A reading list and fortnightly discussion group designed to provoke discussion about ethical applications of, and processes for, data science.
-
Updated
Aug 19, 2026 - Python
A reading list and fortnightly discussion group designed to provoke discussion about ethical applications of, and processes for, data science.
Auditing algorithmic bias in criminal justice, hiring, lending, healthcare, welfare, and tenant screening: 7 open-source audits, measurable fairness gaps, and concrete fixes.
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.
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.
Detecting bias in ML models using heat maps
Dataset, images, metadata, and analysis scripts used in a study on representational bias in AI-generated imagery for university visual communication.
⚖️ An analytical framework for LAPD crime hotspot mapping with a focus on algorithmic fairness. This project identifies high-crime areas while rigorously auditing predictive models for bias, ensuring that resource allocation is driven by data without compromising social equity. 🚔📊
Teaching material for bachelor course at Arcada
Social and Ethical Issues in Information Technology - material and project
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.
AI flub ups
Anexo técnico de la tesis "Gobernanza de la IA en la Administración Tributaria en México"
A comparative ethical audit of commercial Computer Vision APIs (Amazon Rekognition, Face++, and Google Cloud Vision) against 19 best practices for Automated Gender Recognition (AGR).
Add a description, image, and links to the algorithmic-bias topic page so that developers can more easily learn about it.
To associate your repository with the algorithmic-bias topic, visit your repo's landing page and select "manage topics."