Interesting Reads

AI Reproducibility

• The Reproducibility Issues that Haunt Healthcare AI: This Nature article asks the question: Health-care systems are rolling out artificial-intelligence tools for diagnosis and monitoring. But how reliable are the models?

• The Reproducibility Crisis in ML-based Science: Hosted by the Center for Statistics and Machine Learning at Princeton University, this piece highlights the scale and scope of the crisis, identifies root causes of the observed reproducibility failures, and suggests progress towards solutions.

• The replication crisis has led to positive structural, procedural, and community changes

• Wanted: standards for automatic reproducibility of computational experiments 

• Is AI leading to a reproducibility crisis in science? by Philip Ball - This article discusses the ways in which scientists worry that ill-informed use of artificial intelligence is driving a deluge of unreliable or useless research. 

• Detailed Implementation of a Reproducible Machine Learning-Enabled Workflow by Kenneth E. Schackart lll, Heidi J. Imker, Charles E. Cook 

• Reproducibility vs. Replicability: A Brief History of a Confused Terminology by Hans E. Plesser

• How can we make sound replication decisions?

• The Unreasonable Effectiveness of Open Science in AI: A Replication Study

• Reproducibility in machine-learning-based research: Overview, barriers, and drivers

• Reimagining Experimentation: The Path to Replicable Science

• FAIR principles in workflows: A GIScience workflow management system for reproducible and replicable studies