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

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.

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.

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

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

Workshop with readings and exercises on the politics of tech.

Teaching material for bachelor course at Arcada

Detecting bias in ML models using heat maps

Social and Ethical Issues in Information Technology - material and project

AI flub ups

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

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

🧠 Explore cognitive hijacking in long-context LLMs, revealing vulnerabilities in prompt injection through innovative attack methods and research insights.

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

Affevtive Bias in Large Pre-trained Language Models

Automated tool to evaluate Twitter saliency filter algorithmic bias

Fairness in Digital Image Forgery Detection System