Debate contribution: Tackling Online Violence Against Women and Girls
Debate contribution by Mr Stephen Dunne on .
- MLA
- Mr Stephen Dunne
- Party at the time
- Democratic Unionist Party
- Date
- 14 January 2025
- Type
- Debate contribution
- Business
- Opposition Business
- Heading
- Tackling Online Violence Against Women and Girls
- Assembly identifier
- Official Report component 4736408
Read the official Assembly record
Text
I also welcome the opportunity to speak on what is a very important issue, as colleagues have said. The alarming rise in online violence against women and girls, particularly through the misuse of deepfake technology and social media, demands our urgent and decisive action. It is a rapidly evolving issue. AI is becoming an increasingly important part of all our daily lives. It is interesting that, just yesterday, the UK Government announced a major plan to enhance how it is used across our nation. Although it is vital that we grasp the opportunities that AI provides, we must be acutely aware of its potential dangers, particularly in the wrong hands. Unfortunately, deepfake technology has been weaponised to perpetrate the abuse and humiliation of, disproportionately, women and girls. Studies indicate that over 90% of non-consensual deepfake imagery involves female victims. Those manipulated images are not mere pranks or jokes; they are violations of dignity, breaches of privacy and sources of profound psychological and emotional distress and trauma. More robust and proportionate regulation of data and emerging technology is required in order to crack down on the abuse. As has been mentioned today, through the lens of anonymity, it is so easy to engage in harmful practices, such as deepfakes and efforts to undermine democracy through misinformation and disinformation. That is a fundamental issue. For the women who are targeted, the consequences are devastating. Careers can be ruined, relationships can be strained, lives can be disrupted, and, tragically, in some cases, even ended, as we have seen across the world. The abuse has knock-on effects on children, family members and loved ones. Deepfake imagery is becoming more prevalent, with Ofcom recently revealing that 43% of people aged 16 and above say that they have seen at least one deepfake image online within the past six months. For too long, we have seen dither and delay in addressing those issues, while individuals have continued to suffer and actors have continued to escape punishment for their vile abuse. They are leaving a trail of destruction right across our country and beyond. We must address the loopholes that allow perpetrators to exploit technological gaps in order to harm others. Any review must not only focus on criminalisation but consider prevention and education and the provision of support for victims. Education campaigns will be crucial in that regard. There is also a role for our education sector to look at the issue, given the rise in the use of that technology by people of all ages. Legislation alone cannot solve the issue. We must confront the underlying cultural attitudes that enable and normalise online violence against women and girls.
443 words. Text as published by the Northern Ireland Assembly.
Assessment
Jev’s structured answers met the documented threshold for “not flagged”.
- Overall probability that the activity is being used to promote, exploit or escalate an identity-based controversy: 0.04 (flagging needs at least 0.70; at or below 0.30 is not flagged).
- None of the five culture-war criteria was met (each was below 0.60).
- Assessed as legitimate policy scrutiny (0.91).
- No identity-based framing was identified (0.79).
- Subject area: Sexism, misogyny, ageism and other equality groups.
- The overall probability was at or below the not-flagging threshold.
This is an AI-generated assessment of the text, made against published criteria. It is not a finding of fact about the MLA or their intentions. The Assembly record itself is the fact.
Jev’s structured answers
| Question | Probability | Met? |
|---|---|---|
| Identity framing | 0.09 | No |
| Sectarian or communal antagonism | 0.02 | No |
| Cultural grievance politics | 0.02 | No |
| Dog-whistle messaging | 0.02 | No |
| Controversy escalation | 0.04 | No |
| Legitimate policy scrutiny | 0.91 | Yes |
| Overall judgement | 0.04 | At or below not-flagging threshold |
| Option | Probability |
|---|---|
| No identity-based framing (chosen) | 0.79 |
| Reports or questions it | 0.00 |
| Criticises or condemns it | 0.21 |
| Adopts it | 0.00 |
| Subject | Probability |
|---|---|
| Sexism, misogyny, ageism and other equality groups | 0.84 |
| Gender, sexuality, abortion and related social issues | 0.16 |
| No identity-related subject | 0.00 |
| Flags, emblems, symbols, names and memorials | 0.00 |
| Parades, bonfires and commemorations | 0.00 |
Assessed 21 October 2026 at 11:47 UTC by jev-1.13.0 (requested as typesafe/jev) under rubric 2026.10-r9, methodology 1.9.
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