TWC SBE: Option: Frontier: Collaborative: Towards Effective Web Privacy Notice and Choice: A Multi-Disciplinary Prospective

自然语言隐私政策已经成为一种事实上的标准，以解决Web上对通知和选择的期望。然而，有充分的证据表明，用户通常不会阅读这些策略，偶尔阅读的用户也很难理解他们所阅读的内容。旨在通过开发机器可实现的标准或其他要求网站运营商遵守更严格要求的解决方案来解决这一问题的倡议遇到了障碍，许多网站运营商表现出不愿承诺比他们目前所做的更多的事情。该项目提供了克服当前自然语言隐私政策限制的前景，而不会对网站运营商施加新的要求。这个前沿项目建立在自然语言处理、隐私偏好建模、众包、形式化方法和隐私接口等方面的最新进展之上，以克服这种情况。它将基础研究与可扩展技术的发展相结合，从自然语言网站隐私政策中半自动提取关键隐私政策特征，并以易于消化的格式将这些特征呈现给用户，使他们能够在与不同网站交互时做出更明智的隐私决策。该项目的工作还包括系统地收集和分析网站隐私政策，寻找不同部门这些政策的措辞和内容的趋势和不足，并利用这些分析为正在进行的公共政策辩论提供信息。该项目的一个重要部分是与工业界的利益相关者密切合作，使这些技术能够转移到工业中进行大规模部署。

Natural language privacy policies have become a de facto standard to address expectations of notice and choice on the Web. Yet, there is ample evidence that users generally do not read these policies and that those who occasionally do struggle to understand what they read. Initiatives aimed at addressing this problem through the development of machine implementable standards or other solutions that require website operators to adhere to more stringent requirements have run into obstacles, with many website operators showing reluctance to commit to anything more than what they currently do. This project offers the prospect of overcoming the limitations of current natural language privacy policies without imposing new requirements on website operators.This frontier project builds on recent advances in natural language processing, privacy preference modeling, crowdsourcing, formal methods, and privacy interfaces to overcome this situation. It combines fundamental research with the development of scalable technologies to semi-automatically extract key privacy policy features from natural language website privacy policies and present these features to users in an easy-to-digest format that enables them to make more informed privacy decisions as they interact with different websites. Work in this project also involves the systematic collection and analysis of website privacy policies, looking for trends and deficiencies both in the wording and content of these policies across different sectors and using this analysis to inform ongoing public policy debates. An important part of this project is to work closely with stake holders in industry to enable the transfer of these technologies to industry for large-scale deployment.