Wearable technologies involve the integration of technology into clothing or accessories to bring new functionalities for people on the move. Many examples of wearables are emerging, from simple fitness tracking watches to electronics deeply embedded into garments for multi-touch sensing and control for personal music players. Without careful development, wearables can have a negative impact on the environment due to increased production of electronic components, increased e-waste from abandoned devices, and increased energy usage. We examine environmental sustainability issues through a review of recent research and cases across three broad areas including the fashion industry, information and communications technology (ICT), and wearable technologies. In the analysis, we examine stages in the product life cycle and identify the unique issues for each sector, including the extraction of materials, production process, distribution of products, use, and disposal of products that have reached the end of their life. The findings are gathered as implications for design so that researchers, educators, designers, developers, and product managers will gain an overview of the issues related to environmental sustainability. Related examples of products and prototypes are provided to enable informed choices during the design and development of wearables that are more environmentally sustainable.

Echoing the evolving interest and impact of artificial intelligence on society, governments are increasingly looking for ways to strategically position themselves as both innovators and regulators in this new domain. One of the most explicit and accessible ways in which governments outline these plans is through national strategy and policy documents. We follow a systematic search strategy to identify national AI policy documents across twenty-five countries. Through an analysis of these documents, including topic modelling, clustering, and reverse topic-search, we provide an overview of the topics discussed in national AI policies and contrast the differences between countries. Furthermore, we analyse the frequency of eleven ethical principles across our corpus. Our paper outlines implications of the differences between geographical and cultural clusters in relation to the future development of artificial intelligence applications.

Digital personal assistants (DPAs) have recently grown in popularity because they are both a commercially available new technology and reasonably affordable to the average household. This opens opportunities for new ways to assist people in everyday activities in their homes through voice-interaction. Physical activity has significant health benefits, and yet globally, 1 in 4 adults are not active enough. To address this, we investigate the persuasive potential of DPAs in increasing people’s physical activity at home. We conducted a study with 48 participants to understand the effect of applying three of Fogg’s persuasive principles to the design of a DPA exercise programme: Suggestion, Virtual Reward, and Praise. Our findings show that DPAs have the potential, within their current technical and reactive capabilities, to persuade people to increase their physical activity at home, using Suggestion to encourage physical effort, Virtual Reward to encourage endurance, and Praise to create reassurance for beginners. Based on this, we offer three alternate perspectives for developing persuasive DPAs. We also discuss limitations of the study and suggest future research directions around using persuasion with DPAs.

This paper investigates whether immediate impression about websites influences only perceptions of attractiveness. The evaluative constructs of perceived usability, credibility and novelty were investigated alongside visual appeal in an experimental setting in which users evaluated 20 website screenshots in two phases. The websites were rated by the participants after viewing time of 500 ms in the first phase and with no time limit in the second. Within-website and within-rater consistency were examined in order to determine whether extremely short time period are enough to quickly form stable opinions about high level evaluative constructs besides visual appeal. We confirmed that quick and stable visual appeal judgments were made without the need of elaborate investigations and found evidence that this is also true for novelty. Usability and credibility judgments were found less consistent but nonetheless noteworthy.

In this paper, a novel methodology for selecting appropriate color scheme for a web site is presented. The methodology uses a machine learning algorithm for generating a network that relates the color model of a web site with the emotional values that are attributed to it by its users. The approach involves an empirical study to collect data, used to train the algorithm. A preliminary case study has been conducted to validate the applicability of the methodology. Description of the framework and of a set of tools that were built to support the methodology is also included.