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Joint response to the Genesis Mission RFI by the Alliance for Data Science and AI (ADSA) and the United States Research Software Engineer Association (US-RSE)

Authors: Parker, Micaela S.; Gesing, Sandra; Van Tuyl, Steven; Robinson, Nathaniel; Michael, Mykins; Raybourn, Elaine M;

Joint response to the Genesis Mission RFI by the Alliance for Data Science and AI (ADSA) and the United States Research Software Engineer Association (US-RSE)

Abstract

AI may be the most transformative technology of this generation, potentially enabling significant acceleration of scientific discovery and societal benefits at a scale far beyond what humans alone can achieve. The Genesis Mission’s ambition to train 100,000 scientists and engineers in AI over the next decade through coordinated initiatives that treat AI technology and competency as foundational is commendable. The workforce demands of a scalable AI-powered innovation ecosystem will encompass the full lifecycle of AI development and implementation, as well as application by domain-specific practitioners seeking to amplify their work with AI tools. As stewards and operators of the building blocks of a robust AI ecosystem, and as educators of an emerging AI-enabled scientific workforce, Data Scientists (DSs) and Research Software Engineers (RSEs) are key drivers in achieving this ambitious goal, acting as essential workforce multipliers who operationalize AI into sustained scientific infrastructure. ADSA and US-RSE are providing this Response to ensure dedicated investment in the strong and ongoing partnerships between our organizations, Federal decision-makers, and the sectors in which much of this emerging workforce will eventually operate. Importantly, our organizations represent institutional and individual members from academia, industry, and National Laboratories, positioning us as strategic enablers of the dual-competency education and training envisioned by the Mission.

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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average