It takes two to tango: a synergistic approach to human-machine decision making

探戈需要两个人：人机决策的协同方法

• 批准号: 10082666
• 金额: $ 53.87万
• 依托单位: SWANSEA UNIVERSITY
• 依托单位国家: 英国
• 项目类别: EU-Funded
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=10082666
• 关键词: takes; two; tango; synergistic; approach

Artificial Intelligence (AI) holds enormous potential for enhancing human decisions, improving cognitive overload and lowering bias in high-stakes scenarios. Adoption of AI-based support systems in such applications is however minimal, chiefly due to the difficulty of assessing their assumptions, limitations and intentions. In order to realise the promise of AI for individuals, society and economy, people should feel they can trust AIs in terms of reliability, capacity to understand the human’s needs, and guarantees that they are genuinely aiming at helping them. TANGO will develop the theoretical basis and computational framework for hybrid decision support systems (HDSS) in which humans and machines are aligned in terms of values and goals, know their respective strengths, and work together to reach an optimal decision. To this end, TANGO will develop: 1) A cognitive theory of mutual understanding and hybrid decision making, of intuitive vs deliberative approaches to decision making and of how they affect our trust in human and AI teammates. 2) Cognition aware explainable AIsimplementing synergistic human-machine interaction, enabling machinesto determine what information a specific decision maker (e.g., layperson vs expert) needs, or does not need, to reach an informed decision. 3) A “Human-in-the-loop” co-evolution of human decision making and machine learning models building on bi-directional, explanation-augmented interlocution. The TANGO framework will be evaluated on four high impact use cases, namely supporting: i) women during pregnancy and postpartum, ii) surgical teamsin intraoperative decision making, iii) loan officers and applicantsin credit lending decision processes, and iv) public policy makers in designing incentives and allocating funds. Success in these case studies will establish TANGO as the framework of reference for developing a new generation of synergistic AI systems, and will strengthen the leadership of Europe in human-centric AI

人工智能（AI）在增强人类决策、改善认知过载和降低高风险场景中的偏见方面具有巨大的潜力。然而，在这些应用中采用基于人工智能的支持系统的可能性很小，主要是由于难以评估它们的假设、限制和意图。为了实现人工智能对个人、社会和经济的承诺，人们应该感到他们可以在可靠性、理解人类需求的能力方面信任人工智能，并保证它们真正旨在帮助人类。TANGO将为混合决策支持系统（HDSS）开发理论基础和计算框架，在该系统中，人类和机器在价值观和目标方面保持一致，了解各自的优势，并共同努力以达成最佳决策。为此，TANGO将开发：1）相互理解和混合决策的认知理论，直觉与深思熟虑的决策方法，以及它们如何影响我们对人类和人工智能队友的信任。2)认知感知可解释AI实现协同人机交互，使机器能够确定特定决策者（例如，外行vs专家）需要或不需要达成知情决定。3)人类决策和机器学习模型的“人在回路”共同进化，建立在双向的、增强的对话基础上。TANGO框架将在四个高影响力用例中进行评估，即支持：i）怀孕和产后期间的妇女，ii）手术团队术中决策，iii）信贷人员和申请人在信贷决策过程中，以及iv）公共政策制定者在设计激励措施和分配资金方面。这些案例研究的成功将使TANGO成为开发新一代协同AI系统的参考框架，并将加强欧洲在以人为本的AI领域的领导地位。