AI in 5: Deepfakes in Schools: Fake Media, Real Harm (May 18, 2026)

What happens when a fake image, video, or audio clip looks real enough to destroy trust inside a school community? In this episode of AI in 5, AI Learning Guide JR dives into one of the fastest-growing concerns in education technology: deepfakes.

Deepfakes are AI-generated or AI-manipulated media designed to make someone appear to say or do something they never actually said or did. While the term once sounded like something reserved for celebrities or political campaigns, schools are now finding themselves directly impacted. Recent international reports detailed AI-generated explicit deepfakes targeting students, while cybersecurity experts are warning that schools are increasingly becoming targets for blackmail, harassment, and reputational attacks involving synthetic media.

This episode breaks down what deepfakes actually are in plain English, how they work, why they spread so quickly, and why educators, parents, and administrators need to prepare now—not later. JR explains why deepfakes are more than just “fake pictures on the internet.” They challenge the very foundation of trust schools rely on every day: trust between teachers and students, administrators and families, and communities and evidence itself.

Listeners will also learn practical response strategies schools can implement immediately, including how to avoid amplifying harmful content, preserve evidence correctly, support affected students, and begin building digital literacy programs focused on AI-generated media. The episode also explores why “seeing is believing” no longer works in the AI era and why AI literacy must evolve beyond simply learning how to use chatbots.

If your school, classroom, district, or family has not discussed deepfakes yet, this episode explains why that conversation can’t wait much longer.

🎙️ AI in 5 is part of AI Innovations Unleashed — helping educators, parents, students, and leaders make sense of the rapidly changing world of artificial intelligence, one episode at a time.

Sources referenced include reporting from ABC News Australia, Security Magazine, and ongoing AI ethics and digital safety research surrounding synthetic media and education.

Transcript

SPEAKER_00 0:00

What is a neural network? What is all these AI terms confusing you and me? It's AI. Making AI make sense.

SPEAKER_01 0:13

Imagine a student opens their phone between classes and sees a photo that, well, looks real. Real face, real name, real school setting, maybe even a group chat, already moving at the speed of teenage chaos, which is basically fiber internet with feelings. But the image is fake. The harm is not. That is the deep fake problem. It is no longer just a celebrity problem, a political problem, or something lurking in the weird basement of the internet next to crypto gorillas and conspiracy forums. It is now a school problem. Today on AI and 5, what is a deepfake? Why does it matter to schools right now? And what should educators, parents, and students do before a fake image, video, or audio clip becomes tomorrow morning's crisis meeting? Let's start off with defining a deepfake. It's an AI-generated or AI-maniped media that makes someone appear to say or do something they did not actually say or do. That media can be a video, it can be a photo, it can be audio. Plain English version. A deepfake is a digital impersonation. And no, this is not just Photoshop wearing a suspicious trench coat. Deepfakes can manufacture what looks like evidence. That is why they hit schools so hard. Schools run on trust. Teachers trust what students submit. Students trust adults to protect them. And families trust schools to respond when something goes sideways. Deepfakes attack that trust directly. In late April, ABC News reported that the girls at Friends School in Hobart, Tasmania, were targeted in an AI deepfake pornography incident, with parents saying police identified 21 victims. The same report noted that Tasmania's education minister referred a complaint about the school's handling of the incident to the non-government school regulator. Then on May 21st of this year, Security Magazine reported that cyber criminals were using images from school websites and social media to create explicit AI deepfakes of students in blackmail schools. In one UK-linked case cited through the Internet Watch Foundation, 150 generated images from a blackmail attempt were categorized as child sexual abuse material under UK law. That is the moment where this stops being a tech trend and becomes a student safety issue with a blinking red light. Not subtle, very much not subtle, like a fire alarm with a podcast subscription. So what makes deepfakes so different? Well, schools already know how to handle rumors, screenshots, bullying, and inappropriate post. But deepfakes are different because they blur the line between documentation and fabrication. If a fake image spreads, people may react before anyone verifies it. If a fake audio clip appears to show a threat, administrators may feel pressured to act immediately. If a fake video targets a teacher or a student, the damage can move faster than the truth. Danielle Citrin, a law professor and privacy scholar, warns in her TED Talk, not only do we believe fakes, we are starting to doubt the truth. That is the deep fake double whammy. First, people believe the fake things. Then, when real evidence appears, people start shrugging and saying, yeah, but is it AI? Congratulations, reality needs a hole pass. From the industry side, Sensity AI's Francesco Cavalli put it bluntly in 2026. Manipulation is scaling faster than verification, and trust itself is becoming a vulnerability. For schools, that means policies cannot wait until after the group chat detonates. So what can schools even do? What is a practical playbook for them? Well, here are five moves to help out. First, do not reshare. Even resharing to say this is awful can multiply the harm. The screenshot is not a public service announcement. It is gasoline with a caption. Second, preserve evidence safely. Document where it appeared, when it appeared, who reported it, and what platform posted it. Do not turn the entire faculty into forensic detectives with really bad coffee breath, but do keep it as a clean record. Third, report quickly through the school's safety, discipline, technology, and legal channels. If the content involves minors or explicit material, this may require law enforcement or child protection reporting. Fourth, support the targeted student or staff member as a person, not just as a part of an investigation. The media may be fake, but the shame, fear, anger, and isolation can be painfully real. And fifth, teach the community without turning the victim into the lesson. Deep fake literacy should be part of digital citizenship. Pause before sharing, verify before reacting, and understand that AI tools can create real-world harm even when the pixels are synthetic. Deep fakes are one of the clearest examples of why AI literacy cannot just be learn how to prompt better. AI literacy also means knowing when media can be manipulated, knowing how to slow down the share button, and knowing that the trust needs procedures, not panicking. For educators, this means having a response plan. For parents, it means talking with kids about image privacy and group chat behavior before the crisis. For students, it means understanding that creating or sharing a deepfake is not a prank. It can be harassment, abuse, blackmail, or even evidence of serious misconduct. So here is the one-line takeaway for today. A deepfake is fake media, but it can create real consequences. Schools do not need to become terrified of technology. They need to become prepared for it. And this has been AI in five on this May the 18th, a few days later. This has been JR, the AI Learning Tour Guide, and I will see you next week, where we will keep making AI make sense, preferably before the robots ask for substitute teacher credentials.

SPEAKER_00 7:08

What's the neural network? What is TPT? All these AI terms confusing you and me. It's AI.