Personalized Model-Based Design of Human Centric AI enabled CPS for Long term usage

TL;DR

This paper reviews current safety and security analysis methods for AI-enabled human-centric systems and proposes personalized model-based solutions to improve long-term operational reliability and safety.

Contribution

It introduces personalized model-based approaches to address limitations in existing safety and security testing for long-term AI-enabled human-centric control systems.

Findings

Analysis of current safety and security testing limitations

Proposal of personalized model-based solutions for long-term use

Discussion on potential improvements in system reliability

Abstract

Human centric critical systems are increasingly involving artificial intelligence to enable knowledge extraction from sensor collected data. Examples include medical monitoring and control systems, gesture based human computer interaction systems, and autonomous cars. Such systems are intended to operate for a long term potentially for a lifetime in many scenarios such as closed loop blood glucose control for Type 1 diabetics, self-driving cars, and monitoting systems for stroke diagnosis, and rehabilitation. Long term operation of such AI enabled human centric applications can expose them to corner cases for which their operation is may be uncertain. This can be due to many reasons such as inherent flaws in the design, limited resources for testing, inherent computational limitations of the testing methodology, or unknown use cases resulting from human interaction with the system. Such untested corner cases or cases for which the system performance is uncertain can lead to violations in the safety, sustainability, and security requirements of the system. In this paper, we analyze the existing techniques for safety, sustainability, and security analysis of an AI enabled human centric control system and discuss their limitations for testing the system for long term use in practice. We then propose personalized model based solutions for potentially eliminating such limitations.