algorithmic-bias

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.

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.

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. 🚔📊

Social and Ethical Issues in Information Technology - material and project

Teaching material for bachelor course at Arcada

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.

An interactive lab where students train a classifier in the browser, drag one threshold, and watch who absorbs the error.

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).

Anexo técnico de la tesis "Gobernanza de la IA en la Administración Tributaria en México"