MAMMoth: Multi-Attribute, Multimodal Bias Mitigation in AI Systems

MAMMoth：人工智能系统中的多属性、多模式偏差缓解

• 批准号: 10041914
• 金额: $ 9.61万
• 依托单位: TRILATERAL RESEARCH LTD
• 依托单位国家: 英国
• 项目类别: EU-Funded
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=10041914
• 关键词: MAMMoth; Multi; Attribute; Multimodal; Bias

Artificial Intelligence (AI) is increasingly employed by businesses, governments, and other organizations to make decisions with far-reaching impacts on individuals and society. This offers big opportunities for automation in different sectors and daily life, but at the same time it brings risks for discrimination of minority and marginal population groups on the basis of the so-called protected attributes, like gender, race, and age. Despite the large body of research to date, the proposed methods work in limited settings, under very constrained assumptions, and do not reflect the complexity and requirements of real world applications. To this end, the MAMMOth project focuses on multi-discrimination mitigation for tabular, network and multimodal data. Through its computerscience and AI experts, MAMMOth aims at addressing the associated scientific challenges by developing an innovative fairness-aware AI-data driven foundation that provides the necessary tools and techniques for the discovery and mitigation of (multi-)discrimination and ensures the accountability of AI-systems with respect to multiple protected attributes and for traditional tabular data and more complex network and visual data. The project will actively engage with numerous communities of vulnerable and/or underrepresented groups in AI research right from the start, adopting a co-creation approach, to make sure that actual user needs and pains are at the centre of the research agenda and act as guidance to the project’s activities. A social science-driven approach supported by social science and ethics experts will guide project research, and a science communication approach will increase the outreach of the outcomes. The project aims to demonstrate through pilots the developed solutions into three relevant sectors of interest: a) finance/loan applications, b) identity verification systems, and c) academic evaluation.

人工智能（AI）越来越多地被企业、政府和其他组织使用，以做出对个人和社会产生深远影响的决策。这为不同行业和日常生活中的自动化提供了巨大的机会，但同时也带来了基于所谓的受保护属性（如性别、种族和年龄）歧视少数民族和边缘人群的风险。尽管迄今为止有大量的研究，但所提出的方法在有限的环境下工作，在非常有限的假设下工作，并且没有反映现实世界应用的复杂性和需求。为此，猛犸项目侧重于减轻表格、网络和多模态数据的多重歧视。通过其计算机科学和人工智能专家，MAMMOth旨在通过开发创新的公平意识人工智能数据驱动基础来解决相关的科学挑战，该基础为发现和减轻（多重）歧视提供必要的工具和技术，并确保人工智能系统对多个受保护属性以及传统表格数据和更复杂的网络和视觉数据的问责制。该项目将从一开始就积极参与人工智能研究中的众多弱势群体和/或代表性不足的群体，采用共同创造的方法，以确保实际用户的需求和痛苦是研究议程的中心，并作为项目活动的指导。由社会科学和伦理专家支持的社会科学驱动的方法将指导项目研究，而科学传播方法将增加成果的外延。该项目旨在通过试点将开发的解决方案应用于三个相关领域：a)金融/贷款申请，b)身份验证系统，c)学术评估。