A Human-centric AI-driven Framework for Exploring Large and Complex Datasets

Human-Centered Artificial Intelligence (HCAI) is a new frontier of research at the intersection between HCI and AI. It fosters an innovative vision of human-centred intelligent systems, which are systems that take advantage of computer features, such as powerful algorithms, big data management, advanced sensors and that are useful and usable for people, providing high levels of automation and enabling high levels of human control. This position paper presents our ongoing research aiming to extend the HCAI framework for better supporting designers in creating AI-based systems

The Usability of E-learning Platforms in Higher Education: A Systematic Mapping Study

The use of e-learning in higher education has increased significantly in recent years, which has led to several studies being conducted to investigate the usability of the platforms that support it. A variety of different usability evaluation methods and attributes have been used, and it has therefore become important to start reviewing this work in a systematic way to determine how the field has developed in the last 15 years. This paper describes a systematic mapping study that performed searches on five electronic libraries to identify usability issues and methods that have been used to evaluate e-learning platforms. Sixty-one papers were selected and analysed, with the majority of studies using a simple research design reliant on questionnaires. The usability attributes measured were mostly related to effectiveness, satisfaction, efficiency, and perceived ease of use. Furthermore, several research gaps have been identified and recommendations have been made for further work in the area of the usability of online learning

Privacy Design Strategies and the GDPR: A Systematic Literature Review

Article 25 of the GDPR states that data collection, processing and management measures should be implemented following tṇhe privacy by design and privacy by default paradigms. This paper presents a systematic literature review to identify useful guidelines to support the development of GDPR-compliant software. Selected papers are categorized under 8 different data-oriented and process-oriented strategies and their contributions are reported. Future activities will highlight the HCI community’s attitude towards these new technical and organizational approaches in order to bridge the identified gaps and shortcomings

Metamorphic data sources: A user-centric paradigm to consume linked data in interactive workspaces

In the last years, the debate about the success or failure of Linked Data (LD) has been growing. Despite the ever-increasing number of available ontologies and LD datasets, there is still a limited number of applications to let people benefit from using this huge amount of data. Some evident problems relate to the limited opportunities offered to the end users, i.e., people without skills in computer programming, to access, navigate and visualize LD. Tools supporting such tasks typically do not consider the end users’ needs; even when they provide abstraction mechanisms to avoid programming, they do not properly hide the complexity of getting oriented into the plethora of available resources. Thus, they end up to be inadequate to real daily scenarios. In this paper, we propose an approach that enables end users to create visually entry points, which we call Metamorphic Data-Sources (MDSs), to query and visualize the LD without requiring any prior knowledge of semantic Web or visualization technologies. Through the MDS visual paradigm, end users can tailor ad-hoc data sources to retrieve information on topics they are interested in. The MDS creation process is also driven by a quality model that further helps users select LD elements potentially free of data quality problems. The paper also reports on the results of a user study that we conducted to assess the validity of the MDS paradigm with respect to the user needs

Scenes extraction from telementored surgery videos

The huge amount of videos, available for various purposes, makes video editing software very important and popular among people. One of the uses of video in medicine is to store surgical operations for educational or legal purposes. In particular, in telemedicine, the exchange of audio and video plays a very important role. In most cases, surgeons are inexpert in video editing; moreover, the user interface of such software tools is often very complex. This paper presents a tool to extract important scenes from surgery videos. The goal is to enable surgeons to easily and quickly extract scenes of interest

User-defined semantics for the design of IoT systems enabling smart interactive experiences

Automation in computing systems has always been considered a valuable solution to unburden the user. Internet of Things (IoT) technology best suits automation in different domains, such as home automation, retail, industry, and transportation, to name but a few. While these domains are strongly characterized by implicit user interaction, more recently, automation has been adopted also for the provision of interactive and immersive experiences that actively involve the users. IoT technology thus becomes the key for Smart Interactive Experiences (SIEs), i.e., immersive automated experiences created by orchestrating different devices to enable smart environments to fluidly react to the final users’ behavior. There are domains, e.g., cultural heritage, where these systems and the SIEs can support and provide several benefits. However, experts of such domains, while intrigued by the opportunity to induce SIEs, are facing tough challenges in their everyday work activities when they are required to automate and orchestrate IoT devices without the necessary coding skills. This paper presents a design approach that tries to overcome these difficulties thanks to the adoption of ontologies for defining Event-Condition-Action rules. More specifically, the approach enables domain experts to identify and specify properties of IoT devices through a user-defined semantics that, being closer to the domain experts’ background, facilitates them in automating the IoT devices behavior. We also present a study comparing three different interaction paradigms conceived to support the specification of user-defined semantics through a “transparent” use of ontologies. Based on the results of this study, we work out some lessons learned on how the proposed paradigms help domain experts express their semantics, which in turn facilitates the creation of interactive applications enabling SIEs

Translating Privacy Design Principles Into Human-Centered Software Lifecycle: A Literature Review

Companies and organizations involved in software development are stimulated and often obliged to consider procedures and technical solutions to guarantee data privacy and protection from the early phases of the software lifecycle. In addition, by default, personal data might be processed with the highest privacy protection level. These two requirements are Privacy by Design and Privacy by Default principles. Their importance has grown quickly in the last few years, as demonstrated by data protection regulations, like GDPR and PIPEDA, which include them as an important part of some of their articles. However, such regulations do not provide any practical or concrete indications of software requirements, and developers often lack adequate knowledge to understand the privacy prescriptions expressed in legal language. This study addresses these limitations by presenting a systematic and rigorous literature review that aims to answer the following research questions: (RQ1) How do Privacy-By-Design and Privacy-By-Default principles translate into software requirements? and (RQ2) How Privacy-By-Design and Privacy-By-Default principles integrate into a Human-Centred Design process? For RQ1, the analysis of the resulting publications led to identifying several software requirements and business processes organized along 8 data-oriented and process-oriented privacy design strategies. For RQ2, the analysis of the retrieved publications provided a comprehensive view of the HCI methodologies adopted to comply with privacy requirements identified current shortcomings, and proposed future research directions. The results have been distilled into an initial framework that may aid the development of software that must comply with such principles and aims to integrate them into an HCD process

SERENE: a Web platform for the UX semi-automatic evaluation of website

This demo presents SERENE, a Web platform for the UX semiautomatic evaluation of websites. It exploits Artificial Intelligence to predict visitors’ emotions starting from their interaction logs. The predicted emotions are shown by interactive heatmaps overlapped to the webpage to be analyzed. The concentration of negative emotions in a specific area of the webpage can help the UX experts identify UX problems