REU Site: Interdisciplinary AI Research for Undergraduates

REU 网站:本科生跨学科人工智能研究

基本信息

  • 批准号:
    2150643
  • 负责人:
  • 金额:
    $ 40.5万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2022
  • 资助国家:
    美国
  • 起止时间:
    2022-07-01 至 2025-06-30
  • 项目状态:
    未结题

项目摘要

The overall aim of the REU Site is to provide undergraduate students with a research experience that leads to publishable work in interdisciplinary Artificial Intelligence, as well as educate students in the ethics of Artificial Intelligence (AI). AI is having increasing impact in our everyday lives, whether through interacting with smart speakers and digital assistants, preventing collisions, discovering new medicines, intelligent tutoring, Google Translate, and many more avenues. AI is also one of the most controversial new technologies, as many critiques have been made concerning its potential risk as an existential threat, its use as a tool of oppression by authoritarian governments, its use in sentencing decisions by judges, and its biases due to datasets based on human judgments. It is imperative that students and the public become aware of the promise and the potential impacts, good or bad, on our future. In addition, a 2016 World Economic Forum Report “The Future of Jobs 2018” estimates that there will be 58 million new jobs in AI by 2022. Hence, more students, and more diverse students, must be recruited and trained in AI methods and ethics. This project will train eleven students per year for three years, including half from local community colleges, to prepare them for careers in responsible AI.This project will train eleven students per year in interdisciplinary Artificial Intelligence, as well as the ethics of AI research, including its potential benefits and dangers. In addition, the approach is collaborative, rather than competitive, research, as modern AI discoveries will be made by researchers who are willing to work with scientists from other disciplines in order to be able to approach problems with the best tools available no matter what discipline created them. Introducing students to this collaborative approach to Artificial Intelligence is a necessary step to prepare them to contribute to science as it is practiced in the 21st century. A crucial aspect of the project is that it is a thirty week academic year program, giving the trainees the necessary time to absorb the material, think about the project, develop approaches, and test them. The program will begin with an AI Boot Camp, which will meet the first eight Saturdays of the academic year, giving the students a crash course in gradient descent and its application in deep learning. The students will begin with heavily scaffolded starter projects that will give them an initial taste of success. From there, they will apply acquired skills to interdisciplinary projects being carried out in active research labs at UC San Diego. The project mentors include faculty who are using AI in their research in the departments of Computer Science and Engineering, Electrical and Computer Engineering, Cognitive Science, Linguistics, Psychology, and the Contextual Robotics Institute.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.
REU网站的总体目的是为本科生提供研究经验,从而导致在跨学科人工智能中发布可发表的工作,并教育学生的人工智能伦理学(AI)。通过与智能扬声器和数字助手的互动,防止碰撞,发现新药物,智能辅导,Google翻译和更多途径,AI在我们的日常生活中的影响越来越大。 AI也是最具争议的新技术之一,因为许多关键标语是关于其作为现有威胁的潜在风险,专制政府用作意见工具的潜在风险,法官在判决决定中的使用以及其偏见以及基于人类法官的数据集。学生和公众必须意识到对我们未来的承诺和潜在影响,好坏。此外,2016年世界经济论坛报告“ 2018年的就业未来”估计,到2022年,AI将有5800万个新工作。因此,必须以AI方法和道德规范的方式招募和培训更多的学生和更多的学生。该项目将每年培训三年的学生三年,其中包括当地社区学院的一半,为他们的职业生涯做好准备。该项目每年将培训11名学生在跨学科人工智能中的11名学生,以及AI研究的伦理,包括其潜在利益和危险。此外,这种方法是协作的,而不是竞争性的研究,因为现代的AI发现将由愿意与其他学科的科学家合作的研究人员进行,以便能够使用最佳工具来解决问题,无论他们创造了什么纪律。向学生介绍这种对人工智能的协作方法是为他们做好准备,以便他们为科学做出贡献,因为它是在21世纪实践的。该项目的一个关键方面是,这是一个三十周的学年计划,为受训者提供了吸收材料,考虑项目,开发方法和测试的必要时间。该计划将从AI新兵训练营开始,该训练营将符合学年的前八个星期六,使学生在梯度下降及其在深度学习中的应用。学生将从大量脚手架的入门项目开始,这将使他们最初的成功味道。从那里开始,他们将在圣地亚哥分校的活跃研究实验室中将获得的技能应用于正在进行的跨学科项目。该项目导师包括在计算机科学和工程,电气和计算机工程,认知科学,语言学,心理学和上下文机器人学院的研究中使用AI的教师。该奖项反映了NSF的法定任务,并通过使用该基金会的知识分子功能和广泛影响来评估NSF的法定任务,并被认为是珍贵的支持。

项目成果

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Garrison Cottrell其他文献

Garrison Cottrell的其他文献

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{{ truncateString('Garrison Cottrell', 18)}}的其他基金

RET Site: Research Experience for Teachers in Interdisciplinary AI
RET 网站:跨学科人工智能教师的研究经验
  • 批准号:
    2206884
  • 财政年份:
    2023
  • 资助金额:
    $ 40.5万
  • 项目类别:
    Standard Grant
CRCNS US-Japan Research Proposal: Modeling the Dynamic Topological Representation of the Primate Visual System
CRCNS 美日研究提案:灵长类视觉系统的动态拓扑表示建模
  • 批准号:
    2208362
  • 财政年份:
    2022
  • 资助金额:
    $ 40.5万
  • 项目类别:
    Standard Grant
inter Science of Learning Center Conference
国际学习中心科学会议
  • 批准号:
    1542748
  • 财政年份:
    2015
  • 资助金额:
    $ 40.5万
  • 项目类别:
    Standard Grant
REU Site: The Temporal Dynamics of Learning
REU 网站:学习的时间动态
  • 批准号:
    1263405
  • 财政年份:
    2013
  • 资助金额:
    $ 40.5万
  • 项目类别:
    Continuing Grant
inter-Science of Learning Centers Conference
学习中心间科学会议
  • 批准号:
    1212288
  • 财政年份:
    2012
  • 资助金额:
    $ 40.5万
  • 项目类别:
    Standard Grant
RI: Small: A Hierarchical Approach to Unsupervised Feature Discovery
RI:小型:无监督特征发现的分层方法
  • 批准号:
    1219252
  • 财政年份:
    2012
  • 资助金额:
    $ 40.5万
  • 项目类别:
    Standard Grant
Temporal Dynamics of Learning
学习的时间动态
  • 批准号:
    1041755
  • 财政年份:
    2011
  • 资助金额:
    $ 40.5万
  • 项目类别:
    Cooperative Agreement
REU Site: The Temporal Dynamics of Learning
REU 网站:学习的时间动态
  • 批准号:
    1005256
  • 财政年份:
    2010
  • 资助金额:
    $ 40.5万
  • 项目类别:
    Standard Grant
The Temporal Dynamics of Learning
学习的时间动态
  • 批准号:
    0542013
  • 财政年份:
    2006
  • 资助金额:
    $ 40.5万
  • 项目类别:
    Cooperative Agreement
CISE Research Instrumentation: Active Learning for Text, Scene, and Biosequence Analysis
CISE 研究仪器:用于文本、场景和生物序列分析的主动学习
  • 批准号:
    9617307
  • 财政年份:
    1997
  • 资助金额:
    $ 40.5万
  • 项目类别:
    Standard Grant

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REU 网站:科学与工程领域的在线跨学科大数据分析
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    2348755
  • 财政年份:
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  • 批准号:
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REU 网站:气候科学研究和推广跨学科培训 (IT-ROCS)
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REU 网站:本科生在跨学科环境中整合研究、教育和职业发展的暑期体验
  • 批准号:
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  • 财政年份:
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