E-LENS: User Requirements-Oriented AI Ethics Assurance
This work addresses the problem of practical AI ethics assurance for developers and users, though it is incremental by adapting safety assurance methods from critical systems to AI ethics.
The paper tackles the challenge of assuring AI ethics in real-world applications by introducing a user requirements-oriented AI ethics assurance approach, which is implemented in the E-LENS platform and demonstrated effective in a case study on an AI-driven human resource shortlisting system.
Despite the much proliferation of AI ethical principles in recent years, there is a challenge of assuring AI ethics with current AI ethics frameworks in real-world applications. While system safety has emerged as a distinct discipline for a long time, originated from safety concerns in early aircraft manufacturing. The safety assurance is now an indispensable component in safety critical domains. Motivated by the assurance approaches for safety-critical systems such as aviation, this paper introduces the concept of AI ethics assurance cases into the AI ethics assurance. Three pillars of user requirements, evidence, and validation are proposed as key components and integrated into AI ethics assurance cases for a new approach of user requirements-oriented AI ethics assurance. The user requirements-oriented AI ethics assurance case is set up based on three pillars and hazard analysis methods used in the safety assurance of safety-critical systems. This paper also proposes a platform named Ethical-Lens (E-LENS) to implement the user requirements-oriented AI ethics assurance approach. The proposed user requirements-based E-LENS platform is then applied to assure AI ethics of an AI-driven human resource shortlisting system as a case study to show the effectiveness of the proposed approach.