In this work, we provide an industry research view for approaching the design, deployment, and operation of trustworthy Artificial Intelligence (AI) inference systems. Such systems provide customers with timely, informed, and customized inferences to aid their decision, while at the same time utilizing appropriate security protection mechanisms for AI models. Additionally, such systems should also use Privacy-Enhancing Technologies (PETs) to protect customers' data at any time. To approach the subject, we start by introducing current trends in AI inference systems. We continue by elaborating on the relationship between Intellectual Property (IP) and private data protection in such systems. Regarding the protection mechanisms, we survey the security and privacy building blocks instrumental in designing, building, deploying, and operating private AI inference systems. For example, we highlight opportunities and challenges in AI systems using trusted execution environments combined with more recent advances in cryptographic techniques to protect data in use. Finally, we outline areas of further development that require the global collective attention of industry, academia, and government researchers to sustain the operation of trustworthy AI inference systems.

翻译：本文从行业研究视角，探讨了可信人工智能（AI）推理系统的设计、部署与运营方法。此类系统在为客户提供及时、知情且定制化的推理结果以辅助其决策的同时，还需采用适当的安全保护机制保障AI模型。此外，此类系统应始终运用隐私增强技术（PETs）保护客户数据。为深入探讨该主题，我们首先介绍AI推理系统的当前发展趋势，继而阐述此类系统中知识产权（IP）与私有数据保护之间的关系。在保护机制方面，我们系统梳理了设计、构建、部署及运营私有AI推理系统所需的安全与隐私基础组件。例如，我们重点分析了结合可信执行环境与密码学技术最新进展来保护使用中数据的AI系统的机遇与挑战。最后，我们指出了需要全球工业界、学术界及政府研究人员共同关注的待发展领域，以维持可信AI推理系统的持续运营。