fake faces & images

Generated photos, fake profile pics, doctored photographs.

Image generators can produce a person who has never existed, or doctor a real person into a scene they were never in. The tells are getting subtler — but still cluster in five categories of failure.

Flavor-specific habit: reverse-image-search any photo you're about to act on. If you can't find it elsewhere on the web, that itself is signal. Then check the five categories of tell ↓.

02

Fake voices

Cloned from three seconds of audio.

A worried person holds a red telephone receiver to their ear; a ghosted figure with a microphone stands behind, suggesting impersonation

This is the one to take seriously, because it preys on the people you love most. Almost always the script is the same: distress + urgency + money. "Mom — I crashed the car. Don't tell Dad. I need bail money."

Flavor-specific habit: ask a real-time question only the real person would know right now. ("What was the last thing we ate together?" "What's our cat's name?") AI doesn't have the context. A real person does instantly.

03

Fake video calls

Live deepfake faces on Zoom, Teams, FaceTime.

A laptop on a desk shows a single executive in a video conference window; the surrounding room is empty, suggesting the meeting isn't real

This is what got the Hong Kong firm. The caller looks and sounds like a person you know — sometimes multiple people you know — in a normal-looking conference window. Then they ask for an unusual transfer or an urgent approval.

Flavor-specific habit: ask them to do something hard to fake live. Wave a hand sideways across the face quickly. Turn fully sideways. Hold a finger close to the lens. Live deepfake models still glitch on sudden occlusion and unusual angles — the face will smear or distort momentarily.

04

Fake writing & impersonation

AI-polished phishing, written-style impersonation, romance scams.

Two things changed in the last two years. The broken-English phishing email is gone — AI fixes the spelling and grammar in seconds, so "the email reads weird" is no longer a reliable filter. And AI can now mimic a specific person's writing style from a sample.

Flavor-specific habit: filter on request shape, not language quality. Does it ask for money / credentials / unusual action / change of payment details? Did it arrive on the channel you'd expect? Polished writing is no longer proof.

Train your eye. Tap any image, see the tell.

Eight AI-generated examples, one tell each. From the Northwestern five-category taxonomy (Kamali, Black, Lin, Groh et al. 2024). Tap a card to study it; tap "reveal" for the hotspot circle and explanation.

Sources: Kamali, Black, Lin, Groh et al. (2024); Hany Farid's lab at UC Berkeley on lighting/shadow forensics. The example images here are AI-generated for teaching; the same tells apply to images you encounter in the wild.

The four habits that beat 95% of attacks.

The same playbook IT teams use against phishing — calibrated for the AI-fraud era. None of these requires you to spot the fake. They work even when the fake is perfect.

Establish a code word.

Pick a word you'd never use casually. Share it with your kids, partner, parents, finance team. The rule: any urgent request involving money or unusual action requires the code word. If the call sounds exactly like your daughter but she can't say the word — it isn't her.

Hang up. Call back on the number you have.

AI fakes the call coming in. It can't intercept your outbound call. Same principle for email: don't reply to the suspicious email; open a new one to the address you already have. Off-channel verification is the single best defense.

Treat urgency as a red flag.

Real emergencies survive a 60-second pause. Scams die in that minute. Anyone — family, boss, vendor, "tech support," "the IRS" — pressuring you to act now without verification is, by default, suspect. The smartest move under pressure is the slowest one.

Build the friction into team policy.

Most of the big losses (Hong Kong $25M, Arup $35M) happened because there was no policy-level requirement for callback verification on unusual transfers. Add the rule: any change in account details, any large transfer, any unusual approval — requires a callback on a known number. Ten minutes of friction prevents seven-figure losses.

If you remember nothing else
  • Polished writing, familiar voices, and recognizable faces are no longer proof of identity.
  • Most AI-enabled fraud follows the same pattern: impersonate someone you trust, manufacture urgency, request money / credentials / access.
  • Code word. Hang up & call back. Treat urgency as a red flag. Build the friction into team policy. These four habits beat 95% of attacks.

Where to go from here