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Reading history for Fair ML Reading Group in Melbourne
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Fair ML Reading Group 2020

🌏 Melbourne, Australia
🏠 Hosted by Silverpond
🤖 Facilitated by Laura
📬 Listserv at
🗓 Google calendar


A multi-disciplinary group reading papers on the topic of fairness and ethics in Machine Learning and Data Science.

2019 papers —

Reading history

January 16
On Consequentialism and Fairness

January 24
A Framework for Understanding Unintended Consequences of Machine Learning

January 30
Principled Artificial Intelligence: Mapping Consensus in Ethical and Rights-Based Approaches to Principles for Ai

February 14
Bayesian Modeling of Intersectional Fairness: The Variance of Bias

February 21
Autonomous technology – sources of confusion: a model for explanation and prediction of conceptual shifts

February 28
The hidden assumptions behind counterfactual explanations and principal reasons

March 5
Bayesian Modeling of Intersectional Fairness: The Variance of Bias (Revisited)

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