The future of AI will be determined in part by how its developers are educated. Thus, how computer science (CS) education incorporates instruction in various aspects of AI will have a substantial impact on AI's evolution. Understanding how and what CS educators think about AI education is, therefore, an important piece of the landscape in anticipating -- and shaping -- the future of AI. However, little is known about how educators perceive the role of AI education in CS education, and there is no consensus yet regarding what AI topics should be taught to all students. This paper helps to fill that gap by presenting a qualitative analysis of data collected from high school CS instructors, higher education CS faculty, and those working in the tech industry as they reflected on their priorities for high school CS instruction and on anticipated changes in high school, college, and workplace CS. We conclude with recommendations for the CS education research community around AI in K-12, particularly at the high school level.
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The Impact of AI Computing Paradigms on Science Gateways and National Compute Resources
The BoF will address four questions: Q1: What are novel modes of computing implied by AI? Which will have the greatest impact on CI for gateways and national compute resources? Facilitated by Joe Stubbs Q2: What are or should be the goals of broadening access to compute resources for AI purposes? Who can be brought into the community that previously was not? Facilitated by Sandra Gesing Q3: What are the interesting aspects related to data sharing? How do the various compute loads and modes impact how data are shared, moved, and accessed? Facilitated by Rob Quick Q4: How can AI be used in a science gateway to make it more effective, efficient, secure, or otherwise better? Facilitated by Claire Stirm
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- Award ID(s):
- 2231406
- PAR ID:
- 10450536
- Date Published:
- Journal Name:
- PEARC23
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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