Better Together? On the Design and Use of Explanations to Support Novices in Individual and Collective Deliberations About AI

Everyone affected by high-risk AI systems should have the chance to understand them and consider the merits and harms of their deployment. Explanations of AI systems can support this goal, yet it is rarely explored how lay audiences use them for deliberation. In this paper, we examine how explanations support groups and individuals of AI novices in learning and deciding about an AI system. We use question-driven explanations spanning four information categories and evaluate them in a task-based interview study with 8 focus groups and 12 individuals. We find that groups allow participants to use team cognition to make sense of explanations, but rely heavily on social dynamics. In contrast, single settings support focused understanding but lack exchange and discussion. We contribute suggestions to make explanation designs suitable for AI novices and discuss their use in individual and collective settings to support understanding and deliberation of AI systems.