FAccT Conference, 2021
Building ethics into introductory coding assignments: my presentation from our Tutorial, "A Crash Course in Motivating, Supporting and Expanding Ethical Thinking in the Tech Classroom"
FAT* Conference, 2020
How can we create "fair" algorithms when we disagree on what it means for something to be "fair"?
Coding For Social Impact, 2019
The main lecture from my workshop in Santiago de Cali, Colombia.
Topics: corruption, crime, open data, data science, coding, dataviz
Ethics of Machine Learning Talk, 2018
Topics: ML fairness, training data bias, fairness metrics, performance metrics, social responsibility for data scientists
Interviewing experts on the most pressing issues in AI Ethics while building a movement to address the rooted issues embedded in AI systems.
Taking ethical dilemmas introduced in SciFi stories and applying them to contemporary issues with technology through the power of storytelling and case-studies.
On this podcast episode, Jess chatted with Alison and Greyson about my PhD research. They discussed AI ethics, machine learning fairness, algorithmic bias, harmful technologies, and more!
To skip directly to Jess' interview, go to minute 30:33 🎧