United States and European Union Artificial Intelligence Administrative Arrangement
About the Arrangement
On January 27, 2023, the United States and European Union (EU) signed an Administrative Arrangement to collaborate on research using artificial intelligence (AI), computing, and privacy-related technologies. Through this arrangement, researchers will be able to build on existing work being conducted under forums such as the United States and EU Trade and Technology Council and the Joint Consultative Group.
“This arrangement presents an opportunity for joint scientific and technological research with our transatlantic partners, for the benefit of the global scientific community. Furthermore, it offers a compelling vision for how to use AI in a way that serves our peoples and upholds our democratic values such as transparency, fairness, and privacy.”
This arrangement represents a ground-breaking agreement designed to advance the use of AI in a number of fields, from agriculture to health and medicine. In brief, the agreement:
- extends beyond AI techniques to include other aspects related to these technologies, such as preserving privacy, engaging the community, including underserved communities, as well as ethics and trustworthiness.
- enhances collaborative efforts between the United States and EU to advance technology by applying methods such as federated learning. This approach allows researchers in the United States and EU to access diverse data sets for training AI models without having to move those data from their original repositories. The result is better, more comprehensive AI models.
- gives researchers in the United States and EU access to more detailed and data-rich models.
- creates new opportunities for U.S. and EU subject matter experts (SMEs) from diverse AI fields to work together and explore innovative ways to use AI-focused research for the common good.
NCI is fully engaged in helping to advance this unique AI collaboration. With Dr. Sylvia Gayle directing NCI’s efforts under the “Health and Medicine” focus group and providing leadership to five additional focus groups, NCI’s efforts are already well underway. Below are three recent events showcasing NCI’s work in AI.
|Description / Recap
|Workgroup on Equitable and Engaged AI
|A trans-NCI AI Working Group launched a series of meetings focused on “Equitable and Engaged AI to Advance Biomedical Research,” featuring both U.S. and EU SMEs. Topics included:
|Dr. Jennifer Couch (NCI’s Division of Cancer Biology) and Dr. Sylvia Gayle (Director, NCI/National Security Council AI Administrative Arrangement, NCI Office of Scientific Operations/CBIIT)
|Medical Image De-Identification Workshop
|NCI hosted a 2-day workshop looking at challenges in de-identifying medical images to ensure patient privacy. The workshop brought together more than 600 developers, researchers, and data scientists from around the United States and Europe. For more information, view the recordings and speaker slides.
|Dr. Keyvan Farahani (National Heart, Lung, and Blood Institute[NHLBI]) and members of CBIIT’s Informatics and Data Science Program
|Annual Brain Tumor Segmentation (BraTS) Challenges
|NCI, the U.S. Food and Drug Administration (FDA), the University of Pennsylvania, and Sage Bionetwork kicked off the annual International BraTS Challenge. The year’s challenges (which are ongoing) are using BraTS data sets to address diversity, glioma, meningioma, brain metastases, pediatric tumors, as well as missing data concerns, and technical considerations (e.g., augmentations).
|Dr. Keyvan Farahani (NHLBI), and staff from the U.S. FDA, the University of Pennsylvania, and Sage Bionetwork
Connecting with the Cancer Community
NCI also is supporting the U.S.-EU arrangement by collaborating with government agencies outside of NIH. Below are some key programs that are using AI to advance cancer research.
NCI’s Center for Cancer Research (CCR) and the FDA
CCR and the FDA are working together to make clinical trials more efficient and cost effective. The investigators are using AI/machine learning (ML) in digital oncology studies to aid in clinical cancer research and care. CCR and FDA also are piloting a method that automatically extracts common data elements from electronic health records to help in filling out electronic case report forms. If successful, this technology, along with a secure cloud-based system, could be useful for keeping clinical trial participants up to date on findings.
Activity Leads: Dr. Paolo Ascierto (National Tumor Institute, Naples, Italy), Dr. James Gulley (CCR), Dr. Mark Lawler (Queen’s University-Belfast), Dr. Jason E. Levine (CCR), Dr. Ignacio Melero (University of Navarra, Spain), and Dr. Sjoerd Van Der Burg (Leiden University-Netherlands)
NCI-Department of Energy (DOE) Collaborations
NCI and DOE are collaborating on a number of far-reaching research initiatives that fall under the Cancer MoonshotSM project. Many of these initiatives are exploring the use of AI/ML and other advanced technologies and are in line with the work under the U.S.-EU agreement. Specific projects include the following:
- ADMIRRAL: AI-Driven Multi-Scale Investigation of the RAS/RAF Activation Lifecycle—ADMIRRAL is using AI to develop effective strategies for cancer diagnosis and therapy.
- IMPROVE: Innovative Methodologies and New Data for Predictive Oncology Model Evaluation—IMPROVE offers a framework for comparing and evaluating cancer drug response, which is a key research area in the AI Administrative Arrangement.
- MOSSAIC: Modeling Outcomes Using Surveillance Data and Scalable AI for Cancer—MOSSAIC and NCI’s Surveillance, Epidemiology and End Results (SEER) Program are actively researching AI/deep learning and natural language processing.
- ATOM: Accelerating Therapeutics for Opportunities in Medicine—The ATOM Consortium is generating ML models to predict the mechanisms and safety of cancer medications and to identify new compounds for study.
- Cancer Patient Digital Twins (CPDTs)—CPDTs is exploring the use of AI in cancer screening and how it can help in prevention and treatment efforts.
Activity Lead: Dr. Emily Greenspan (NCI CBIIT)
These are just a sampling of the NCI programs and initiatives that are using AI. Please check this page in the future, as we’ll be updating information as available.