Yes, it may be amusing to see a kitten apparently posing on Donald Trump’s knee. On its own, that sort of image feels harmless enough: a bit of internet theatre, a digital joke, a moment of absurdity. But it also trains the public to hesitate. People no longer simply laugh and move on. They ask: is this fake, is this real, has this been generated, edited or manipulated?
Seeing Is No Longer Believing
For generations, humanity placed unwavering trust in the evidence of its own eyes. A photograph served as irrefutable proof; a video, as unassailable testimony. If one could see an event unfold, it was presumed to have occurred.
Last week, the BBC Panorama programme, presented by Marianna Spring and titled Seeing Is Believing, confronted a profound shift in this long-held assumption. In an era of rapidly advancing artificial intelligence, the programme posed a sobering question: what happens when seeing is no longer believing?
The broadcast guided viewers through the expanding realm of AI-generated content that now permeates social media platforms. At first glance, much of this material appears innocuous and entertaining. Images of dancing dogs, talking fruit, impossibly agile infants, and cats voicing distinctly human perspectives populate feeds worldwide. Such absurdities align with the internet’s longstanding affection for the whimsical, now supercharged by accessible AI tools that grant anyone the power to animate the improbable.
Yet beneath this veneer of harmless amusement lies a more unsettling reality. The programme revealed how inexpensive and widely available AI technologies are being deployed for far more consequential purposes: fraudulent advertisements, cloned voices, fabricated celebrity endorsements, political propaganda, deepfake scams, and racially inflammatory disinformation. What begins as digital novelty evolves into a pervasive pollution of shared reality—an erosion of the very foundations upon which trust depends.
The term “AI slop” may carry a certain levity, yet it aptly describes the phenomenon of mass-produced, synthetic content engineered primarily to capture attention, elicit emotional responses, and generate revenue. Authenticity is irrelevant; clickability is paramount. Herein resides the core danger. A fabricated video that provokes laughter may be shared impulsively. A counterfeit advertisement featuring a familiar face or voice can result in financial loss. A manipulated political image that reinforces existing beliefs may intensify prejudice. A cloned voice mimicking a distressed loved one can serve as an instrument of extortion.
Artificial intelligence does not independently sow distrust; human actors do. However, AI equips those with malicious intent with unprecedented efficiency—a factory for deception. What once demanded considerable skill, time, and specialised equipment can now be accomplished swiftly, at scale, and with remarkable fidelity.
This development carries particular significance for politics and journalism. Democratic societies rely upon a common foundation of verifiable facts. When every image can be contested as potentially fabricated and every fabrication defended as possibly authentic, public discourse transforms into a hall of mirrors. Deceivers acquire convenient avenues of escape—“It cannot be proven”—while those upholding truth bear an ever-heavier burden of verification.
The resulting exhaustion fosters disengagement. Individuals retreat into familiar ideological circles, prioritising what feels correct over what can be substantiated. Algorithms, attuned to engagement metrics, amplify this cycle, as emotional provocation proves highly effective fuel.
Panorama did not portray artificial intelligence as inherently malevolent. On the contrary, the technology offers substantial benefits: enhancing creativity for writers and artists, supporting researchers, assisting individuals with disabilities, and empowering small enterprises and everyday users with tools once reserved for professionals. The innovation itself is neutral; the concerns centre on power, accountability, and trust.
Fundamental questions arise: Who benefits from the proliferation of synthetic content? Who bears responsibility for its moderation and removal? What mechanisms ensure proper labelling? How should platforms safeguard the public when deceptive material appears in prominent spaces? Accountability cannot be evaded by attributing outcomes solely to algorithmic processes. The very platforms that cultivated an attention-driven economy now reap its consequences and must address the synthetic fog filling their systems.
The appropriate response is neither panic nor resignation, but informed vigilance. Society requires a renewed digital literacy—an instinct for caution rather than outright cynicism. Simple practices such as reverse image searches, consultation of reputable sources, and deliberate pauses before sharing represent essential acts of self-protection.
Educational institutions should incorporate these skills into curricula. News organisations must continue to illuminate the issue. Governments have a role in regulating egregious abuses, while platforms should be held to higher standards of transparency, rapid response, and responsibility.
The longstanding internet maxim advised against believing everything one reads. The contemporary imperative is more demanding: one must exercise discernment regarding everything seen, heard, or inclined to share.
Panorama’s Seeing Is Believing transcended a mere examination of artificial intelligence. It addressed the editable nature of reality itself in the digital age. While dancing dogs and talking fruit may entertain, they signal a deeper challenge: when screens can deceive with near-perfection, how does society preserve fidelity to truth?
The resolution may lie in recognising that seeing alone is no longer sufficient. Verification has become indispensable.
