Trustworthy Machine Learning by Demonstration

Bettering Our Worlds（BOW）Ltd.正在开发软件，为机器人技术的商业和家庭应用提供可解释、可信赖和易于使用的人工智能。这项可行性研究的目标是在三个不同的领域建立这项新技术的测试平台：辅助医疗保健，动态制造和危险环境操作。在这个项目中，我们将开发一种混合机器学习方法，能够直接从熟练工人那里学习，并提供决策和行动的可解释性。该系统不仅将由熟练的人类操作员进行培训，还将集成人工操作的远程操作，作为人工智能过于困难或不可预测的任务的故障保护。BOW相信这种方法将增加对自动化的信任，并克服成本和部署时间等进入障碍。该项目及其以信任为中心的方法与BOW Ltd的长期愿景和技术路线图保持一致，该公司迄今为止已经提供了一个软件开发工具包，使任何人都可以一次编写代码并部署到任何机器人上。在iUK的帮助下，我们正在将我们在复杂技术民主化方面的专业知识应用于人工智能和机器学习，使任何人都能使用这些强大的技术。

Bettering Our Worlds (BOW) Ltd. is working on developing software that will provide explainable, trustworthy and easy to use AI for commercial and domestic applications of robotic technologies. The goal of this feasibility study is to establish test-beds for this new technology in three different domains: domiciliary healthcare, dynamic manufacturing and hazardous environment operations.Within this project we will develop a hybrid machine learning approach that is capable of learning directly from skilled workers and provide explainability of decisions and actions. The system will not only feature training by skilled human operators but also integrates human-operated teleoperation as a failsafe for tasks that are too difficult or unpredictable for the AI.BOW believes that this approach will increase trust in automation, and overcome barriers to entry such as cost and deployment time. This project and its trust-centric approach is aligned with the long term vision and technological roadmap for BOW Ltd that has so far delivered a software development kit that enables anyone to code once and deploy to any robot. With the help of iUK we are bringing our expertise in democratising complex technologies and applying it to AI and ML to empower anyone to use these powerful technologies.