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Ethical and Responsible AI as a Means of Diagnosing and Eliminating Bias

Presentation #127.06 in the session Driving Towards a More Diverse Space Physics Research Community – Perspectives, Initiatives, Strategies, and Actions — Poster Session.

Published onOct 20, 2022
Ethical and Responsible AI as a Means of Diagnosing and Eliminating Bias

AI and Machine Learning (ML) are powerful tools that allow us to analyze and derive knowledge from information that may not be accessible using more traditional methods. AI/ML opens the gateway to exploring more complex relationships in both our data and in our practices as a community of scientists. However, the results of any ML model must be examined to ensure that they are valid and beneficial; otherwise the practitioners may act on false or misleading results. The NASA Framework for the Ethical Use of AI identifies six principles that are fundamental to Ethical AI: Explainable and Transparent, Fair, Accountable, Secure and Safe, Human-Centric and Societally Beneficial, Scientifically and Technically Robust. The Responsible AI focus team (of the NASA GSFC Center for HelioAnalytics) is working on guidelines and resources to help the Heliophysics community understand and comply with new best-practice standards.

There are many ways that Ethical AI can be leveraged to improve equity and fairness in our field. For example, there are practices in machine learning that can be used to clearly diagnose the factors behind human decisions, allowing us to pinpoint the presence and sources of bias. This can become a roadmap for ensuring fairness in future decisions. This presentation will review strategies for implementing Ethical/Responsible AI and discuss how they can be used to advance Diversity, Equity and Inclusion.

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