对着镜头微笑：情感的隐私和政策含义AI
Smile for the Camera: Privacy and Policy Implications of Emotion AI
摘要：
在视觉图像上引入人工智能（AI）进行情感分析，消除了我们面部显示的自然主观性和上下文依赖性。情感人工智能将自己作为我们的数字工件和实时交互的算法镜头，创造了一种新的、客观的数据类别的错觉：我们的情感和精神状态。这些情感算法建立在现有公共照片的丰富网络上，以及来自监控录像或智能手机摄像头的新鲜信息，不需要额外的基础设施或图像质量的改进。为了研究情感人工智能作为一种新兴技术的潜在政策和法律补救措施，我们首先建立了一个演员，收集动机，时间尺度和空间考虑的框架，将情感人工智能与其他算法透镜区分开来。这些因素中的每一个都影响着可用的政策补救措施，并应形成对使情感人工智能在特定环境中可接受或不可接受的先决条件的持续讨论。基于我们的独特元素框架，我们研究了潜在的可用政策补救措施，以防止或补救损害。具体而言，我们的论文着眼于美国联邦贸易委员会的监管作用，欧盟一般数据保护条例（GDPR）允许情感数据汇集的差距，以及测谎技术在法律规定的证据和使用限制方面的先例。我们还研究了社会规范和适应的方式，也可以调节更广泛的使用。鉴于控制这些数据流的挑战，我们呼吁进一步研究和关注，因为情感人工智能技术仍然准备采用。
英文摘要：
The introduction of artificial intelligence (AI) on visual images for emotional analysis obliterates the natural subjectivity and contextual dependence of our facial displays. Emotion AI places itself as an algorithmic lens on our digital artifacts and real-time interactions, creating the illusion of a new, objective class of data: our emotional and mental states. Building upon a rich network of existing public photographs--as well as fresh feeds from surveillance footage or smart phone cameras--these emotion algorithms require no additional infrastructure or improvements on image quality. In order to examine the potential policy and legal remedies for emotion AI as an emerging technology, we first establish a framework of actors, collection motivations, time scales, and space considerations that differentiates emotion AI from other algorithmic lenses. Each of these elements influences available policy remedies, and should shape continuing discussions on the antecedent conditions that make emotional AI acceptable or not in particular contexts. Based on our framework of unique elements, we examine potential available policy remedies to prevent or remediate harm. Specifically, our paper looks toward the regulatory role of the Federal Trade Commission in the US, gaps in the EU's General Data Protection Regulation (GDPR) allowing for emotion data collection, and precedent set by polygraph technologies in evidentiary and use restrictions set by law. We also examine the way social norms and adaptations could grow to also modulate broader use. Given the challenges in controlling the flow of these data, we call for further research and attention as emotion AI technology remains poised for adoption.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
