Lesandro Ponciano

Henrique Ramos, Mateus Fonseca, Lesandro Ponciano

This work focuses on the context of software explainability, which is the production of software capable of explaining to users the dynamics that govern its internal functioning. User models that include information about their requirements and their perceptions of explainability are fundamental when building software with such capability. This study investigates the process of creating personas that include information about users' explainability perceptions and needs. The proposed approach is based on data collection with questionnaires, modeling of empathy maps, grouping the maps, generating personas from them and evaluation employing the Persona Perception Scale method. In an empirical study, personas are created from 61 users' response data to a questionnaire. The generated personas are evaluated by 60 users and 38 designers considering attributes of the Persona Perception Scale method. The results include a set of 5 distinct personas that users rate as representative of them at an average level of 3.7 out of 5, and designers rate as having quality 3.5 out of 5. The median rate is 4 out of 5 in the majority of criteria judged by users and designers. Both the personas and their creation and evaluation approach are contributions of this study to the design of software that satisfies the explainability requirement.

Lesandro Ponciano, Pedro Barbosa, Francisco Brasileiro et al.

Internet of Things (IoT) systems have aroused enthusiasm and concerns. Enthusiasm comes from their utilities in people daily life, and concerns may be associated with privacy issues. By using two IoT systems as case-studies, we examine users' privacy beliefs, concerns and attitudes. We focus on four major dimensions: the collection of personal data, the inference of new information, the exchange of information to third parties, and the risk-utility trade-off posed by the features of the system. Altogether, 113 Brazilian individuals answered a survey about such dimensions. Although their perceptions seem to be dependent on the context, there are recurrent patterns. Our results suggest that IoT users can be classified into unconcerned, fundamentalists and pragmatists. Most of them exhibit a pragmatist profile and believe in privacy as a right guaranteed by law. One of the most privacy concerning aspect is the exchange of personal information to third parties. Individuals' perceived risk is negatively correlated with their perceived utility in the features of the system. We discuss practical implications of these results and suggest heuristics to cope with privacy concerns when designing IoT systems.

Lesandro Ponciano, Francisco Brasileiro, Nazareno Andrade et al.

A human computation system can be viewed as a distributed system in which the processors are humans, called workers. Such systems harness the cognitive power of a group of workers connected to the Internet to execute relatively simple tasks, whose solutions, once grouped, solve a problem that systems equipped with only machines could not solve satisfactorily. Examples of such systems are Amazon Mechanical Turk and the Zooniverse platform. A human computation application comprises a group of tasks, each of them can be performed by one worker. Tasks might have dependencies among each other. In this study, we propose a theoretical framework to analyze such type of application from a distributed systems point of view. Our framework is established on three dimensions that represent different perspectives in which human computation applications can be approached: quality-of-service requirements, design and management strategies, and human aspects. By using this framework, we review human computation in the perspective of programmers seeking to improve the design of human computation applications and managers seeking to increase the effectiveness of human computation infrastructures in running such applications. In doing so, besides integrating and organizing what has been done in this direction, we also put into perspective the fact that the human aspects of the workers in such systems introduce new challenges in terms of, for example, task assignment, dependency management, and fault prevention and tolerance. We discuss how they are related to distributed systems and other areas of knowledge.