The National Institutes of Health will invest $130 million over four years, pending the availability of funds, to accelerate the widespread use of artificial intelligence (AI) by the biomedical and behavioral research communities. The Bridge to Artificial Intelligence (Bridge2AI) program of the Joint Fund of the National Institutes of Health brings together team members from diverse disciplines and backgrounds to generate tools, resources, and rich, detailed data that respond to AI methods. At the same time, the program will ensure that its tools and data do not perpetuate inequality or ethical problems that may occur during data collection and analysis. Through extensive collaboration across projects, Bridge2AI researchers will establish guidelines and standards for developing modern, ethically-equipped data sets that have the potential to help solve some of the most pressing challenges in human health — such as revealing how genetic, behavioral, and environmental factors affect a person’s physical condition throughout their life. .
Creating high-quality data sets from ethical sources is critical to enabling the use of next-generation AI technologies that are changing the way research is done. Solutions to long-term challenges in human health are at our fingertips, and now is the time to connect researchers and artificial intelligence technologies to tackle our toughest research questions and ultimately help improve human health.”
Lawrence A. Tabak, MD, PhD, performing the duties of Director of the National Institutes of Health
Artificial intelligence is a field of science and a set of technologies that enable computers to simulate the feeling, learning, reasoning, and action of humans. Although AI is already used in biomedical research and healthcare, its widespread adoption has been limited in part by the challenges of applying AI techniques to diverse data types. This is because routinely collected biomedical and behavioral data sets are often inadequate, meaning they lack important contextual information about data type, collection conditions, or other parameters. Without this information, artificial intelligence technologies cannot accurately analyze and interpret data. AI techniques may also inadvertently include bias or inequality unless careful attention is paid to the social and ethical contexts in which the data is collected. In order to harness the power of AI to discover and accelerate its use of biomedicine, scientists first need well-described and ethically generated data sets, standards and best practices to generate biomedical and behavioral data ready for AI analytics.
As it creates tools and best practices for making data AI ready, Bridge2AI will also produce a variety of diverse data types that are ready for use by the research community for AI analytics. These types include sound and other data to help identify abnormal changes in the body. The researchers will also create data that can be used to make new connections between complex genetic pathways and changes in cell shape or function to better understand how they work together to affect health. In addition, AI-ready data will be prepared to help improve decision-making in critical care settings to accelerate recovery from acute illness and to help reveal the complex biological processes underlying an individual’s recovery from illness.
The Bridge2AI program is committed to forming diverse research teams rich in academic and technical perspectives, backgrounds, and disciplines. Diversity is central to the ethical generation of data sets, and to the training of future AI techniques to reduce bias and improve efficacy for the entire population, including those underrepresented in biomedical and behavioral research. Bridge2AI will develop ethical practices for data generation and use, addressing key issues such as privacy, data reliability, and reducing bias.
The National Institutes of Health has issued four awards for data generation projects, and three awards for the creation of the Bridge Center for Integration, Dissemination, and Evaluation Activities. Data generation projects will produce new biomedical and behavioral datasets ready for use in the development of AI technologies, along with creating data standards and tools to ensure data can be found, accessible, interoperable and reused, a principle known as FAIR. In addition, data generation projects will develop training materials that promote a culture of diversity and the use of ethical practices throughout the data generation process. The Bridge Center will be responsible for integrating activities and knowledge across data generation projects, dissemination of products, best practices and training materials.
The Bridge2AI program is an NIH-wide effort collaboratively managed by the NIH Common Fund, the National Center for Complementary and Integrative Health, the National Eye Institute, the National Human Genome Research Institute, the National Institute of Biomedical Imaging and Bioengineering, and The National Center for Biomedical Imaging and Bioengineering. Medicine Library. To learn more about Bridge2AI, visit Musings from the National Library of Medicine’s Mezzanine blog, and watch this video about Bridge2AI.