Responsible AI for Inclusive, Democratic Societies: A cross-disciplinary approach to detecting and countering abusive language online

恶毒和辱骂的语言威胁着公共对话和民主的完整性。侮辱性语言，如嘲讽、诽谤、种族主义、极端主义、粗鲁、挑衅和伪装通常被认为是冒犯和侮辱，被认为与政治两极分化和公民冷漠；恐怖主义和激进化的兴起；以及网络欺凌有关。作为回应，世界各国政府颁布了强有力的法律，禁止导致仇恨、暴力和针对特定群体的刑事犯罪的辱骂语言。这包括及时对含有仇恨或非法语言的在线材料进行温和(即检测、评估以及可能的移除或删除)的法律义务；社交媒体公司在其使用条款上采取了更严格的规定。然而，在过去的几年里，这种网络虐待行为激增，政府、社交媒体平台和个人都在努力应对后果。负责任的(即有效、公平和不偏不倚的)对辱骂语言的节制会带来重大的实践、文化和法律挑战。虽然目前的立法和公众的愤怒要求迅速作出反应，但我们还没有有效的人力或技术程序来满足这一需要。广泛部署人类内容版主的代价高昂，而且在许多层面上都是不够的：这项工作的性质具有心理挑战性，而且重大努力落后于每秒发布的大量数据。与此同时，为解决辱骂语言而实施的人工智能(AI)解决方案引发了人们对影响基本人权的自动化过程的担忧，如言论自由、隐私和缺乏企业透明度。值得注意的是，审查互联网内容的第一步行动集中在LGBTQ社区使用的术语和艾滋病激进主义上。因此，内容审核被业界和媒体称为“数十亿美元的问题”也就不足为奇了。因此，这个项目解决了一个首要问题：如何通过将言论自由、对人权的承诺和保护不受侵犯的多文化参与结合起来，更好地利用人工智能来促进民主？我们的项目通过一种新的方法来检测和对抗辱骂语言，这是一个困难和紧迫的问题。这种方法结合了计算机科学与社会科学和人文科学的专业知识和方法。我们专注于两个因有毒而臭名昭著的群体：政客和游戏玩家。政客们，因为他们的公共角色，经常受到辱骂。网络游戏和游戏空间已被认定为私人的极端政治观点“招募网站”，并与离线暴力袭击有关。具体地说，我们的团队将量化当前内容审查系统中嵌入的偏见，这些系统使用对侮辱性语言的僵化定义或确定，可能会矛盾地产生基于身份的新形式的歧视或偏见，包括性别、性别、种族、文化、宗教、政治派别或其他。我们将通过生产更多情景感知的动态检测系统来抵消这些影响。此外，我们将通过将这些开放源码工具嵌入民主反言论和基于社区的护理和反应战略来增强用户的能力。项目成果将通过开放获取的白皮书、出版物和其他在线材料与政策、学术、行业、社区和公共利益攸关方广泛共享。该项目将吸引和培训下一代跨学科学者--这对负责任的人工智能的发展至关重要。这项研究的重点是以有效和合法的方式应对网络滥用的强大人工智能方法，以适应民主社会的活力，这项研究对加拿大和英国具有广泛的影响和相关性。

Toxic and abusive language threaten the integrity of public dialogue and democracy. Abusive language, such as taunts, slurs, racism, extremism, crudeness, provocation and disguise are generally considered offensive and insulting, has been linked to political polarisation and citizen apathy; the rise of terrorism and radicalisation; and cyberbullying. In response, governments worldwide have enacted strong laws against abusive language that leads to hatred, violence and criminal offences against a particular group. This includes legal obligations to moderate (i.e., detection, evaluation, and potential removal or deletion) online material containing hateful or illegal language in a timely manner; and social media companies have adopted even more stringent regulations in their terms of use. The last few years, however, have seen a significant surge in such abusive online behaviour, leaving governments, social media platforms, and individuals struggling to deal with the consequences. The responsible (i.e. effective, fair and unbiased) moderation of abusive language carries significant practical, cultural, and legal challenges. While current legislation and public outrage demand a swift response, we do not yet have effective human or technical processes that can address this need. The widespread deployment of human content moderators is costly and inadequate on many levels: the nature of the work is psychologically challenging, and significant efforts lag behind the deluge of data posted every second. At the same time, Artificial Intelligence (AI) solutions implemented to address abusive language have raised concerns about automated processes that affect fundamental human rights, such as freedom of expression, privacy and lack of corporate transparency. Tellingly, the first moves to censor Internet content focused on terms used by the LGBTQ community and AIDS activism. It is no surprise then that content moderation has been dubbed by industry and media as a "billion dollar problem." Thus, this project addresses the overarching question: how can AI be better deployed to foster democracy by integrating freedom of expression, commitments to human rights and multicultural participation in the protection against abuse? Our project takes on the difficult and urgent issue of detecting and countering abusive language through a novel approach to AI-enhanced moderation that combines computer science with social science and humanities expertise and methods. We focus on two constituencies infamous for toxicity: politicians and gamers. Politicians, because of their public role, are regularly subjected to abusive language. Online gaming and gaming spaces have been identified as private "recruitment sites"' for extreme political views and linked to off-line violent attacks. Specifically, our team will quantify the bias embedded within current content moderation systems that use rigid definitions or determinations of abusive language that may paradoxically create new forms of discrimination or bias based on identity, including sex, gender, ethnicity, culture, religion, political affiliation or other. We will offset these effects by producing more context-aware, dynamic systems of detection. Further, we will empower users by embedding these open source tools within strategies of democratic counter-speech and community-based care and response. Project results will be shared broadly through open access white papers, publications and other online materials with policy, academic, industry, community and public stakeholders. This project will engage and train the next generation of interdisciplinary scholars-crucial to the development of responsible AI. With its focus on robust AI methods for tackling online abuse in an effective and legally-compliant manner to the vigour of democratic societies, this research has wide-ranging implications and relevance for Canada and the UK.