ULTIMATE: mUlti-Level Trustworthiness to IMprove the Adoption of hybrid arTificial intelligencE

最终：多级可信度以提高混合人工智能的采用

• 批准号: 10038467
• 金额: $ 51.34万
• 依托单位: CBRNE LIMITED
• 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=10038467
• 关键词: ULTIMATE; mUlti; Level; Trustworthiness; IMprove

AI has entered the business mainstream, opening opportunities to boost productivity and innovation but suffer limitations hindering wider adoption of model-based or data-driven AI algorithms in industrial settings. Both approaches complement each other and form a critical foundation for the adoption of AI in industry. However, hybrid AI does not fully address the issue of trust (validity, explainability, and ethics). ULTIMATE will pioneer the development of industrial-grade hybrid AI based on three stages to ensure trustworthiness, relying on interdisciplinary data sources and adhering to physical constraints (1st stage), as well as the development of tools for explaining, evaluating and validating hybrid AI algorithms and asserting their adherence to ethical and legal regulations (2nd stage). These will be exemplified using real-world industrial use cases (3rd stage) in the Robotics (collaboration between human and robots for logistics activities) and Space domains (Failure detection for satellites) to promote the widespread adoption of hybrid AI in industry. The breakthrough generic hybrid AI architectures with improved explainability and interpretability and the predictive model on trustworthiness developed in ULTIMATE will provide industrials with improved shopfloor efficiency (reduction of downtime by 30% and of operational costs) and empower their staff through trustful human/machine cooperation allowing highly skilled jobs and increasing decision power and safety. This will be beneficial to European industry to gain pre-emptive advantage in the market of industrial AI solutions and will eventually increase trustworthiness in the use of hybrid AI components by the wider public. Extending over 36 months, the ULTIMATE project brings together key industrial stakeholders, with relevant end-users from manufacturing sectors, leading academic and research institutions, and SMEs to collaboratively investigate and lead the development of hybrid AI approaches.

人工智能已经进入商业主流，为提高生产力和创新提供了机会，但也存在限制，阻碍了基于模型或数据驱动的人工智能算法在工业环境中的广泛采用。这两种方法相互补充，并为人工智能在工业中的应用奠定了重要基础。然而，混合人工智能并不能完全解决信任问题（有效性、可解释性和道德）。ULTIMATE将基于三个阶段率先开发工业级混合人工智能，以确保可信度，依赖跨学科数据源并遵守物理约束（第一阶段），以及开发用于解释，评估和验证混合人工智能算法并声明其遵守道德和法律的法规的工具（第二阶段）。这些将使用机器人（人类和机器人之间的物流活动协作）和空间领域（卫星故障检测）中的真实工业用例（第三阶段）来举例说明，以促进混合人工智能在工业中的广泛采用。突破性的通用混合人工智能架构具有更好的可解释性和可解释性，ULTIMATE开发的可信度预测模型将为工业提供更高的车间效率（减少30%的停机时间和运营成本），并通过可靠的人机合作为员工提供高技能工作，提高决策能力和安全性。这将有利于欧洲工业在工业人工智能解决方案市场上获得先发制人的优势，并最终提高更广泛公众使用混合人工智能组件的可信度。ULTIMATE项目为期36个月，汇集了主要的工业利益相关者，来自制造业的相关最终用户，领先的学术和研究机构以及中小企业，共同研究和领导混合人工智能方法的开发。