Advancing AI and Data Science Education in the US through Collaborative Coordination

CSforALL将召集计算机科学（CS）教育，人工智能（AI），机器学习（ML）和数据科学（DS）领导者的研讨会，探索AI和AI相关领域的教育途径。研讨会之后将提交一份报告，为决策者提供关于实施这些重要主题的指导，并提出政策建议，以确保在整个环境中公平实施。 一个新兴的运动集中了人工智能，机器学习和数据科学的相关计算学科，许多组织和课程项目都在倡导课堂上的CS教育。该研讨会旨在利用当前的时刻，创造协调的社区努力，通过美国教育系统显着影响学习者的轨迹，其结果是（1）更好地准备所有学生生活在人工智能和数据科学显着影响日常生活的数字世界中，（2）加强计算专业人员的途径，为他们在职业生涯中使用人工智能和数据科学做好适当的准备，（3）激发下一代人工智能和数据科学研究人员为世界技术格局做出贡献，以及（4）扩大女性，黑人，西班牙裔，土着，以及其他在教育途径中代表性不足的人群，这些教育途径导致了所列出的结果。人工智能（AI），机器学习（ML）和数据科学（DS）是创新的关键，今天和未来。国家需要创造一个更加多样化和包容性的人工智能创新者队伍，并在所有人中建立对人工智能的基本理解。该研讨会的目的是（1）围绕CS教育运动和公平变革机制建立清晰的认识，从而扩大CS和AI，ML和DS途径的参与;（2）审查当前的运动目标和国家CS标准，以更新指南;以及（3）告知与有希望的公平实践和扩大人工智能，ML，该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

CSforALL will convene a workshop of Computer Science (CS) education, Artificial Intelligence (AI), Machine Learning (ML), and Data Science (DS) leaders to explore education pathways to careers in AI and AI-related fields. The workshop will be followed by a report with guidance for decision makers regarding implementation of these important topics, and recommendations for policy that will ensure equitable implementation across the landscape. An emerging movement has centered the related computational disciplines of artificial intelligence, machine learning, and data science, and numerous organizations and curriculum projects are advocating specifically for these flavors of CS education in classrooms. The workshop seeks to leverage the current moment in time to create coordinated community efforts to significantly impact trajectories for learners through the US education system with an outcome of (1) better preparation of all students to live in a digital world where AI and Data Science significantly impact everyday life, (2) strengthen pathways for computing professionals with appropriate preparation to use AI and data science in their careers, (3) excite the next generation of AI and Data Science researchers to contribute to the landscape of technology in the world, and (4) broaden the participation of women, Black, hispanic, indigenous, and other underrepresented populations in the educational pathways that result in the outcomes listed.Artificial Intelligence (AI), Machine Learning (ML), and data science (DS) are key to innovation, today and into the future. There is a national need to create a more diverse and inclusive workforce of AI innovators, and create fundamental understanding of AI in all. The workshop aims to (1) create clarity around the CS education movement and mechanisms for equitable change resulting in broadening participation in CS and AI, ML, and DS pathways; (2) review of current movement goals and national CS standards to update guidance; and (3) inform movement trajectories that align with promising practices for equity and broadening participation in AI, ML, and DS pathways.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.