HarmonicAI: Human-guided collaborative multi-objective design of explainable, fair and privacy-preserving AI for digital health

人工智能（AI）是现代医疗保健系统数字化转型的最重要支柱之一，它将利用通过可穿戴设备和传感器收集的越来越多的真实世界数据，并考虑疾病与个人/人群之间的多种复杂相互作用。虽然支持人工智能的数字医疗服务和产品在数量和种类上迅速扩大，但大多数人工智能创新仍处于概念验证的形式。关于人工智能是否值得信任，人们一直在争论。欧盟人工智能HLEG定义了值得信赖的人工智能系统应该是合法的、道德的和强大的。要将其转化为可操作的做法，提供可解释性、公平性和隐私性至关重要。在可解释的人工智能、公平的人工智能和保护隐私的人工智能领域进行了大量的研究。然而，目前解决这三个挑战的研究工作是分散的，并且以各种各样的解决方案告终，这些解决方案具有异构的、不可互操作的，甚至是相互冲突的功能。HarmonicAI的宏伟愿景是建立一个人机协作的多目标设计框架，以促进数字健康领域可连贯解释、公平和保护隐私的人工智能。HarmonicAI汇集了人工智能、医疗保健、物联网、数据科学、隐私、网络安全、软件工程、HCI和工业设计等领域的资深专家，其基本共同目标是为人工智能从业者制定具体的技术和操作指南，以设计以人为本、特定领域、面向需求、值得信赖的人工智能解决方案。加快以人工智能为动力的数字卫生服务的可扩展部署，并向公众保证，正在以合乎道德和值得信赖的方式开发和使用数字卫生中的人工智能。

Artificial Intelligence (AI) is one of the most significant pillars for the digital transformation of modern healthcare systems which will leverage the growing volume of real-world data collected through wearables and sensors, and consider multitude of complex interactions between diseases and individual/population. While AI-enabled digital health services and products are rapidly expanding in volume and variety, most of the AI innovations remain in the form of proof-of-concept. There is a continuous debate regarding whether AI is worthy of trust. The EU AI HLEG has defined that trustworthy AI systems should be lawful, ethical and robust. To translate it into actionable practices, provision of explainability, fairness and privacy is crucial. A considerable volume of research has been conducted in the areas of explainable AI, fair AI and privacy-preserving AI. However, the current research efforts to tackle the three challenges are fragmented and have culminated in a variety of solutions with heterogeneous, non-interoperable, or even conflicting capabilities. The ambitious vision of HarmonicAI is to build a human-machine collaborative multi-objective design framework to foster coherently explainable, fair and privacy-preserving AI for digital health. HarmonicAI draws together proven experts in AI, health care, IoT, data science, privacy, cyber security, software engineering, HCI and industrial design with an underlying common aim to develop concrete technical and operational guidelines for AI practitioners to design human-centered, domain-specific, requirement-oriented trustworthy AI solutions, accelerating the scalable deployment of AI-powered digital health services and offering assurance to the public that AI in digital health is being developed and used in an ethical and trustworthy manner.