AI4CAREER: Responsible AI for STEM Career Development at Scale in K-16 Education
Fuente:
arXiv
Enregistré dans:
| Auteurs principaux: | , , , , , , , |
|---|---|
| Format: | Preprint |
| Publié: |
2026
|
| Sujets: | |
| Accès en ligne: | |
| Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
| _version_ | 1866908861623959552 |
|---|---|
| author | Chawla, Sugana Chen, Si Qian, Julia Svarovsky, Gina Cheng, Alison Johnson, Rick Chawla, Nitesh V. Metoyer, Ronald |
| author_facet | Chawla, Sugana Chen, Si Qian, Julia Svarovsky, Gina Cheng, Alison Johnson, Rick Chawla, Nitesh V. Metoyer, Ronald |
| contents | Rapid advances in artificial intelligence (AI) are reshaping how students imagine, explore, and prepare for STEM careers across K-16 education. As AI systems increasingly influence feedback, advising, and access to information about opportunities, they are becoming part of the developmental infrastructure that shapes career identity formation and readiness. Yet uncertainty remains about how AI-supported career exploration tools should be designed, governed, and evaluated at scale, particularly across developmental stages and institutional contexts. This half-day workshop convenes researchers, educators, practitioners, and policymakers to examine responsible AI for STEM career development. We focus on four themes: (1) how AI reshapes definitions and assessment of STEM career readiness; (2) appropriate roles and boundaries for AI in career decision-making; (3) developmental alignment of AI supports across the K-16 continuum; and (4) equity-related design considerations that prevent the reproduction of structural disparities. Through lightning talks, structured group activities, and cross-sector dialogue, participants will surface design tensions, articulate governance principles, and identify research gaps. The workshop aims to advance shared language and actionable frameworks for responsible, developmentally grounded AI use in STEM career learning at scale. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_02568 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | AI4CAREER: Responsible AI for STEM Career Development at Scale in K-16 Education Chawla, Sugana Chen, Si Qian, Julia Svarovsky, Gina Cheng, Alison Johnson, Rick Chawla, Nitesh V. Metoyer, Ronald Computers and Society Rapid advances in artificial intelligence (AI) are reshaping how students imagine, explore, and prepare for STEM careers across K-16 education. As AI systems increasingly influence feedback, advising, and access to information about opportunities, they are becoming part of the developmental infrastructure that shapes career identity formation and readiness. Yet uncertainty remains about how AI-supported career exploration tools should be designed, governed, and evaluated at scale, particularly across developmental stages and institutional contexts. This half-day workshop convenes researchers, educators, practitioners, and policymakers to examine responsible AI for STEM career development. We focus on four themes: (1) how AI reshapes definitions and assessment of STEM career readiness; (2) appropriate roles and boundaries for AI in career decision-making; (3) developmental alignment of AI supports across the K-16 continuum; and (4) equity-related design considerations that prevent the reproduction of structural disparities. Through lightning talks, structured group activities, and cross-sector dialogue, participants will surface design tensions, articulate governance principles, and identify research gaps. The workshop aims to advance shared language and actionable frameworks for responsible, developmentally grounded AI use in STEM career learning at scale. |
| title | AI4CAREER: Responsible AI for STEM Career Development at Scale in K-16 Education |
| topic | Computers and Society |
| url | https://arxiv.org/abs/2603.02568 |