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Christopher Bard

Publications and source records attributed to Christopher Bard.

Supporting Responsible Machine Learning in Heliophysics

Over the last decade, Heliophysics researchers have increasingly adopted a variety of machine learning methods such as artificial neural networks, decision trees, and clustering algorithms into their workflow. Adoption of these advanced data science methods had quickly outpaced institutional response, but many professional organizations such as the European Commission, the National Aeronautics and Space Administration (NASA), and the American Geophysical Union have now issued (or will soon issue) standards for artificial intelligence and machine learning that will impact scientific research. These standards add further (necessary) burdens on the individual researcher who must now prepare the public release of data and code in addition to traditional paper writing. Support for these is not reflected in the current state of institutional support, community practices, or governance systems. We examine here some of these principles and how our institutions and community can promote their successful adoption within the Heliophysics discipline.

Machine learning

Recommendations to Advance Space Trusted Autonomy

While the various space agencies of the U.S. federal government have distinctly different visions for future operational space systems, all share important foundational commonalities: improve mission performance, reduce mission costs, incorporate technology advances more rapidly, increase reliability and resiliency, reduce risk, and adapt to anomalies and environmental hazards. These common needs, combined with the maturation of autonomous technology and the prospect of leveraging autonomous systems to address these needs, have led each agency to consider how and when to implement increasing levels of autonomy in their space systems. Simultaneously, the related question of how to determine the trustworthiness of an autonomous system is also escalating in significance.

Christopher A Jones

Recommendations to Advance Space Trusted Autonomy

The interagency Space Science and Technology Partnership Forum was established in2015 to identify synergistic efforts and technologies across the U.S. government. While the various space agencies of the U.S. government have distinctly different visions for future operational space systems, all share important foundational common needs. These needs, combined with the maturation of autonomous technology and the prospect of leveraging autonomous systems to address those needs, have led each agency to consider how and when to to implement increasing levels of autonomy in their space systems, and how to determine the trustworthiness of an autonomous system. The Partnership facilitated dialogue among the partners, collected and analyzed data on current and desired future levels of capability, and identified gaps to motivate three recommendations that can be addressed within the Partnership community. These recommendations address the need for more robust documenting and socializing of anomalies in space system operations; the need to expand communication and trust within the community of developers, operators, and end users; and the need for a safe development and testing environment for maturing and demonstrating future autonomous space systems. These recommendations will facilitate both near-term programmatic actions and long-term steps for implementing enduring progress towards enabling space trusted autonomy.

Christopher A Jones