The National Science Foundation’s Directorate for STEM Education (EDU) is seeking input from institutions of higher education (IHEs) and other interested parties to help with an assessment of the capacity of IHEs related to Artificial Intelligence (AI). This Dear Colleague Letter (DCL) is not intended to solicit proposals, but rather to invite input from a variety of sources. 
This DCL welcomes input from a diverse range of experts, including those from academia, industry, government, and non-profit sectors. Submissions from Historically Black Colleges and Universities (HBCUs) and Minority Serving Institutions (MSIs) are particularly encouraged.

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* 1. Respondent’s Name [Point of Contact]

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* 2. E-mail

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* 3. Respondent’s Affiliation

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* 4. Respondent’s Position and Title (if applicable)

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* 5. Name of IHE Described

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* 6. Current AI programs, if applicable, (i.e., descriptions or URLs of major, minor, concentration, certificate, etc.) at the IHE

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* 7. You may upload files or URLs to respond to the above question. 

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* 8. Current AI-related courses, if applicable, (i.e., descriptions or URLs of AI-related courses), including courses with AI theme or AI content, the IHE is offering.

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* 9. You may upload files or URLs to respond to the above question. 

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* 10. Expertise of faculty teaching AI-related courses (i.e., faculty with AI research portfolios, or faculty from general list)

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* 11. AI topical focus areas that the IHE faculty are prepared to contribute expertise for the purpose of development of AI curriculum development, if applicable

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* 12. AI topical research and development areas that the IHE faculty are working on, if applicable. 

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* 13. What factors are critical for increasing AI education and workforce development capacity at your institution? What are the current barriers? 

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* 14. What factors are critical for increasing the number of graduates with AI skills, knowledge, and competencies?  What are the current barriers?  

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* 15. Do you have any other comments?

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* 16. By submitting this input, I consent to NSF's use and display of the submitted information, consistent with the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode). NSF may make submissions publicly accessible through a website.

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