How to Support Users in Understanding Intelligent Systems? Structuring the Discussion
This work addresses the problem of unclear assumptions in HCI research for improving user comprehension of opaque intelligent systems, though it is incremental as it structures existing concepts rather than introducing new methods.
The paper tackles the conceptual ambiguity in HCI regarding how to support users in understanding intelligent systems by reviewing literature and synthesizing a framework based on user questions, mindsets, involvement, and knowledge outcomes to classify and differentiate existing notions like transparency and explainability.
The opaque nature of many intelligent systems violates established usability principles and thus presents a challenge for human-computer interaction. Research in the field therefore highlights the need for transparency, scrutability, intelligibility, interpretability and explainability, among others. While all of these terms carry a vision of supporting users in understanding intelligent systems, the underlying notions and assumptions about users and their interaction with the system often remain unclear. We review the literature in HCI through the lens of implied user questions to synthesise a conceptual framework integrating user mindsets, user involvement, and knowledge outcomes to reveal, differentiate and classify current notions in prior work. This framework aims to resolve conceptual ambiguity in the field and enables researchers to clarify their assumptions and become aware of those made in prior work. We thus hope to advance and structure the dialogue in the HCI research community on supporting users in understanding intelligent systems.