# Ethics Core (FABRIC)

> **NIH NIH U54** · UNIVERSITY OF CALIFORNIA, SAN DIEGO · 2022 · $543,010

## Abstract

Bridge2AI: a FAIR AI BRIDGE Center (FABRIC) Ethics Core Summary
The use of artificial intelligence (AI), and particularly machine learning (ML), in healthcare opens up many
opportunities to improve healthcare and biomedical research. However, AI/ML also raise important issues that
implicate ethics and trust, including defining parameters for consent and re-use of personal data, protecting
privacy, ensuring transparency and engagement with stakeholders about this research, and developing and
deploying tools that are useful and valid for all people. Without an ethically robust set of principles and practices
that are generalizable and reusable in a wide range of biomedical environments, AI/ML could violate personal
rights, widen the gap between fairness and equality, and fan the flames of mistrust, as exemplified by recent
work showing how racial bias can influence clinical decision algorithms. Our vision for the FAIR AI Bridge Center
- Ethics Core (FABRIC-Ethics) is to ensure that AI/ML is developed and applied in an ethical and trustworthy
manner. FABRIC-Ethics will support the Bridge2AI program to become sustainable by making it more ethical
and trustworthy by the end of the four-year project period.
To realize this vision, we will use an iterative and reflective four-step cycle: 1) Scaffold, 2) Assess, 3) Facilitate
and 4) Evaluate and educate, or SAFE, to provide a platform for convening, analyzing and curating, public
relations and original research in a multidisciplinary manner. We will work with the Bridge2AI program to
formulate ethical and trustworthy principles for AI/ML (ETAI) to address existing and future practices in
biomedical AI research and applications. These include the collection and management of data, the development
and deployment of AI/ML technologies and AI/ML applications. In close collaboration with the Bridge2AI program
and its Data Generation Projects (DGPs), we will conduct a closed- and open-ended survey, discuss priorities
and experiences with Bridge2AI DGPs, and develop an open, curated catalog of relevant literature. These efforts
will run in parallel with multiple mechanisms for building a learning ETAI community, convening Bridge2AI data
generation projects to distill best practices, and organizing studio sessions to support contact with the other core
areas of the Bridge2AI Center and the broader community. Our core will further develop a digital health checklist
and framework that prepares Bridge2AI DGPs to evaluate: 1) access and usability, 2) risks and benefits, 3)
privacy and 4) data management. We will work with the Bridge2AI DGPs to share knowledge about ETAI, inform
the development of principles and best practices, and to set up conferences for sustainable development of ETAI
culture beyond Bridge2AI. The team assembled for the core has expertise in a wide range of areas, including
bioethics, digital health research ethics, law, public policy, AI/ML, data protection, informatics, medicine, human-
centere...

## Key facts

- **NIH application ID:** 10473062
- **Project number:** 1U54HG012510-01
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN DIEGO
- **Principal Investigator:** Bradley A. Malin
- **Activity code:** U54 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $543,010
- **Award type:** 1
- **Project period:** 2022-07-08 → 2022-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10473062

## Citation

> US National Institutes of Health, RePORTER application 10473062, Ethics Core (FABRIC) (1U54HG012510-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10473062. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*