When tech meets women’s rights

Can technology be harnessed for social good? Set in a context where the world is still over a century away from closing the gender gap, Associate Professor Vijeyarasa will discuss her motivations for going beyond the boundaries of the law to offer new solutions to address global gender inequality. Drawing from her experiences as the architect of the Gender Legislative Index, she will share her thoughts on why law, technology & data offer new potential to make the world more equal. She will also share her advice, from her first foray to her most recent experiences using technology for social justice as a ‘data outsider’, as well as her insights on the role of women in data, data science & technology.

Biography

Ramona Vijeyarasa is a legal academic and women’s rights activist. An Associate Professor in the Faculty of Law at UTS, she is the designer behind the award-winning Gender Legislative Index, a collaboration with Rapido Social and the UTS Connected Intelligence Centre, a tool that uses human evaluators and machine-learning to assess how well laws work for women. Her career began as a corporate lawyer in Sydney. Driven by a passion for human rights, her focus unsurprisingly shifted to international women’s rights law. Ramona’s decade working in civil society has taken her from the slums of Rio de Janeiro, capturing the stories of survivors of domestic violence, to the floating villages of Cambodia, where she supported women’s demands for better access to reproductive health care. As a legal activist, Ramona has helped advance anti-trafficking victim reintegration networks in Vietnam and Ukraine, filed briefs before the European Court of Human Rights, the Supreme Court of Moldova and the Supreme Court of the Philippines and made submissions to United Nations treaty bodies. This rich experience informs her impact-driven approach to research, where sound methodologies are created to deliver tangible change in order to improve lives through the law.

Zoom link will be emailed 1 day prior to event.