A reading list and fortnightly discussion group designed to provoke discussion about ethical applications of, and processes for, data science.

A deep exploration of Algorithmic Empathy, the next frontier in AI understanding. This project examines how machines can learn from human fallibility, model disagreement, and align with moral reasoning. It blends psychology, fairness metrics, interpretability, and co-learning design into one framework for humane intelligence.

Computational Social Science Project: "Algorithmic Bias in Echo Chamber Formation".

[MLHC 2020] Deep Learning Applied to Chest X-Rays: Exploiting and Preventing Shortcuts (Jabbour, Fouhey, Kazerooni, Sjoding, Wiens). https://arxiv.org/abs/2009.10132

Analyzing clinical decision instruments through the lens of data and large language models.

FairBook: A Reproducibility Study on The Unfairness of Popularity Bias in Book Recommendation (Bias@ECIR 2022)

Studying the Cumulative Effect of Multiple Fairness-Enhancing Interventions on Fairness, Accuracy and Population groups

Workshop with readings and exercises on the politics of tech.

Teaching material for bachelor course at Arcada

A Reflection on Truth, Power, and the Misdiagnosis of Awareness

Detecting bias in ML models using heat maps

Social and Ethical Issues in Information Technology - material and project

AI flub ups

Demonstrates the use of bias mitigation algorithms from IBM's AIF360 toolkit.

Analyzing geographic and cultural bias in AI therapy advice. Interactive visualization showing how AI systems draw from predominantly Anglophone sources when advising users about culturally specific dilemmas in India, Nigeria, and the Philippines.

Originally conceived as an academic report, this project evolved into a portfolio piece that combines code, slides, and case analysis to communicate ethical concerns in AI in a clear, accessible, and professional format.

Fairness in Digital Image Forgery Detection System

Automated tool to evaluate Twitter saliency filter algorithmic bias

Website for TechEquity's Tech, Bias, and Housing initiative.