A Human-AI interaction paradigm and its application to rhinocytology.

This article explores Human-Centered Artificial Intelligence (HCAI) in medical cytology, with a focus on enhancing the interaction with AI. It presents a Human-AI interaction paradigm that emphasizes explainability and user control of AI systems. It is an iterative negotiation process based on three interaction strategies aimed to (i) elaborate the system outcomes through iterative steps (Iterative Exploration), (ii) explain the AI system's behavior or decisions (Clarification), and (iii) allow non-expert users to trigger simple retraining of the AI model (Reconfiguration). This interaction paradigm is exploited in the redesign of an existing AI-based tool for microscopic analysis of the nasal mucosa. The resulting tool is tested with rhinocytologists. The article discusses the analysis of the results of the conducted evaluation and outlines lessons learned that are relevant for AI in medicine.

The fine line between automation and augmentation in website usability evaluation.

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.

Multimedia augmented reality game for learning math.

The traditional method for learning the multiplication tables is a repetitive and boring task. Teachers try to find new methods to motivate children in this tedious duty, and one of the lines to consider is to integrate en- tertainment into educational processes. This work presents a new multimedia interaction approach in order to allow children to practice these math opera- tions and have fun. The learning process has been gamified by means of two mini-games designed for mobile platforms, based on meromictic or repetitive learning. The genre of these mini-games have been selected according to chil- dren preferences: one turn-based fighting and other throwing-objects game. A series of proposed multiplications have to be solved during the play to per- form the player actions. Moreover, in order to support learning engagement, both have been visualized through Augmented Reality, combining real and virtual reality. This paper discusses the good results of mixing entertainment with some learning tasks, due to the engagement of the children to the mobile based games. A pilot study has been performed in order to evaluate the learn- ing effectiveness and usability of the proposal. Results support that playing the video games makes this tedious multiplication practice more enjoyable and attractive for children so they improve their math skills.