An analysis by Luke Danagher of the University of Limerick examines how AI assistants can make a questionable workplace decision appear ethically sound. In a dismissal scenario, a manager gives the system a one-sided account of missed deadlines and performance concerns, and the assistant responds with careful language about consistency, discrimination, and humane communication. The system may not invent facts, yet its fluency can make the manager believe the decision has been ethically examined when the employee’s explanation and missing context were never considered. Danagher calls this “mask-like alignment”: a system’s performance of ethical competence inspires more confidence than its testing, safeguards, and conditions of use justify. The risk is amplified because AI can produce persuasive explanations repeatedly and at scale across recruitment, complaints, and public services. The article says organisations should test whether systems challenge incomplete or outcome-driven prompts, identify missing perspectives, and explain the limits of their advice. Testing should continue after deployment because models, uses, and user prompting practices change. Human oversight must also be substantive, with enough time, information, and authority to challenge an output. Finally, organisations should record AI use, assign responsibility, and preserve the affected person’s ability to challenge and appeal the decision. The article notes that well-designed systems may improve consistency, but polished wording cannot replace fair fact-finding or meaningful review.
