The importance of transparency and reproducibility in artificial intelligence research
arXiv:2003.00898 · doi:10.1038/s41586-020-2766-y
Abstract
In their study, McKinney et al. showed the high potential of artificial intelligence for breast cancer screening. However, the lack of detailed methods and computer code undermines its scientific value. We identify obstacles hindering transparent and reproducible AI research as faced by McKinney et al and provide solutions with implications for the broader field.
Cited by in corpus (25)
- The Fallacy of AI Functionality
- Trustworthy AI and Robotics and the Implications for the AEC Industry: A Systematic Literature Review and Future Potentials
- Opening up ChatGPT: Tracking openness, transparency, and accountability in instruction-tuned text generators
- brainlife.io: A decentralized and open source cloud platform to support neuroscience research
- AutoPrognosis 2.0: Democratizing Diagnostic and Prognostic Modeling in Healthcare with Automated Machine Learning
- CovidCTNet: An Open-Source Deep Learning Approach to Identify Covid-19 Using CT Image
- The worst of both worlds: A comparative analysis of errors in learning from data in psychology and machine learning
- Molecular MRI-Based Monitoring of Cancer Immunotherapy Treatment Response
- A Robust Ensemble Algorithm for Ischemic Stroke Lesion Segmentation: Generalizability and Clinical Utility Beyond the ISLES Challenge
- Economic Recommender Systems -- A Systematic Review
- A Rigorous Uncertainty-Aware Quantification Framework Is Essential for Reproducible and Replicable Machine Learning Workflows
- Navigating the challenges in creating complex data systems: a development philosophy
- A Green(er) World for A.I
- FAIR AI Models in High Energy Physics
- Stochastic Modeling of Inhomogeneities in the Aortic Wall and Uncertainty Quantification using a Bayesian Encoder-Decoder Surrogate
- The NCI Imaging Data Commons as a platform for reproducible research in computational pathology
- Identifying High Accuracy Regions in Traffic Camera Images to Enhance the Estimation of Road Traffic Metrics: A Quadtree-Based Method
- Towards Better User Studies in Computer Graphics and Vision
- KheOps: Cost-effective Repeatability, Reproducibility, and Replicability of Edge-to-Cloud Experiments
- Confronting the Reproducibility Crisis: A Case Study of Challenges in Cybersecurity AI
- ANALYSE -- Learning to Attack Cyber-Physical Energy Systems With Intelligent Agents
- Beyond Low Earth Orbit: Biological Research, Artificial Intelligence, and Self-Driving Labs
- Exploring complex pattern formation with convolutional neural networks
- The Practice of Ensuring Repeatable and Reproducible Computational Models
- Statistical Assessment of Replicability via Bayesian Model Criticism