Social Media Trends Fuel AI Surveillance, Militarisation, and the Future of Targeted Hate
The Evolution of Fun: From Face Filters to Data Harvesting
Before Instagram turned into the curated feed of AI-generated content we see today, people were playing with altered versions of their own faces on TikTok. Its age-progression filter, which showed people's aging process in real time on-screen, quickly spread across platforms. What seemed like harmless fun became a massive dataset for training AI models to recognize human aging patterns. Big Tech monetises attention by extracting behavioural patterns, preferences, and biometric data extracted through photos, feeding them into algorithms that refine the predictive machinery of surveillance capitalism.
Over time, this infrastructure of "free" interaction becomes a training manual for building more invasive technologies using the images users upload to feel seen or validated, which teach machines to see us better than we see ourselves. When applied to generative AI, this dynamic no longer stops at fun family activities, advertising, content curation, or even data annotation; instead, it expands into training systems that can accurately predict and track human identities over time, transforming connection into control.
#10YearChallenge: Innocent Nostalgia or Mass Surveillance?
The logic of profit through data extraction extends seamlessly into viral social media trends that disguise surveillance as play. Take the infamous #10YearChallenge or #MeAt20 trends that flooded Twitter timelines around 2019, urging people to flaunt their decade-long "glow-up" with photographic evidence. What seems like a harmless exercise in nostalgia could be a mass effort to submit data voluntarily. These trends masquerade as acts of creativity or remembrance, but are really engineered nostalgia traps that draw users in under the guise of emotional connection while harvesting intimate biometric data.
More recently, with the commercialisation of generative AI, social media platforms are saturated with AI-generated imagery that blurs the boundaries between real memory and manipulation. Google's Gemini appears to be leading this commercial wave, driving trends that turn people's wedding photos into Ghibli-style art, or the latest update, Nano Banana, enables users to generate Polaroid-like images of themselves with their younger selves, a celebrity crush, or even a deceased relative. Each interaction further distorts our perception of reality, allowing AI systems to perfect that illusion with every new image they generate.
Fun-For-Data to Militarise Identity
The price of participation, though invisible, is far from free. Each image uploaded, for example, to generate a Polaroid image of oneself with their younger self, feeds the vast data pipelines that train AI to recognise patterns in human appearance over time, i.e., from childhood to adulthood – information that now sits in the hands of anyone willing to pay for access. Research into face-age estimation models shows that large datasets of age-annotated or age-progressed face images are already used to train models to recognise how individuals age across ethnicities and are helpful in "intelligent surveillance" and other industries.
Strategically and from an economic standpoint, social media trends such as the Polaroid-style images or the earlier #10YearChallenge appear to be an ideal mechanism for encouraging people to contribute publicly available data that can help fill the research gaps around how people age under different conditions, and enable corporations to scrape that data without consequence in order to train AI models that are being used far beyond simple text or image queries. The applications of such datasets and resulting trained AI models are equally vast – many venture into policing, including implementation at borders and in law enforcement for profiling in the name of 'predictive threat assessment', as well as in militarised technologies to surveil and target individuals across different lifecycle stages.
From Social Media to Kill Lists: AI in Warfare
What begins as a cultural moment of connection through images ultimately reinforces the infrastructure of surveillance capitalism and ties directly into the militarised applications of predictive identity technologies. For instance, research has explored the wide variety of potential applications of AI in defence settings – from autonomous drones to target identification – stressing the need for policymaking informed by public attitudes to ensure responsible governance. A practical example of this application has been documented in Palestine, where the Israeli Defense Forces used AI-powered systems like Lavender, Where's Daddy, and others to prepare a "kill list" and target Palestinians.
Investigators found that operators sometimes approved a strike in as little as 20 seconds. These technologies, in part, have been enabled by Big Tech companies like Google that grant the Israel Defense Forces (IDF) access to Google Photos' facial recognition data to instrumentalise the so-called kill list against Palestinians. In this context, social media trends that generate vast quantities of biometric data (including age-progression) become more than cultural quirks and turn into training material for models that can reidentify, predict, and track individuals over time. As biometric surveillance migrates from policing on borders and in cities to warfare, the implications for communities already subject to profiling, especially in the global South, become all-the-more sinister.
The Rise of Weaponised AI and Targeted Hate
The work of fact-checkers has grown significantly more challenging during the genocide in Palestine, as the Israeli occupation has relied heavily on artificial intelligence to disseminate misinformation. The current war of extermination has marked a turning point in the spread of misinformation, with artificial intelligence playing a central role. Israeli media and official institutions employed an army of supporter accounts and fake accounts, exploiting one of the tools of the world of artificial intelligence, which are fake accounts driven by artificial intelligence, known as bots. These bots were programmed to post comments and articles supporting the occupation and undermining Palestinian rights across various platforms, particularly Facebook, X, and Instagram.
On May 29, Meta reported the removal of a network of hundreds of fake accounts linked to an Israeli company named STOIC, based in Tel Aviv. These accounts, driven by AI, were used to amplify Israeli propaganda and disseminate false claims, especially targeting Arabic-speaking audiences. A day later, on May 30, OpenAI, the developer of ChatGPT, announced that it had banned another group of accounts operated by the same company. These accounts had used AI to impersonate Jewish students and African American citizens in an effort to make their messages appear authentic and diverse. This weaponisation of AI extends beyond disinformation to directly fuel targeted hate, as fake accounts amplify divisive rhetoric and sow discord.
The Self-Sustaining Algorithm: Shifting from Collection to Exploitation
At this point, it no longer matters whether someone participated in a specific social media trend contributing to training datasets for AI models. The reality is that once sufficient data has been gathered, machine learning tools can predict human ageing patterns with little additional input and with high accuracy. In other words, the saturated pool of voluntary image contributions may prompt a shift from data collection to data exploitation, where algorithms become self-sustaining, only requiring minimal new input to generate far-reaching predictions. This is occurring in a country where the right to privacy is weak and digital oversight is minimal. Voluntarily sharing age-progressed images can easily feed into emerging predictive tools, with real-world consequences for surveillance, profiling, and social control.
It is within the realm of possibility that AI-enabled military grade surveillance technology which identifies individuals accurately over time as they age, could be weaponised in a country where the focus of policymakers and law enforcement authorities is to control citizens rather than protect them, in which the state has already spent millions of dollars on military grade surveillance technology to use against civilians in the name of 'national security'. What appears innocuous today in the form of aging filters, nostalgia trends, or image sharing will strengthen existing systems of oppression for tomorrow. The fusion of social media trends, AI surveillance, and militarisation represents a profound shift in how our digital footprints are exploited, ultimately paving the way for targeted hate that undermines the very fabric of democratic societies.