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

CSforALL将召集一场由计算机科学（CS）教育、人工智能（AI）、机器学习（ML）和数据科学（DS）领导者参加的研讨会，探讨通往人工智能和人工智能相关领域职业的教育途径。讲习班结束后将提交一份报告，为决策者提供关于落实这些重要议题的指导，并提出政策建议，确保在各个领域公平落实这些议题。一场新兴的运动以人工智能、机器学习和数据科学等相关计算学科为中心，许多组织和课程项目都在专门倡导在课堂上进行这些CS教育。该研讨会旨在利用当前时刻，创建协调的社区努力，通过美国教育系统显著影响学习者的轨迹，其结果是：(1)更好地为所有学生做好准备，使他们生活在一个人工智能和数据科学显著影响日常生活的数字世界中；(2)加强计算机专业人员的途径，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；(4)扩大女性、黑人、西班牙裔、土著和其他代表性不足的人群在教育途径中的参与，从而产生所列出的结果。人工智能（AI）、机器学习（ML）和数据科学（DS）是当今和未来创新的关键。全国需要建立一支更加多样化和包容性的人工智能创新者队伍，并建立对人工智能的基本理解。研讨会旨在(1)明确计算机科学教育运动和公平变革机制，从而扩大计算机科学和人工智能、机器学习和计算机科学途径的参与；(2)审查现行运动目标和国家CS标准，更新指导意见；(3)告知运动轨迹，这些轨迹与有希望的公平实践和扩大AI， ML和DS途径的参与相一致。该奖项反映了美国国家科学基金会的法定使命，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.