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REU Site: Computational Sensing for Human-centered AI

REU 网站：以人为中心的人工智能的计算传感

基本信息

批准号：
1851591
负责人：
Cecilia Alm
金额：
$ 35.99万
依托单位：
Rochester Institute of Tech
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2019
资助国家：
美国
起止时间：
2019-04-01 至 2024-03-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1851591&HistoricalAwards=false
关键词：
REU Site Computational Sensing Human

项目摘要

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.

以人为中心的人工智能计算感知本科生研究经验（REU）网站认识到人机交互（HCI）和人工智能（AI）之间的界限正在模糊，人工智能正变得越来越敏捷和普及。因此，下一代计算科学家必须能够负责任和有效地利用来自数据生成人类的一系列传感数据。有了这一重点，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，他们将获得感知硬件和软件的经验，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发现如何收集、融合、推断和可视化多模态人类数据，有助于培养一支能够改变人类和机器互动和协作方式的劳动力队伍。REU网站的研究将解决人工智能的两个局限性：首先，由于目前关注的是大数据人工智能，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的经验，也缺乏对人类引发的数据集的批判性思考。REU网站将激发新颖、安全的方式，让系统与人们合作，解决社会上令人烦恼的问题，同时保持公平、适应偏见，并代表一般人群的不同结构。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、包容性数据集的健全人工智能实验相结合；(2)制定程序性机制，帮助学生自信地从被教授过渡到被研究教师指导，并确保他们为进入计算机科学/STEM博士课程做好准备；(3)加强和加强我们的招聘策略，目标是在我们的申请者中增加一倍的印第安人或拉丁裔学生和残疾学生，并为非常多样化的群体达到更苛刻的选拔目标。我们将这些目标与四个相关的网站目标联系起来：(a)提供基于团队的研究，研究强调社会公益和影响的现实问题；(b)以具成本效益的方式，促进环境研究小组同学在校内进行国际文化交流，以提高他们的全球意识和技能；(c)为研究小组提供丰富的外展服务，以学习如何广泛传播研究成果；(d)向科学界传播从REU站点吸取的经验教训。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。

项目成果

期刊论文数量（14）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Dynamic Visualization System for Gaze and Dialogue Data

视线和对话数据的动态可视化系统

DOI：
10.5220/0008953201380145
发表时间：
2020
期刊：
Imaging and Computer Graphics Theory and Applications - HUCAPP
影响因子：
0
作者：
Kvist, Jonathan;Ekholm, Philip;Vaidyanathan, Preethi;Bailey, Reynold;Alm, Cecilia
通讯作者：
Alm, Cecilia

Capturing Laughter and Smiles under Genuine Amusement vs. Negative Emotion

在真正的娱乐与负面情绪下捕捉笑声和微笑

DOI：
10.1109/percomworkshops48775.2020.9156102
发表时间：
2020
期刊：
2020 Workshop on Human-Centered Computational Sensing - IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops
影响因子：
0
作者：
Forman, Cleo;Thiel, Pablo;Ptucha, Raymond;Dominguez, Miguel;Alm, Cecilia O.
通讯作者：
Alm, Cecilia O.

Emotional Empathy and Facial Mimicry of Avatar Faces

情感同理心和阿凡达面孔的面部模仿

DOI：
10.1109/vrw55335.2022.00236
发表时间：
2022
期刊：
2022 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW
影响因子：
0
作者：
Saquinaula, Angela;Juarez, Adriel;Geigel, Joe;Bailey, Reynold;Alm, Cecilia O.
通讯作者：
Alm, Cecilia O.

News Consumption Helps Readers Identify Model-Generated News

新闻消费帮助读者识别模型生成的新闻

DOI：
10.1109/wnyispw60588.2023.10349588
发表时间：
2023
期刊：
2023 IEEE Western New York Image and Signal Processing Workshop (WNYISPW
影响因子：
0
作者：
Kothari, Ammina;Orama, Andrea;Miller, Rachel;Peeks, Matthew;Bailey, Reynold;Alm, Cecilia
通讯作者：
Alm, Cecilia

Multimodal Modeling of Task-Mediated Confusion

任务介导的混乱的多模态建模