SBIR Phase I: A Human-Aware Platform for Socially Collaborative Personal Artificial Intelligence (AI) Assistants

SBIR 第一阶段：用于社交协作个人人工智能 (AI) 助理的人类感知平台

• 批准号: 2223224
• 负责人: Crystal Chao
• 金额: $ 27.5万
• 依托单位: APPLIED SENTIENCE INC.
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-05-01 至 2024-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2223224&HistoricalAwards=false
• 关键词: SBIR; Phase; Human; Aware; Platform

The broader impact of this Small Business Innovation Research (SBIR) Phase I project is enabling Artificial Intelligence (AI) assistants to become proactive, empowering them to provide better service to users. Currently, commercial AI assistants respond to user requests reactively. The technologies developed in this project would provide AI assistants with the situational awareness to understand users’ lives and predict their needs. The technology will also enable social intelligence to take the initiative to support users in appropriate ways. This SBIR Phase I project will apply these technologies to a consumer product for assisting users with time management and meeting goals while establishing and strengthening healthy, desirable habits in their daily lives. Proactive personal AI assistants have the potential to improve productivity, convenience, and quality of life for every person, as well as to promote aging in place with greater independence and wellness. Fundamental scientific advancements will also enable a new generation of potential applications for AI assistants across sectors, fueling economic growth and creating jobs. This project addresses two central technical challenges for enabling proactive AI assistants: contextual awareness of users and agent-initiated interaction. Contextual awareness includes the AI agent’s real-time understanding of current user state and activity, as well as a long-term understanding of past user habits. The project proposes to develop hybrid computational models combining machine learning of multimodal user observations from visual, acoustic, and geolocation data with probabilistic graphical models that perform long-term inference and prediction over historical user observations. A virtually-embodied AI agent will leverage these contextual awareness representations to conduct real-time, face-to-face collaborations with users. The project proposes to research and develop a dynamic scheduling approach to proactively enable the agent to communicate with users. These models will be integrated within a broader system that assists users with time management. This system will implement an end-to-end architecture for protecting user privacy while handling their data. The technical solution will be validated based on quantitative metrics related to utility and user acceptance by deploying the prototype in end users’ homes over a multi-week period and conducting surveys about their subjective experience of the proactive AI assistants.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.

这项小型企业创新研究（SBIR）I阶段项目的更广泛影响正在使人工智能（AI）助手变得积极主动，使他们能够为用户提供更好的服务。目前，商业AI助手反应反应对用户的要求做出反应。该项目中开发的技术将为AI助手提供情境意识，以了解用户的生活并预测他们的需求。该技术还将使社会情报以适当的方式主动支持用户。该SBIR I期项目将把这些技术应用于消费产品，以帮助用户时间管理和实现目标，同时建立和增强日常生活中健康，理想的习惯。积极主动的个人AI助手有可能提高每个人的生产力，便利性和生活质量，并以更大的独立性和健康来促进老化。基本的科学进步还将为跨部门的AI助手提供新一代的潜在应用，推动经济增长和创造就业机会。该项目解决了实现主动AI助手的两个核心技术挑战：对用户的上下文意识和代理引发的互动。上下文意识包括AI代理对当前用户状态和活动的实时理解，以及对过去用户习惯的长期理解。该项目的建议是开发混合计算模型，结合了来自视觉，声学和地理位置数据的多模式用户观察的机器学习与概率图形模型，这些模型对历史用户观察进行了长期推断和预测。虚拟型的AI代理将利用这些上下文意识表示形式来与用户进行实时，面对面的合作。该项目的建议是研究和开发一种动态调度方法，以主动使代理商与用户沟通。这些模型将集成到更广泛的系统中，该系统可以帮助用户进行时间管理。该系统将实施端到端体系结构，以在处理其数据时保护用户隐私。该技术解决方案将基于与实用性和用户接受有关的定量指标通过在为期一周的最终用户家庭中部署原型和用户接受的验证，并对他们在积极主动的AI助手的主题经验进行调查。该奖项反映了NSF的法定任务，反映了通过使用基础的智力效果和宽阔的评估来评估的支持。