As society continues to confront the challenges of gender-based violence (GBV), emerging technologies like artificial intelligence (AI) are proving to be both an opportunity and a risk. While AI offers innovative ways to support prevention, response, and advocacy, it also poses critical threats that require immediate and thoughtful attention. Here are three key risks associated with AI in the context of GBV:

The Risks of AI in Gender-Based Violence

1. Deepfakes and non-consensual content
AI-powered tools can create highly realistic deepfake images and videos, often weaponised to humiliate, harass, or extort women. This misuse of AI technology has amplified the prevalence of revenge pornography and online sexual exploitation, with devastating psychological and social consequences for victims.

2. Bias in AI Systems
AI systems frequently inherit biases from the data they are trained on. These biases can manifest in applications such as hiring algorithms, facial recognition tools, or chatbots, perpetuating harmful stereotypes or failing to address the needs of marginalised communities. Survivors of GBV may find that such systems fail to adequately recognise or respond to their concerns, reinforcing systemic inequities.

3. Cyberstalking and predictive policing
AI-driven surveillance and tracking technologies are increasingly being used by perpetrators for cyberstalking, enabling them to monitor, intimidate, or locate survivors, making it harder for women who have experienced violence to seek safety. Additionally, predictive policing technologies risk reinforcing biases in law enforcement, leading to inadequate handling of GBV cases or neglect of survivor needs.

How the Alfie Project Supports Ethical AI

At Alfie, we are committed to developing AI technologies that are trustworthy. We aim to harness the power of AI responsibly, ensuring it is a force for good:

1. Building ethical AI solutions
Alfie is dedicated to designing AI systems that emphasise fairness, inclusivity, and accountability. By using diverse datasets and implementing strong measures to detect and mitigate bias, we strive to create technology that is free from harmful stereotypes, safe, and accessible to all.

2. Advocating for responsible AI policies
We work closely with policymakers, industry leaders, and civil society to develop regulations that address AI misuse, including its role in perpetuating harmful stereotypes or enabling acts of violence. Alfie advocates for policies that ensure AI systems are developed and used responsibly.

3. Raising awareness and promoting digital literacy
Alfie is dedicated to empowering individuals and communities by equipping them with the knowledge and tools to navigate AI safely. Through educational campaigns and initiatives, we raise awareness about the potential risks of AI misuse and provide practical strategies for protection against harm.

4. Collaborating for a safer AI future
We believe that trustworthy AI development requires collaboration. Alfie partners with organisations, researchers, and activists to tackle unethical uses of AI, particularly in addressing gender-based violence. Together, we work toward creating an inclusive digital environment where safety and dignity are prioritised for all.

A shared responsibility

The impact of AI on gender-based violence depends on the collective actions of policymakers, technologists, and society as a whole. On this International Day for the Elimination of Violence Against Women, we must commit to using AI responsibly, ensuring it serves as a tool for justice and equality rather than harm.

By working together, we can create a future where technology protects and uplifts, safeguarding the safety and dignity of every individual.

References

Broussard, M. (2023). More than a glitch: Confronting race, gender, and ability bias in tech. MIT Press.

Citron, D. K., & Chesney, R. (2019). Deepfakes and the new disinformation war. Foreign Affairs.

Lucas, K. T. (2022). Deepfakes and domestic violence: perpetrating intimate partner abuse using video technology. Victims & Offenders, 17(5), 647-659.

Noble, S. U. (2018). Algorithms of oppression: How search engines reinforce racism. In Algorithms of oppression. New York university press.

Pittaro, M. L. (2007). Cyber stalking: An analysis of online harassment and intimidation. International journal of cyber criminology, 1(2), 180-197.

Wagner, T. L., & Blewer, A. (2019). “The word real is no longer real”: Deepfakes, gender, and the challenges of ai-altered video. Open Information Science, 3(1), 32-46.