REU Site: Computational Sensing for Human-centered AI

以人为本的人工智能计算传感本科生（REU）网站的研究经验认识到，人机交互（HCI）和人工智能（AI）之间的界限正在模糊，AI越来越敏捷和普遍。因此，下一代计算科学家必须能够负责任和有效地利用数据生成人类的传感数据。有了这个重点，REU网站将扩大其轨迹，吸引高度多样化的学生，包括女性或性别少数群体和残疾学生，他们将获得传感硬件和软件的经验，以实现专注于人类行为和认知过程的智能系统的变革性进步。让不同的利益相关者在职业生涯的早期就能发现如何收集、融合、推理和可视化多模态人类数据，这有助于培养一支能够改变人类和机器参与和协作方式的员工队伍。REU网站的研究将解决人工智能的两个局限性：首先，由于目前对大数据人工智能的关注，服务不足的人群有被边缘化的风险，其次，人工智能学员往往缺乏人类数据收集和对人类引发的数据集进行批判性思考的经验。REU网站将激发新的，安全的方法，让系统与人们合作，解决社会的棘手问题，同时保持公平，适应偏见，并代表普通人群的多样化结构。REU以人为中心的人工智能计算传感网站设定了三个雄心勃勃且可实现的目标，并将在计算和科学，技术，工程和数学（STEM）研究和教育场所广泛发布研究结果：（1）推进以人为中心的人工智能计算传感的基础研究，将人类研究与专注于适度规模的合理人工智能实验相结合，包容性数据集;（2）制定程序机制，帮助学生自信地从教学过渡到由研究教师指导，并确保他们准备进入计算机科学/STEM博士课程;和（3）加强和加强我们的招聘战略，目的是使我们的申请人中的美洲原住民或拉丁美洲/o学生和残疾学生增加一倍，以及达到更苛刻的选择目标，为异常多样化的同伙。我们将这些目标与四个相关的网站目标联系起来：（a）提供以团队为基础的研究，强调社会公益和影响的现实问题;（B）通过促进校园内REU组的国际文化交流，以具有成本效益的方式实现全球意识和技能建设;（c）为队列提供外延丰富，以学习如何广泛传播研究;以及（d）向科学界传播从REU站点中吸取的经验教训。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。

The Research Experiences for Undergraduates (REU) Site in Computational Sensing for Human-centered Artificial Intelligence recognizes that the boundaries between human-computer interaction (HCI) and artificial intelligence (AI) are blurring and that AI is growing increasingly agile and pervasive. Thus, the next generation of computational scientists must be capable of responsibly and effectively leveraging a spectrum of sensing data from data-generating humans. With this focus, the REU Site will expand its trajectory as an attractor for highly diverse students, including women or gender minorities and students with disabilities, who will gain experience with sensing hardware and software towards transformative advances in intelligent systems focused on human behaviors and cognitive processes. Enabling diverse stakeholders early in their careers to discover how to collect, fuse, make inference with, and visualize multimodal human data helps nurture a workforce that can transform how humans and machines engage and collaborate. The research in the REU Site will address two limitations in AI: first, that underserved populations are at risk of being marginalized with the present focus on big data AI and, second, that AI trainees often lack experience with human data collection and critical thinking about human-elicited datasets. The REU Site will stimulate novel, safe ways for systems to team up with people to address society's vexing problems while remaining fair, attuned to bias, and representative of the diverse fabric of the general population. The REU Site in Computational Sensing for Human-centered Artificial Intelligence sets three ambitious and attainable goals and will publish widely on the findings at computational and Science, Technology, Engineering, and Mathematics (STEM) research and education venues: (1) to advance basic research in computational sensing for human-centered AI, integrating human study with sound AI experimentation focused on modestly-sized, inclusive datasets; (2) to develop programmatic mechanisms for aiding students to transition confidently from being taught to being mentored by research faculty and ensure their readiness for entering computer science/STEM PhD programs; and (3) to enhance and intensify our recruiting strategies with the aim of doubling Native American or Latina/o students and students with disabilities among our applicant pool, as well as reach even more demanding selection targets for exceptionally diverse cohorts. We link these objectives to four associated Site aims: (a) to offer team-based research with real-world problems that emphasize social good and impact; (b) to cost-effectively enable global awareness and skills-building, by facilitating on-campus international cultural exchange for REU cohorts; (c) to provide outreach enrichment for cohorts to learn how to communicate research broadly; and (d) to disseminate lessons learned from the REU Site to the scientific community.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.