EAGER: SaTC-EDU: Transformative Educational Approaches to Meld Artificial Intelligence and Cybersecurity Mindsets

社会正变得越来越依赖技术，而这些技术很容易被坏人滥用。人工智能(AI)和网络安全，就像许多计算机科学一样，是非常技术性的领域，在知识和应用方面都继续以快速的速度发展。计算机科学通常允许一个小团队通过使用即插即用解决方案来利用其成员的专业知识，这些解决方案几乎不需要或不需要用户干预。相比之下，很明显，依赖数量有限的高技能人员在网络安全方面效果不佳。这一不足似乎可以通过应用人工智能概念和培训人工智能和网络安全方面的专家来解决。然而，在人工智能和网络安全领域变得高度熟练所需的时间、重点和努力是这一解决方案的一个重大障碍。该项目努力探索潜在的变革性教育方法，以便在人工智能和网络安全的交叉点培养一支更强大的劳动力队伍。具体地说，项目团队提出了一门协作性、基于小组的实践课程，将在人工智能或网络安全领域具有特定兴趣和现有背景的学生与具有互补背景的学生结合在一起。这种教育方法将培养出具有人工智能和网络安全相结合的思维方式的学生。该项目的基本假设是，学生将很少需要对网络安全领域内的人工智能领域应用深入的技术理解。因此，培养一支在这两个领域都能胜任的劳动力队伍的一个更可行、更简洁的方法是专注于扩展学生的工具包，并为他们提供参考锚。这种方法将使学生在进入工作队伍时能够更有效地与特定领域的专家进行协作，并跨越领域边界。为了探索这种方法，项目组提议开发一门针对具有人工智能或网络安全背景的学生的课程。本课程将结合基于问题的学习、基于工作室的学习和基于小组的学习的元素。这种方法将培养学生具有融合人工智能和网络安全的心态，尽管他们可能在非重点领域缺乏技术深度。这种心态或意识将使这些学生为进入劳动力大军并跨技术学科进行协作做好准备。虽然未来的目标可能是将人工智能和网络安全“原住民”结合起来，但重要的是首先评估更容易实现的选项，即灌输技术意识和多视角方法。该项目得到了安全和值得信赖的网络空间(SATC)计划的一项特别倡议的支持，该计划旨在促进网络安全、人工智能和教育领域之间新的、以前从未探索过的合作。SATC计划与联邦网络安全研究和发展战略计划和国家隐私研究战略保持一致，以保护和维护网络系统日益增长的社会和经济效益，同时确保安全和隐私。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Society is becoming increasingly dependent on technology that is susceptible to abuse by bad actors. Artificial Intelligence (AI) and cybersecurity are, like much of computer science, extremely technical fields that continue to advance at rapid rates both in knowledge and application. Computer science often allows a small team to leverage its members' expertise through the use of plug-and-play solutions that require little or no user intervention. In contrast, it has become obvious that reliance on a limited number of highly skilled people does not work as well for cybersecurity . This inadequacy appears to be addressable through the application of AI concepts and by training individuals who are expert in both AI and cybersecurity. However, the amount of time, focus, and effort required to become highly proficient in both AI and cybersecurity fields is a significant barrier to this solution. This project strives to explore potentially transformative educational approaches in order to prepare a more robust workforce at the intersection of AI and cybersecurity. Specifically, the project team proposes a collaborative, group-based, and hands-on course that combines students with a specific interest and existing background in either the AI or cybersecurity domain with students with the complementary background. This educational approach will produce students who share a combined AI and cybersecurity mindset.The fundamental assumption of this project is that students will rarely need to apply a deep, technical understanding of the AI field within the cybersecurity domain. As such, a more viable and succinct approach to producing a workforce competent in both domains is to focus on expanding students’ toolkits and providing them reference-anchors. This approach will enable students to more efficiently collaborate with domain-specific experts and across domain boundaries when they enter the workforce. In order to explore this approach, the project team proposes to develop a course directed at students with backgrounds in AI or cybersecurity. The course will combine elements from problem-based learning , studio-based learning, and group-based learning. This approach will cultivate students with a melded AI and cybersecurity mindset even though they may lack technical depth in their non-focus domain. This mindset or awareness will prepare these students to enter the workforce and collaborate across technical disciplines. While a future goal may be combined AI and cybersecurity “natives” it is important first to evaluate the more easily attainable option of instilling technical awareness and a multi-perspective approach. This project is supported by a special initiative of the Secure and Trustworthy Cyberspace (SaTC) program to foster new, previously unexplored, collaborations between the fields of cybersecurity, artificial intelligence, and education. The SaTC program aligns with the Federal Cybersecurity Research and Development Strategic Plan and the National Privacy Research Strategy to protect and preserve the growing social and economic benefits of cyber systems while ensuring security and privacy.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.