Subtopic: Data Centers and Electronic Waste
Summary: These articles illustrate how data centers themselves can be bad for environment due to the nature of the materials used to build them and the excessive energy and materials needed to maintain and run these facilities.
Big Data, Big Waste? A Reflection on the Environmental Sustainability of Big Data Initiatives. Federica Lucivero (2020). Science and Engineering Ethics.
Our data centers now work harder when the sun shines and wind blows. Google Blog.
Renewable Energy Alone Can’t Address Data Centers’ Adverse Environmental Impact. Forbes.
Subtopic: Crypto Mining
Summary: Crypto mining may seem innocent, but the sheer number of rare materials and carbon footprint emitted from millions of graphic cards being used at 100% power 24 hours a day cannot be understated.
Subtopic: Carbon Tax and Green Computing
Summary: Discusses the debate centered around the carbon tax: is it worth it? How could we implement it? When should we implement it? And so on.
Calculate your carbon footprint (a helpful tool to aid in showing how much carbon an individual uses)
Green AI. Schwartz et al. (2019). arXiv.
Green algorithms: Quantifying the Carbon Footprint of Computation. Lannelongue et al. (2021). Advanced Science.
Chasing Carbon: The Elusive Environmental Footprint of Computing. Gupta et al. (2020). arXiv.
Green Computing, a contribution to save the environment. Data Science of the Natural Environment Blog, Lancaster University
Subtopic: Carbon Neutrality
Summary: This article “explores the world's response to the increasing impact of carbon emissions on the sobering threat posed by global warming: the carbon offset market.”
The Ethics of Carbon Neutrality: A Critical Examination of Voluntary Carbon Offset Providers. Dhanda & Hartman (2011). Journal of Business Ethics.
Big-business greenwash or a climate savior? Carbon offsets raise tricky moral question. The Conversation.
Subtopic: Computational Sustainability
Summary: Benefits from using machine learning to solve environmental problems
How machine learning can sharpen environmental research. Argonne National Laboratory.
Computational Sustainability: Computing for a Better World and a Sustainable Future. Gomes et al (2019). Communications of the ACM.
The 17 Sustainable Development Goals. United Nations Department of Economic and Social Affairs.
The role of AI in achieving the Sustainable Development Goals. Vinuesa et al. (2020). Nature Communications.
Solar powered dawn poems: progress report. Blog post by Allison Parrish (2022).
Subtopic: Ethics & Sustainability
Summary: These articles discuss how machine learning effects the environment and its energy inefficiency
AI and climate change: The mixed impact of machine learning.
Earth Systems Modeling Must Become More Energy Efficient. EoS.
Sustainable AI: Environmental Implications, Challenges and Opportunities. Wu et al. (2022). arXiv.
Astronomy’s contribution to climate change rivals the emissions from some countries. NPR.
Ethics of Artificial Intelligence and Robotics. Müller, Vincent C. (2021). Stanford Encyclopedia of Philosophy.
Artificial Intelligence: Ethics vs. Public Policy. Vardi (2022). SIAM News.
Energy and Policy Considerations for Deep Learning in NLP. Strubell et al (2019). arXiv.
Summary: These articles show the limitations of ML and different types of biases that can cause unintended effects in ML systems.
Thanks to Data Fellow Nikolai Stambler for his contributions to this course module.