Evaluating User Experience in a Selection Based Brain-Computer Interface Game: A Comparative Study

In human-computer interaction, it is important to offer the users correct modalities for particular tasks and situations. Unless the user has the suitable modality for a task, neither task performance nor user experience can be optimised. The aim of this study is to assess the appropriateness of using a steady-state visually evoked potential based brain-computer interface (BCI) for selection tasks in a computer game. In an experiment participants evaluated a BCI control and a comparable automatic speech recogniser (ASR) control in terms of workload, usability and engagement. The results showed that although BCI was a satisfactory modality in completing selection tasks, its use in our game was not engaging for the player. In our particular setup, ASR control appeared to be a better alternative to BCI control

Report of the Media Violence Commission

The media landscape is ever changing, with new technologies resulting in greater interactivity on smaller, graphically superior, and computationally more powerful devices. These new technologies are tremendous re- sources for learning and knowledge acquisition at a rate unparalleled in the past. Unlike traditional media (such as broadcast TV), these new technologies, in combination with an Internet connection, give children and adolescents new ways of playing games as well as access to more diverse forms of visually stimulating content than ever before (Donnerstein, 2011). Access to such content has many benefits, but it also carries risks. Youth can now download, view, play, and listen to violent material any time of day or night, often from the privacy of their own rooms, and with little supervision from their parents. With new technologies, the opportunities for viewing violent content, which was once relegated to more public spaces (such as the neighborhood, the movie theater, or the living room), have become increasingly private

Information, accountability and perceptions of public sector programme success: A conjoint experiment among bureaucrats in Africa

Motivation: Whether public sector organizations implement programmes successfully is a key concern of development scholars and practitioners across the world. While many studies purport a link between social accountability and public sector performance, this relationship has been difficult to study empirically. / Purpose: This article examines whether bureaucrats anticipate that public sector programmes with information‐sharing mechanisms, including visibility, transparency and collaboration, will be successful in terms of effectiveness and limiting corruption. / Approach and Methods: The paper uses a conjoint survey experiment administered to thousands of bureaucrats across three African countries: Ghana, Malawi and Uganda. By asking bureaucrats – those with insider knowledge of government programme operations—about two hypothetical programmes with randomly assigned characteristics, we examine whether bureaucrats associate opportunities for monitoring by citizens and civil society groups with the success of public sector programmes. / Findings: Across diverse country and organizational contexts, bureaucrats consistently attribute high probabilities of success to programmes that are visible to the public, transparent in their implementation, and open to collaboration with civil society. Moreover, the inclusion of any one of these information‐sharing mechanisms can independently increase the perceived likelihood of success. The findings hold across institutional contexts and diverse subgroups of bureaucrats surveyed. / Policy Implications: To promote success in the implementation of public sector development programmes, officials should look for ways to increase the visibility of their programmes, set requirements for frequent public updates on programme progress, and build in opportunities for outside groups to collaborate

Designing Interactions with Intention-Aware Gaze-Enabled Artificial Agents

As it becomes more common for humans to work alongside artificial agents on everyday tasks, it is increasingly important to design artificial agents that can understand and interact with their human counterparts naturally. We posit that an effective way to do this is to harness nonverbal cues used in human-human interaction. We, therefore, leverage knowledge from existing work on gaze-based intention recognition, where the awareness of gaze can provide insights into the future actions of an observed human subject. In this paper, we design and evaluate the use of a proactive intention-aware gaze-enabled artificial agent that assists a human player engaged in an online strategy game. The agent assists by recognising and communicating the intentions of a human opponent in real-time, potentially improving situation awareness. Our first study identifies the language requirements for the artificial agent to communicate the opponent’s intentions to the assisted player, using an inverted Wizard of Oz method approach. Our second study compares the experience of playing an online strategy game with and without the assistance of the agent. Specifically, we conducted a within-subjects study with 30 participants to compare their experience of playing with (1) detailed AI predictions, (2) abstract AI predictions, and (3) no AI predictions but with a live visualisation of their opponent’s gaze. Our results show that the agent can facilitate awareness of another user’s intentions without adding visual distraction to the interface; however, the cognitive workload was similar across all three conditions, suggesting that the manner in which the agent communicates its predictions requires further exploration. Overall, our work contributes to the understanding of how to support human-agent teams in a dynamic collaboration scenario. We provide a positive account of humans interacting with an intention-aware artificial agent afforded by gaze input, which presents immediate opportunities for improving interactions between the counterparts