reading-list

Things I am reading

Reading List 2021

• The Steep Cost of Capture THIS!

• Indigenous Protocol and Artificial Intelligence Position Paper

• The Myth of Complete AI-Fairness

• Sustainable AI: AI for sustainability and the sustainability of AI

• Mapping AI in the Global South

• The Role and Limits of Principles in AI Ethics: Towards a Focus on Tensions

• Tackling Climate Change with Machine Learning

• Combining Satellite Imagery and Machine Learning to Predict Poverty

• When conflicts get heated, so does the planet: social-climate dynamics under inequality

• Combining MCTS and A3C for Prediction of Spatially Spreading Processes in Forest Wildfire Settings

• AI for the Common Good?! Pitfalls, challenges, and Ethics Pen-Testing

• The Human Effect Requires Affect: Addressing Social-Psychological Factors of Climate Change with Machine Learning

• Challenges and Prospects for Data-Driven Climate Change Mitigation

• Transport: A roadblock to climate change mitigation?

• Prdictibility in the midst of chaos: a scientific basis for climate forecasting

• Machine Learning for applications for Earth obeservation

• The power of peer pressure in combatting climate change

• Policy design for the anthropocene

• Basic methods of policy analysis and planning (D.S.Patton, C.V.annd, J.Clark)

• From Satellite Imagery to Disaster Insights

• Automated Hate Speech Detection and the Problem of Offensive Language

• Automatic Differentiation in Machine Learning: A Survey

Privacy and Fairness

Title	Aims	Notes	Read?
Privacy for All: Ensuring Fair and Equitable Privacy Protections	Position Paper - applying recent research on ensuring socio-technical systems are fair and non-discriminatory to the privacy protections those systems may provide	Privacy systems may disproportionately fail to protect vulnerable members of the population.	read
On the Compatibility of Privacy and Fairness	To see if both privacy and fairness can be achieved by one classifier or if tensions exist between the two		read
Fair Decision Making Using Privacy-Protected Data	To study the impact of formally private mechanisms on fair and equitable decision-making	Consider settings where sensitive personal data is used to decide who will recieve resources or benefits.	read
Neither Private Nor Fair: Impact of Data Imbalance on Utility and Fairness in Differential Privacy	To study how different levels of imbalance in data affect the accuracy and fairness of decisions made by a model given different levels of privacy	Even small imbalances and loose privacy guarantees can cause disparate impacts	read
Do the Machine Learning Models on a Crowd Sourced Platform Exhibit Bias? An Empirical Study on Model Fairness	To investigate the empirical evaluation of fairness and mitigation on real-world ML models	Some model optimization techniques result in inducing unfairness in the models. Although there are some fairness control mechanisms in ML libraries, they aren’t documented.	read
SoK: Towards the Science of Security and Privacy in Machine Learning			read
Co-Designing Checklists to Understand Organisational Challenges and Opportunities around Fairness in AI			read
AI FAIRNESS 360: AN EXTENSIBLE TOOLKIT FOR DETECTING, UNDERSTANDING, AND MITIGATING UNWANTED ALGORITHMIC BIAS	On AI Fairness 360 IBM	A tool to measure fairness	read
Transparency Tools for Fairness in AI (Luskin)			read
Delayed Impact of Fair Machine Learning			read

Ocean Particle Clustering

Title	Aim	Notes	Read?
Unsupervised Learning Reveals Geography of Global Ocean Dynamical Regions			read
Unsupervised Clustering of Southern Ocean Argo Float Temperature Profiles			read
Temporal changes in the causes of the observed oxygen decline in the St. Lawrence Estuary	To examine what has been contributing to the oxygen decline over the last five decades		read

Misc.

• Attention Is All You Need
• The Grey Hoodie Project: Big Tobacco, Big Tech, and the threat on academic integrity