Artificial intelligence is now one of the singular most powerful arbiters of human rights across the globe. It is no longer an experimental technology operating at the margins of our world, but an active geopolitical force embedded in the molecular fabric of our society. For those tasked with anticipating, mitigating, and underwriting systemic threats, one truth is now unavoidable: AI risk is human risk.
This year’s United Nations’ call to Unite to End Digital Violence Against Women and Girls is a recognition that technology-facilitated abuse has become a transnational, high-impact risk category, and one that current governance frameworks are nowhere near containing. It calls attention to a fact which far too few practitioners have internalised: technological violence has real-world consequences.
From code to corporeality
We can already see the fact that the digital does not stay digital manifesting in the worst of possible ways. In Australia for one, 15-year-old Matilda “Tilly” Rosewarne died by suicide after a doctored nude image of her was circulated widely among peers on Snapchat and other platforms; a horrifying example of deepfake image-based abuse that started on a phone screen, and ended in her tragic demise. Similarly, in the United States in 2025, 16-year-old Elijah “Eli” Heacock took his own life after being sextorted using AI-generated nude photos of himself; material that never existed in reality, but which was real enough to terrorise him.
Women and underrepresented groups are demonstrably bearing the overarching brunt of digital violation. Research from UNESCO shows that online harassment has chilling effects on women’s participation in public life: 44% of female parliamentarians receive death and sexual violence threats, 30% of women journalists self-censor on social media, 20% withdraw completely, and over a quarter report negative mental health impacts linked to online violence. These are not fringe figures; they are professional realities that diminish societal resilience and democratic legitimacy. This also causes a dangerous negative feedback loop; the more that women are deterred from public service or bullied out of it, the less representative governments become. And as a litany of studies have shown, when representation suffers, outcomes, economies, policies, diplomacy and overall social equality suffers as a result.
One particularly urgent emerging category of digital violence against women and girls (DVAWG) is deepfake pornography. 96% of this is directed at women, with 99% of cases being sexualised. This isn’t merely another sexist genre of multimedia content; in her seminal book The New Age of Sexism: How AI is Reinventing Misogyny, Laura Bates has classed this as the next sexual violence epidemic facing schools and workplaces alike. Recently, X has been flooded with pornographic deepfakes made by the platform’s AI tool Grok, estimated at one nonconsensual image generated per minute, predominantly of women. When complaints are made, the tool issues “apologies” yet continues to generate further imagery. As founder of Full Fathom Five Claire Roberts said, “Musk’s move to restrict this to paying subscribers isn’t a safeguard, it’s a business model that treats the sexualisation of children as a premium feature”. Global backlash has now catalysed watchdogs from the UK’s to Australia’s to launch investigations into the tool.
Artificial affection: the age of AI companionship
Another category where AI is bridging the digital-physical divide is one with exponentially growing influence; AI driven sex and companion robots almost solely marketed to men. This new lucrative, extractive and globally exploding frontier is set to become one of the greatest altering forces of human relationships and a key, defining factor in the direction of travel on gender based violence. Millions of men are already using these “companions”, -virtual girlfriends, available and subservient 24/7, whose breast sizes and personalities they can customise and manipulate.
Insidious narratives being used to justify these products are fast taking hold, such as the aggressively promoted idea that these robots are a potential solution to male loneliness. Responsible Robotics argues that they in fact risk increasing it, given that they do not meet the species-specific needs of humans. In fact, by creating unrealistic “frictionless intimacy” they may end up desensitising men to empathy instead, which can only be developed through real world interaction and mutually consenting relationships.
“Negotiation, conflict repair, and empathy are pretty hard to practice when your partner is programmed never to challenge you.” -Dr Tara Logan, AI Researcher
This laudable apparent philanthropic motivation of sex robots being altruistic creations that prevent MVAWG (Male Violence Against Women and Girls)…falls apart against the fact that manufacturers actually make frequent efforts to enable the simulation of real-life abuse, thereby monetising sexual violence. Rather than normalising the dehumanising sexual objectification of women by providing misogynists with robots to abuse, we need to be interrogating the societal disintegration that contributes to their loneliness and misogynistic behaviours which women are increasingly, and rightly, refusing to tolerate.
“Femicides often sit on a continuum of violence that can start with controlling behaviour, threats and harassment-including online”. -Sarah Hendriks, Director of UN Women’s Policy Division
Who the algorithm amplifies – and who it silences
Another even more critical concern from a society-wide standpoint is that algorithmic bias algorithmic bias in AI systems is continuously and actively rewriting our realities When moderation algorithms suppress gender equality advocacy while not just allowing, but encouraging misogynistic abuse to flourish, the outcome is not neutral error, it is corrosive structural distortion. These distortions carry measurable downstream consequences: withdrawal from public life, career attrition, psychological harm, and as aforementioned, actual loss of life.
Bias in AI systems is also certainly not theoretical. It determines who is believed in courtrooms, who is flagged by moderation tools, who is excluded from credit, healthcare, employment, and whose content is made visible or ultimately hidden. To exemplify this; in December 2025, women on LinkedIn from the US to the UK participated in a collective experiment by changing their genders to male on linked in and using more agentic language. The results were staggering; content reach for many as much as quadrupled almost immediately after making the switch. For example, Kamales Lardi, a CEO and thought leader saw her post impressions increase by 421% in a few days , while Megan Cornish, a top voice on LinkedIn watched her views increase 400% on the platform.
The implications for this in terms of representation are seismic, as this materially affects reach and both political and corporate influence for women. It must also be remembered that AI bias does not in fact stay at the same level, but often steadily increases in a feedback loop, as shown by the racially biased Predictive Policing algorithm which incorrectly predicted reoffending rates for black residents in Chicago at twice the rate for white residents even when controlling for actual crime rates. Many have also drawn parallels on this to the Amazon recruitment algorithm scandal, which downgraded CVs containing the word “women” for two years before discovery. The upshot is, AI is now indubitably an active decider in what, and whom, gets normalised.
“Equality in AI shows up in very ordinary places. Who gets an appointment, who gets a follow up call, whose concern is taken seriously. It is not abstract”. -Katy Cherry, CEO, HTL
No innovation without inclusion
The duality is clear; though the current and potential harms of AI are deeply problematic, on the flip side, the shared benefits of well-governed systems are of huge significance. This can look like AI detecting coercive control patterns earlier than human-only models, revealing hidden trends in abuse data, supporting law enforcement with trauma-informed design, as well as strengthening resilience across education, healthcare, and justice systems. However, these benefits do not emerge spontaneously. They require shared responsibility. AI can either be the most disastrous accelerant of inequality we have ever built, or one of the most powerful levellers at our disposal.
Where the expectation of ethics in application lies is of paramount importance. Currently, the onus of responsibility is grossly inverted, with women and ethnic minorities being expected to operate in a state of hypervigilance both offline and online, including self-policing, reporting, even proving harm, all the while absorbing the consequences. This can be downright retraumatising.
During a recent summit I organised, Championing Equality in AI which was featured by Politics UK, Head of Al at Globeducate Clara Hawking described four forces shaping online misogyny: AI algorithms that reward engagement, content that spreads quickly because it elicits strong reactions, generative tools making creating abusive content “incredibly easy,” and malicious groups using gamification to recruit and radicalise youth. This environment, she warned, is becoming “a training ground for a belief system of our entire generation.” What we design and deploy now is not just generating incredibly serious consequences for today’s users, but is also quietly and profoundly codifying the values that will govern tomorrow’s world.
“Secret systems create public problems” Cha’Von (CJ) Clarke Noelle, AI Psychology & Root Ethics Strategist and author of ‘The Digital Polycrisis’
Excellent regulation and responsible design does not stifle innovation; on the contrary, as widely observed, it is simply good business, engendering trust, adoption and customer retention. For AI products and programs to stay competitive, feminist design with inclusion at its core needs to be reframed from a moral preference or “activist ask” to the strategic upgrade it is. In essence, AI can either be a gateway, or a gatekeeper. Whether it expands freedom or entrenches harm depends on architectural choices being made now by those designing and implementing it. It’s high time to stop expecting the most vulnerable in society to keep playing physical and digital whack-a-mole. What is permissible in design becomes probable in deployment; essentially, that which we do not reject, especially within AI, we reinforce.
