The investment – distributed over four years pending availability of funds – will help assemble team members from diverse disciplines and backgrounds to generate tools, resources, and richly detailed data that are responsive to AI approaches.
Computers which mimic humans
AI is both a field of science and a set of technologies that enable computers to mimic how humans sense, learn, reason, and take action.
Although AI is already used in biomedical research and healthcare, its widespread adoption has been limited - in part due to challenges of applying AI technologies to diverse data types.
This is because routinely collected biomedical and behavioral data sets are often insufficient: because they lack important contextual information about the data type, collection conditions, or other parameters. Without this information, AI technologies cannot accurately analyze and interpret data.
Without the social and ethical contexts from data collection, AI technologies may also inadvertently incorporate bias or inequities.
Setting standards
The Bridge2AI project will seek to address these challenges.
Through collaboration across projects, researchers will create guidance and standards for the development of ethically sourced, state-of-the-art, AI-ready data sets that have the potential to help solve some of the most pressing challenges in human health — such as uncovering how genetic, behavioral, and environmental factors influence a person’s physical condition throughout their life.
“Generating high-quality ethically sourced data sets is crucial for enabling the use of next-generation AI technologies that transform how we do research,” said Lawrence A. Tabak, D.D.S., Ph.D., Performing the Duties of the Director of NIH. “The solutions to long-standing challenges in human health are at our fingertips, and now is the time to connect researchers and AI technologies to tackle our most difficult research questions and ultimately help improve human health.”
As it creates tools and best practices for making data AI-ready, Bridge2AI will also produce a variety of diverse data types ready to be used by the research community for AI analyses.
These types include voice and other data to help identify abnormal changes in the body. Researchers will also generate 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 influence health.
Meanwhile, AI-ready data will be prepared to help improve decision making in critical care settings to speed recovery from acute illnesses and to help uncover the complex biological processes underlying an individual’s recovery from illness.
The Bridge2AI program will put a focus on diversity: noting it is is fundamental to the ethical generation of data sets (particularly to reduce bias and thus improve effectiveness across populations).
It will also develop ethical practices for data generation and use, addressing key issues such as privacy and data trustworthiness.
NIH has issued four awards for data generation projects, and three awards to create a Bridge Center for integration, dissemination and evaluation activities.
The Bridge2AI program is an NIH-wide effort managed collaboratively 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 Library of Medicine.