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Version: 2.0.0

Training

We anticipate that users accessing the data will have varied exposure to formal training in research methods and considerations for the ethical conduct of research involving data collected from human participants. If you have completed a formal course in research methods as part of your education AND, have successfully completed training on how to conduct ethical and responsible research (see Collaborative Institutional Training Initiative [CITI] or Human Research Protections[OHRP] programs), you may access the AI-READI public dataset.

If you have not completed formal training in research methods, please review the materials located here before accessing the dataset:

Basic Research Concepts training covers fundamental principles and methodologies essential for understanding and conducting research effectively across various disciplines.

If you have not completed training on how to conduct ethical and responsible research with data collected from human participants, please review the materials located here before accessing:

Human Rights Protection Training focuses on ethical guidelines, regulations, and procedures to ensure the welfare and rights of human subjects in research.

All of Us Educational Modules

Provided below are modules developed by a team affiliated with the All of Us Research Program. Like AI-READI and other Bridge2AI datasets, the data are available to data users for the purpose of advancing health knowledge. The data were collected from patients/participants and, as such, it is important that research using these data be conducted ethically and responsibly. The modules available are to provide data users with information about conducting ethical and responsible research.

AI/ML Training

We are also providing some training resources regarding AI/ML specifically. Because the AI-READI dataset is envisioned to facilitate developing downstream AI models and applications, these resources may be helpful to data users who are planning to use the data for these purposes.

  • AI Essentials for All Audiences - This is an introductory course developed by faculty at the University of California San Diego that is an open-access, free, self-paced training on AI concepts. It takes approximately 20-40 minutes to complete and introduces the basics of AI. It is designed to be helpful to any audience, regardless of industry or prior familiarity with AI, and provides an opportunity to gain a better understanding of this rapidly evolving field and how it can be applied in various contexts.

  • AI LAB Tutorial Videos - AI LAB is an initiative developed by the American College of Radiology, and the video tutorial section linked here provides a series of short digestible videos (each 4 minutes or less) that detail general concepts for imaging AI.

  • Aequitas - Created by the Center for Data Science and Public Policy at the University of Chicago, this is an open source bias audit toolkit for machine learning developers, analysts, and policymakers to audit machine learning models for discrimination and bias, and make informed and equitable decisions around developing and deploying predictive risk-assessment tools. This is a more advanced tool to evaluate fairness and is appropriate for developers and advanced users who have had prior training in this area. Instructions on how to use the tool are available here: http://aequitas.dssg.io/

Citation

K.D. Blizinsky, S. Chandrasekharan, S. Jooma, et al. The _All of Us_ Responsible Conduct of
Research Training: A Modular Approach to Researcher Education (manuscript forthcoming).