Tourism and Community Perception: Quest of Sustainability from Happiness Paradigm

Change is normally phenotypic and influenced by external environment however transformation is genotypic and irreversible which mostly comes from within. Social change and transformation might also be triggered by external stimulus that may be intentional or accidental. Tourism has emerged globally as one of the powerful external but intentional agents of modern society for socio-economic transformation. Namche Bazar, the gateway to Mt. Everest, experienced tremendous socio-economic transformation (genotypic) due to tourism otherwise it would simply be a seasonal resting place for Sherpa shepherds and nomads. The dichotomy of discourses on tourism lies on perspectives: tourism as a symbol of modern society or postmodernity versus tourism as a vehicle of imperialism. The former view depicts tourism as an agent of economic prosperity whereas the later claims that tourism consumes and despoils destinations’ image and essence. The imperialistic discourse on tourism is entirely built on negative hypothesis. In tourism, phenotypic impact is rather superficial and can be restored if perceived negatively unlike genotypic. Amid these positive and negative propositions, a third paradigm emerged with sustainability variant that hooked up the two juxtaposed hypotheses as an alternative model of mass tourism. It portrayed tourism as a double-edged dagger that insists on efficient and effective manipulation of tourism for positive implications. The ‘sustainable tourism’ – a buzzword among tourism academia - stands in favor of planned, managed, controlled and responsible tourism. However, the crux of sustainable tourism lies in the quantification and measurement of sustainability. A sustainability premise of a stakeholder at the destination might be unsustainable for the other as like of economists and environmentalists for example. The incongruity perspectives have troubled the tourism academia to quantify, measure and analyze the indicators of sustainable tourism from unanimous parameters. This study is, therefore, an attempt to analyze the sustainability of a tourism destination via happiness (hedonic as well as eudaemonic) parameters of the community people, one of the main stakeholders in the destination and yet do not directly thrive on tourism business. The paper is directed by a thematic proposition ‘the more the happiness level of stakeholders, the better will be the sustainability situation of the destination’.

Group Agency and Artificial Intelligence

The aim of this exploratory paper is to review an under-appreciated parallel between group agency and artificial intelligence. As both phenomena involve non-human goal-directed agents that can make a difference to the social world, they raise some similar moral and regulatory challenges, which require us to rethink some of our anthropocentric moral assumptions. Are humans always responsible for those entities’ actions, or could the entities bear responsibility themselves? Could the entities engage in normative reasoning? Could they even have rights and a moral status? I will tentatively defend the (increasingly widely held) view that, under certain conditions, artificial intelligent systems, like corporate entities, might qualify as responsible moral agents and as holders of limited rights and legal personhood. I will further suggest that regulators should permit the use of autonomous artificial systems in high-stakes settings only if they are engineered to function as moral (not just intentional) agents and/or there is some liability-transfer arrangement in place. I will finally raise the possibility that if artificial systems ever became phenomenally conscious, there might be a case for extending a stronger moral status to them, but argue that, as of now, this remains very hypothetical.

Social Interaction in Infancy

The present chapter reviews the early development of various forms of social cognition guiding social interaction in infancy. There is wide agreement that very early in the first year of life infants reveal remarkable sensitivity to social information, and engage in remarkable forms of contingent social interaction. It is equally undisputed that towards the end of the first year of life infants begin to operate with basic forms of folk psychology, understanding others and themselves as intentional agents who perceive their surroundings and act intentionally, and that from their second year on infants engage in shared intentionality with others. What is controversial, however, is whether infants already operate with fully fledged meta-representational Theory of Mind, or whether this capacity develops in more protracted ways, depending on language acquisition and cultural experience. This chapter reviews theoretical debates and empirical findings related to this controversy in detail.

I Am Looking for Your Mind: Pupil Dilation Predicts Individual Differences in Sensitivity to Hints of Human-Likeness in Robot Behavior

The presence of artificial agents in our everyday lives is continuously increasing. Hence, the question of how human social cognition mechanisms are activated in interactions with artificial agents, such as humanoid robots, is frequently being asked. One interesting question is whether humans perceive humanoid robots as mere artifacts (interpreting their behavior with reference to their function, thereby adopting the design stance) or as intentional agents (interpreting their behavior with reference to mental states, thereby adopting the intentional stance). Due to their humanlike appearance, humanoid robots might be capable of evoking the intentional stance. On the other hand, the knowledge that humanoid robots are only artifacts should call for adopting the design stance. Thus, observing a humanoid robot might evoke a cognitive conflict between the natural tendency of adopting the intentional stance and the knowledge about the actual nature of robots, which should elicit the design stance. In the present study, we investigated the cognitive conflict hypothesis by measuring participants’ pupil dilation during the completion of the InStance Test. Prior to each pupillary recording, participants were instructed to observe the humanoid robot iCub behaving in two different ways (either machine-like or humanlike behavior). Results showed that pupil dilation and response time patterns were predictive of individual biases in the adoption of the intentional or design stance in the IST. These results may suggest individual differences in mental effort and cognitive flexibility in reading and interpreting the behavior of an artificial agent.

The human brain reveals resting state activity patterns that are predictive of biases in attitudes towards robots.

The increasing presence of robots in society necessitates a deeper understanding into what attitudes people have toward robots. People may treat robots as mechanistic artifacts or may consider them to be intentional agents. This might result in explaining robots’ behavior as stemming from operations of the mind (intentional interpretation) or as a result of mechanistic design (mechanistic interpretation). Here, we examined whether individual attitudes toward robots can be differentiated on the basis of default neural activity pattern during resting state, measured with electroencephalogram (EEG). Participants observed scenarios in which a humanoid robot was depicted performing various actions embedded in daily contexts. Before they were introduced to the task, we measured their resting state EEG activity. We found that resting state EEG beta activity differentiated people who were later inclined toward interpreting robot behaviors as either mechanistic or intentional. This pattern is similar to the pattern of activity in the default mode network, which was previously demonstrated to have a social role. In addition, gamma activity observed when participants were making decisions about a robot’s behavior indicates a relationship between theory of mind and said attitudes. Thus, we provide evidence that individual biases toward treating robots as either intentional agents or mechanistic artifacts can be detected at the neural level, already in a resting state EEG signal.

I am looking for your mind. Pupil dilation predicts individual differences in sensitivity to hints of human-likeness in robot behavior

The presence of artificial agents in our everyday lives is continuously increasing. Hence, the question of how human social cognition mechanisms are activated when we interact with artificial agents, such as humanoid robots, has been asked. One interesting question is whether humans perceive humanoid robots as mere artefacts (interpreting their behavior with reference to their function, thereby adopting the design stance) or as intentional agents (interpreting their behavior with reference to mental states, thereby adopting the intentional stance). Due to their human-like appearance, humanoid robots might be capable of evoking the intentional stance. On the other hand, the knowledge that humanoid robots are only artefacts should call for adopting the design stance. Thus, observing a humanoid robot might evoke a cognitive conflict between the natural tendency of adopting the intentional stance and the knowledge about the actual nature of robots, which should elicit the design stance. In the present study, we investigated the cognitive conflict hypothesis measuring participants’ pupil dilation during the completion of InStance Test. Prior to each pupillary recording, participants were instructed to observe the humanoid robot iCub behaving in two different ways (either machine-like or human-like behavior). Results showed that pupil dilation and response time patterns were predictive of individual biases in the adoption of the intentional or design stance in the IST. These results may suggest individual differences in mental effort and cognitive flexibility in reading and interpreting the behavior of an artificial agent.

Repositioning luxury fashion brands as intentional agents: the roles of consumer envy and admiration

PurposeBuilding on the Brands as Intentional Agents Framework (BIAF), the aim of this study is to demonstrate the effectiveness of social media marketing (SMM) as a tool to communicate luxury fashion brands' good intentions toward the general public.Design/methodology/approachA sample of 488 US female consumers was used to test a conceptual model delineating the sequential linkages from luxury fashion brands' intentions to brand emotions (i.e. envy vs admiration) and to consumer–brand relationships (i.e. emotional brand attachment and brand forgiveness). Structural equation modeling (SEM) was performed to test the measurement and structural models.FindingsThe results indicated that luxury fashion brands' “populist” intentions had a positive impact on consumer admiration. Both consumer envy and admiration had positive effects on emotional brand attachment and brand forgiveness. However, admiration had a stronger effect than envy on these relational consumer responses.Originality/valueThis study identified that luxury fashion brands, frequently stereotyped as exclusive, can become brands admired by mass-market consumers by expressing warmth on social media. Drawing on social psychological perspectives and the BIAF, this study adds to the literature on luxury brands' social media communication by demonstrating the effectiveness of brand warmth to induce consumers' strong relational outcomes.

Animacy and the prediction of behaviour

To survive, all animals need to predict what other agents are going to do next. The first step is to detect that an object is an agent and, if so, how sophisticated it is. To this end, visual cues are especially important: the form of the agent and the nature of its movements. Once identified, the movements of an agent, however sophisticated, can be anticipated in the short term on the basis of purely physical constraints, but, in the longer term, it is useful to take account of the agent’s goals and intentions. Goal directed agents are marked by the rationality of their movements, reaching their goals by the shortest or least effortful path. Observing goal directed behaviour activates the brain’s action observation/mirror neuron network. The observer’s own action generating mechanism has an important role in predicting future movements of goal directed agents.Intentions have a critical role in determining actions when agents interact with other agents. In such interactions, movements can become communicative rather than directed to immediate goals. Also, each agent can be trying to predict the behaviour of the other, leading to a recursive arms race. It is difficult to infer intentional behaviour from movement kinematics and interpretation is much more dependent upon prior beliefs about the agent. When people believe that they are interacting with an intentional agent, the brain’s mentalising system is activated as the person tries to assess the degree of sophistication of the agent. Several biologically-constrained computational models of action recognition are available, but equivalent models for understanding intentional agents remain to be developed.