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.
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
Demonstrates the use of bias mitigation algorithms from IBM's AIF360 toolkit.
Website for TechEquity's Tech, Bias, and Housing initiative.
Fairness in Digital Image Forgery Detection System
Automated tool to evaluate Twitter saliency filter algorithmic bias
Affevtive Bias in Large Pre-trained Language Models
A fairly simple AI classifier to find out if adopting a cat or a dog will make a person(me) happier.
Exercise repository for Algorithmic Fairness, Accountability and Ethics (Spring 2022), IT University of Copenhagen
The code presented here is meant to accompany our Playbook, which illustrates our threshold adjustment methodology that can mitigate bias in EHR-based classification models. Our paper and the Playbook can be found in npj Digital Medicine at the link below:
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