EAGER: SaTC: Towards Accounting for the Human in Emotion Recognition Technologies

情感是强大的，调解人类与周围环境的经历，影响决策和注意力。隐私和情感是相关的概念；无论是在线上还是线下，情绪通常都被视为隐私。与他人分享和表达自己的情绪可能是有益的，但涉及隐私计算和复杂的决策过程。尽管人类情感具有深刻的个人性质，但人们正在构建人工智能（AI）算法，利用社交媒体行为、流媒体服务使用、语音、面部表情、生物识别和肢体语言等数据源，以用户通常不知道的方式识别和推断情感。到2025年，情感识别的新兴市场预计将增长到38亿美元。该项目假设情感识别技术可以优先考虑他们影响的人类的隐私和偏好。这个项目通过调查人们对情感识别的态度，以及用户和技术人员对这项技术的看法，逐步解决用户的隐私和其他问题。这个项目加深了关于新兴技术隐私和安全的智力对话；伦理与人工智能、数据科学和研究之间的互动；以及社交媒体设计。技术专家、政策制定者和诸如计算、经济学和医学等领域的研究人员可以使用这个项目的结果框架来评估系统的潜在影响。此外，该项目的主题提供了一个重要的背景，挑战学生在教学和研究中深入思考道德，隐私，社会责任和技术-这对于培养负责任和有思想的下一代信息和计算专业人员至关重要。这项工作将专注于情感和用户对情感识别技术的态度，以帮助我们了解在影响个人生活的算法决策中对数据的社会和道德负责的使用和处理。使用以人为中心的镜头，这项工作将提供一个指导框架，在这个框架内，可以评估情感识别技术与人们的价值观、需求和关注点的兼容性。研究团队将1)对人工制品（包括专利）进行一系列批判性分析，以询问技术专家和学者阐明情感识别技术在应用领域的重要性的方式，以及它的用例、愿景和含义（例如，道德、隐私、个人、人际关系、社会）；2)使用访谈、小短文和焦点小组来研究社交媒体用户对情绪识别的态度及其对他们隐私和生活的感知影响，突出可能利用情绪识别的可信赖或不可信赖的网络空间的因素。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。

Emotions are powerful, mediate human experiences with their surroundings, and impact decision-making and attention online and off. Privacy and emotion are related concepts; online and off, emotions are often deemed private. Sharing and signaling one's emotions to other humans can be beneficial, but involves privacy calculations and complex decision-making processes. Despite the deeply personal nature of human emotion, artificial intelligence (AI) algorithms are being built to recognize and infer emotions using data sources such as social media behavior, streaming service use, voice, facial expressions, biometrics, and body language in ways often unknown to users. Emotion recognition’s emerging market is expected to grow to $3.8 billion by 2025. This project posits that emotion recognition technologies can prioritize the privacy and preferences of the humans they impact. This project takes steps toward addressing users' privacy and other concerns by investigating people's attitudes towards emotion recognition and how users and technologists conceive of this technology. This project deepens intellectual conversations about emerging technologies' privacy and safety; interactions between ethics and AI, data science, and research; and social media design. Technologists, policy makers, and researchers in fields such as computing, economics, and medicine can use this project’s resulting framework to evaluate systems' potential implications. Furthermore, the project’s topic provides an important context to challenge students to think deeply about ethics, privacy, social responsibility, and technology in teaching and research — crucial for generating a responsible and thoughtful next generation of information and computing professionals.This work will focus on emotions and users' attitudes towards emotion recognition technologies to contribute to our knowledge about socially and ethically responsible use and treatment of data in algorithmic decision-making that impacts personal lives. Using a human-centered lens, this work will contribute a framework of guidelines within which emotion recognition technologies can be evaluated for compatibility with people's values, needs, and concerns. The research team will 1) conduct a series of critical analyses of artifacts, including patents, to interrogate the ways technologists and academics articulate emotion recognition technology's importance across application domains, and its use-cases, visions, and implications (e.g., ethical, privacy, personal, inter-personal, social); and 2) use interviews, vignettes, and focus groups to examine social media users' attitudes towards emotion recognition and its perceived impacts on their privacy and their lives, highlighting factors contributing to a trustworthy or untrustworthy cyberspace that may utilize emotion recognition.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.