Zoekresultaten

Four categories for meaningful discussion of immersion in video games.

The term ‘immersion’ is used frequently by professional video game developers (in both the entertainment and serious/applied industries), academics, journalists, and players. However, this word can refer to a range of different modes of engagement for players and standardisation would improve discussion of the topic. This paper suggests and explains four categories: 1. 'Systems immersion' can be used to describe when players are deeply engaged with the mechanics, challenges, and rules of a game, and is similar to a state of ‘flow’. 2. 'Spatial immersion' is the sense of a player being present in, or transported to, the virtual world, and is linked to the concept of embodiment. 3. 'Empathic/social immersion' describes the connection that a player may develop towards the characters (AI or human) and the social context of a game.4. 'Narrative/sequential immersion' can be used to describe a player’s compulsion to see how a sequence of events continues, typically in a narrative, but this is related to any progression, such as exploring new spaces or evolving gameplay mechanics.

Meaningful leisure and tourism experiences as catalysts for wellbeing.

To use or not to use

Technology in general, and assistive technology in particular, is considered to be a promising opportunity to address the challenges of an aging population. Nevertheless, in health care, technology is not as widely used as could be expected. In this chapter, an overview is given of theories and models that help to understand this phenomenon. First, the design of (assistive) technologies will be addressed and the importance of human-centered design in the development of new assistive devices will be discussed. Also theories and models are addressed about technology acceptance in general. Specific attention will be given to technology acceptance in healthcare professionals, and the implementation of technology within healthcare organizations. The chapter will be based on the state of the art of scientific literature and will be illustrated with examples from our research in daily practice considering the different perspectives of involved stakeholders.

Identifying XAI User Needs

One aspect of a responsible application of Artificial Intelligence (AI) is ensuring that the operation and outputs of an AI system are understandable for non-technical users, who need to consider its recommendations in their decision making. The importance of explainable AI (XAI) is widely acknowledged; however, its practical implementation is not straightforward. In particular, it is still unclear what the requirements are of non-technical users from explanations, i.e. what makes an explanation meaningful. In this paper, we synthesize insights on meaningful explanations from a literature study and two use cases in the financial sector. We identified 30 components of meaningfulness in XAI literature. In addition, we report three themes associated with explanation needs that were central to the users in our use cases, but are not prominently described in literature: actionability, coherent narratives and context. Our results highlight the importance of narrowing the gap between theoretical and applied responsible AI.

Mastering Meaningful Customer Connections

Within large service organizations there are currently two trends visible. These trends seem to be diametrically opposed. On the one hand organizations face increasing price pressure and thus a pressure to cut costs. One of the consequences of this trend is that organizations are increasingly encouraging customers to make more use of digital communication channels. At the same time, companies find it important to know their customers in order to respond adequately to their needs. To do this, organizations must have a certain degree of personal involvement to their customers and they must have regular personal contact. It is assumed that both trends – digitisation and personalisation – will have a strong impact on customer experience and (perhaps) on the relational models customers use. If it is true that relational models - so the way in which people perceive and assess a relationship - play a role in the perception of the customer, it is also interesting to know if it is possible to influence these relational models. During the last fifty years much research has been done into the possibilities to influence customers by using subliminal priming techniques. In these techniques thoughts and feelings are unconsciously activated by showing people certain words or images (eg Bargh, Chen & Burrows, 1996; Dijksterhuis, 2005). In recent years a number of experiments were performed in which customers were unconsciously primed at some type of relationship (eg Aggarwal, 2004; McGraw & Tetlock, 2005; Tuk, Verlegh, Smidts & Wigboldus, 2009). These experiments showed that it is possible to activate a certain type of relationship. The experiments however the researchers used scenario’s based on an interpersonal relationship, and often to a fictitious relationship. The question is whether priming techniques also work for an already existing and more complex relationship between an organization and its customers. From 2010-2013 we conducted research for six large service providers in banking, insurance, utilities and social welfare to discover what the customer experience of these organisations, what role relational models played in customer experience and whether it was possible to influence these relational models. The research project has provided answers to the following questions: - Which relational models are used by customers and what is the influence of these models on customer experience? - What is the influence of digitisation in customer communication on relational models and customer experience? - What is the influence of personalisation in customer communication on relational models and customer experience? And finally, - Is it possible to influence relational models (and customer experience) by using specific words and images that are associated with relational models (relational framing)?

Employers have a Duty of Beneficence to Design for Meaningful Work

Artificial intelligence-driven technology increasingly shapes work practices and, accordingly, employees’ opportunities for meaningful work (MW). In our paper, we identify five dimensions of MW: pursuing a purpose, social relationships, exercising skills and self-development, autonomy, self-esteem and recognition. Because MW is an important good, lacking opportunities for MW is a serious disadvantage. Therefore, we need to know to what extent employers have a duty to provide this good to their employees. We hold that employers have a duty of beneficence to design for opportunities for MW when implementing AI-technology in the workplace. We argue that this duty of beneficence is supported by the three major ethical theories, namely, Kantian ethics, consequentialism, and virtue ethics. We defend this duty against two objections, including the view that it is incompatible with the shareholder theory of the firm. We then employ the five dimensions of MW as our analytical lens to investigate how AI-based technological innovation in logistic warehouses has an impact, both positively and negatively, on MW, and illustrate that design for MW is feasible. We further support this practical feasibility with the help of insights from organizational psychology. We end by discussing how AI-based technology has an impact both on meaningful work (often seen as an aspirational goal) and decent work (generally seen as a matter of justice). Accordingly, ethical reflection on meaningful and decent work should become more integrated to do justice to how AI-technology inevitably shapes both simultaneously.