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、改善认知超负荷和减少高风险场景中的偏见方面拥有巨大潜力。然而，在此类应用中采用基于人工智能的支持系统的情况很少，这主要是由于难以评估其假设、限制和意图。为了实现人工智能对个人、社会和经济的承诺，人们应该相信人工智能的可靠性、理解人类需求的能力，并保证人工智能的真正目的是帮助人类。 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，并共同努力达成最佳决策。为此，TANGO 将开发：1）关于相互理解和混合决策、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的认知理论。 2）认知意识可解释人工智能实现协同人机交互，使机器能够确定特定决策者（例如外行与专家）需要或不需要哪些信息来做出明智的决策。 3）基于双向、解释增强对话的人类决策和机器学习模型的“人在环”共同进化。 TANGO 框架将根据四个高影响力用例进行评估，即支持：i) 怀孕和产后妇女，ii) 术中决策中的手术团队，iii) 信贷决策过程中的信贷员和申请人，以及 iv) 公共政策制定者设计激励措施和分配资金。这些案例研究的成功将使 TANGO 成为开发新一代协同人工智能系统的参考框架，并将加强欧洲在以人为中心的人工智能领域的领导地位