The guest of Episode 17 of the podcast
The Road Less Traveled is Jean Linis-Dinco, a human rights activist, academic and data scientist from the Philippines. She is currently doing her PhD in cybersecurity at the University of South Wales Canberra, focusing on the analysis of government propaganda, and disinformation in the context of the Rohingya crisis in Myanmar.
Already a good communicator by training, Jean also did the
Master’s Programme in Human Rights and democratisation in Asia Pacific (APMA), which made her start working towards a more progressive approach to human rights, one that also ecompasses social political economy.
She works towards a future where people matter over profit.
“To ensure that AI does not become a tool of oppression, we must strive to democratize its ownership. By promoting open source AI technologies, cooperatives, worker-owned enterprises, we can encourage widespread access to AI resources and prevent monopolistic control by rich people. And this collective ownership empowers the working class to participate in AI decision-making and benefit from its advancement.”She also sees the potential in AI becoming a force for good and having the power to revolutionize the global workforce. “
The present is our battleground and the place where we construct the very foundation of the future that we desire.”Her advice for someone who is keen to work in the field of machine learning, or data governance, or just machine learning in general and doing programming: “
As a human rights graduate, you actually already have every soft skill that the market needs.”Regarding human rights education, she stresses that the best tool to use is the one that is working and that
we should avoid treating technology as the be all and end all solution to every challenge. What we need is culturally relevant pedagogy: developing educational materials and curriculum that resonate with the students cultural backgrounds and experiences.
She concludes by reminding everybody to keep the poor in mind especially when making decisions related to AI.