It starts with a video.
A politician making claims they never said.
A celebrity endorsing a product they’ve never used.
A friend is sending a voice note that… feels off.
But there’s no glitch. No obvious clue it’s fake.
Just pixels. Flawless. Frictionless. Fiction.
Welcome to the deepfake era, where synthetic media is no longer a novelty but a clear and present danger. In a world where seeing is no longer believing, the rules of trust, truth, and accountability are being rewritten in real time.
The Harm Is Real, Even When the Fake Is Exposed
“Even corrected fakes can harm reputations through the continuing influence effect.”
The continuing influence effect (CIE) means people still believe misinformation—even after it's been debunked. That’s what makes deepfakes uniquely dangerous: damage persists, long after truth arrives.
For Spindt, regulation must be direct and uncompromising:
Remove deepfakes made without legal consent
Enforce accountability for creators and distributors
Make digital watermarking mandatory
Penalize repeat offenders with escalating consequences
“The best ethical response is automated detection, fines, and escalating penalties... especially for creators who omit watermarks.”
Consent, Identity, and the Emotional Toll
“It is not for fun... it is so dangerous.”
— Jarrod Teo
Jarrod Teo avoids uploading any likeness of himself. No AI selfies, no filters, no voice recordings. Even gestures like a thumbs-up can be weaponized. In an era where your image can be cloned at scale, identity becomes vulnerability.
Meanwhile, Srinivas Chippagiri sees the potential of deepfakes—to enhance education, accessibility, and creative storytelling—but only with consent and ethical design.
“In a world where seeing is no longer believing, redefining trust in digital content becomes urgent.”
His prescription includes:
Developer safeguards
Platform-level detection
Shared responsibility across the ecosystem
AI that doesn’t just create, but defends against misuse
Infrastructure, Platforms, and the Need for New Guardrails
Hemant Soni raises the alarm for telecom and enterprise systems: voice and video fraud are growing attack surfaces. The solution? AI-driven anomaly detection, biometric validation, and systems that verify not just messages—but identities.
Dmytro Verner echoes this need at the infrastructure level. His focus: cryptographic provenance, labeling standards, and third-party verification.
“People will shift their trust from visual content to guarantor identity.”
He points to real-world initiatives like Adobe’s Content Authenticity Initiative, which adds cryptographic metadata to content for verification at the source.
Who’s Responsible? Everyone.
“Responsibility for deepfakes should begin with the developer and the company. But it’s an ethics partnership.”
— Brooke Tessman
“Leaving accountability to any single layer won’t work.”
Both Tessman and Suresh stress that shared governance is the only way forward.
Developers must build with ethical constraints
Platforms must monitor and intervene
Users must act with awareness
Lawmakers must ensure consequences match capabilities
“Digital content should carry clearer signals of authenticity… AI should help us detect, not just generate.”
— Nivedan Suresh
Truth Isn’t Plug-and-Play
“Deepfakes aren’t the problem. Our blind faith is.”
Rao reminds us: the real threat isn’t synthetic media, it’s synthetic belief. From television to TikTok, we’ve long trained ourselves to trust the screen.
“Truth is not plug-and-play, it still requires effort.” — Dr Anuradha Rao
AI tools can help. So can regulation and detection. But ultimately, human discernment is the last line of defense.
What Happens Next?
Deepfakes will get more convincing. Their reach will expand. But our defense tools, if aligned, can keep up:
Mandate watermarking and provenance tagging
Deploy AI-powered detection across platforms
Enforce legal consequences for misuse
Elevate digital literacy for all users
If we act now, we protect what’s real. If we wait, the fakes will define reality.
