The Fine Line between Automation and Augmentation in Website Usability Evaluation
Andrea Esposito, Giuseppe Desolda, Rosa LanzilottiAbstract
Artificial Intelligence (AI) systems are becoming widespread in all aspects of society, bringing benefits to the whole economy. There is a growing understanding of the potential benefits and risks of this type of technology. While the benefits are more efficient decision processes and industrial productivity, the risks may include a potential progressive disengagement of human beings in crucial aspects of decision-making. In this respect, a new perspective is emerging that aims at reconsidering the centrality of human beings while reaping the benefits of AI systems to augment rather than replace professional skills: Human-Centred AI (HCAI) is a novel framework that posits that high levels of human control do not contradict high levels of computer automation. In this paper, we investigate the two antipodes, automation vs augmentation, in the context of website usability evaluation. Specifically, we have analyzed whether the level of automation provided by a tool for semi-automatic usability evaluation can support evaluators in identifying usability problems. Three different visualizations, each one corresponding to a different level of automation, ranging from a full-automation approach to an augmentation approach, were compared in an experimental study. We found that a fully automated approach could help evaluators detect a significant number of medium and high-severity usability problems, which are the most critical in a software system; however, it also emerged that it was possible to detect more low-severity usability problems using one of the augmented approaches proposed in this paper.
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To Automate or To Augment Humans? That is the Question for AI, and The Answer Depends on Users’ Requirements
May 2, 2024
The growing influence of AI brings benefits and risks. Our research explores how human-centred AI balances automation and human control in website usability evaluation. It shows how AI streamlines the detection of critical usability issues while augmented approaches also uncover less severe issues.
