To boldly go… : designing an agent-based intercultural training tool

People from all over the world must live and work together in today’s society. Such integration is not always a smooth process, and interactions with people from other cultures may lead to misunderstandings or even outright conflicts. In the last few years, researchers and practitioners have been working on creating digital tools that can be used to mediate these misunderstandings and conflicts. These tools typically involve interactions with so-called intelligent agents, i.e. virtual characters that are able to take decisions autonomously, that behave as if they are from another culture. The aim of these interactions is to make potential trainees experience how misunderstandings can shape interactions with and perceptions of people from other cultures. In this work, we take the first steps in the design of a digital culture-general training tool to help young adults deal with misunderstandings or conflicts due to differences in culture, through interactions with intelligent agents. We have posed the following design research questions and found the following answers: Which concepts are required to describe the design of a digital culture-general training tool involving agents that show culturally varying behaviour? The answer to this question can be found in the glossary, which presents the key concepts that have been used in this work to create agents that show culturally varying behaviour and to create scenarios that incorporate these agents to increase the intercultural competence of trainees. Can we use theories of culture to create scripted scenarios in which virtual characters behave appropriately for a given culture? To answer this question we designed scripted scenarios in which virtual characters show culturally varying behaviour based on a theory of culture. To ensure that the behaviours of these virtual characters were representative of real-life cultural differences, we conducted an evaluation with people from a wide range of cultures. The results show that the dimensions of culture can be used to generate culturally varying behaviour in agents, but that extensive (pre)testing is required to ensure that the underlying intention of the characters’ behaviour aligns with the users’ interpretation of that behaviour. Can we identify requirements for sociocultural agents that can help them to make sense of their social world? To answer this question we focused on describing important concepts of social interactions based on theories from sociology and psychology. These concepts are incorporated into a conceptual model for socio-cultural agents that can be used to describe their social world. The model differentiates between three levels of analysis: the interaction, the group, and the society. These levels range from being more specific, and thus more visible, to more abstract, and thus less visible, and help us to understand how each level affects interpretation and behaviour. Can we create intelligent agents that can vary their behaviour depending on the culture to be simulated? To answer this question we described the creation of intelligent agents that show culturally varying behaviour. We use an existing model to create believable social interactions, in which agents attribute, claim, and confer social importance in their interactions with other agents and users. Social importance is a way to measure the importance of a certain individual in the eyes of others. The strength of attribution, claims, and conferrals was varied using cultural modifiers. The generated behaviour of the agents was then evaluated to ensure that the intelligent agents showed behaviour representative of a given culture. The results suggest that it is possible to create intelligent agents that can act out appropriate culturally varying behaviour for a given culture. Can we create critical incidents, involving intelligent agents that show appropriate behaviour for given cultures, through which potential trainees become more sensitive to and knowledgeable about differences across cultures? To answer this question we focused on applying different methods of intercultural training in the design of a digital culture-general training tool. These methods were incorporated into critical incidents, in which users can interact with intelligent agents. To ensure that the critical incidents led to an attribution of perceived differences in behaviour to specific differences in culture and to (potential) trainees becoming less judgemental of inappropriate behaviours by people from different cultures, the tool was evaluated by two groups of students. The results suggest that it is possible to create agent-based critical incidents to make potential trainees more knowledgeable about differences across cultures. Contributions The findings to our design research questions represent a set of important contributions to the field. First, we have identified and structured important concepts to better understand the design and implementation of socio-cultural agents and the design of critical incidents that involve these agents for intercultural training. Second, we have described and used models that help to define the simulated world of the agents and help them to navigate through that world. Third, we have attempted to systematize the process of creating scenarios involving agents that show culturally varying behaviour through a set of guidelines that need to be met to ensure that the behaviour of socio-cultural characters is properly evaluated. Fourth, besides conceptual elements, we have also created practical implementations that can freely be used and modified by others. In our work, we have only taken the first steps in designing a digital culture-general training tool. Additional work on the generalization and validation of the critical incidents and the behaviours of the agents is still required; however, we believe that our results show our approach to be viable. We believe that future work will have to focus on three fields: understanding how trainees can be emotionally engaged in the scenarios, systematizing the process of using model-driven approaches to generate socio-cultural behaviour, and using the design outputs in different contexts and with different people from different cultures.</p

Who’s friends, who’s boss? Affiliation and hierarchy in agent societies

The everyday life of people working in organizations requires con-tinuous coordination. In fact, coordination is what organizations are for. Yet people do not stick to what the organization prescribes for them to do. Human coordination is rife with issues of group affiliation, power, and leadership, and associated emotions. The fields of organizational behaviour and management reflect this. Modellers of organizational behaviour need to take these areas on board. This goes beyond formal organization. While sophisticated logics are used as well as intricate models of organizations, the social, volitional nature of the humans in them is hardly modelled, thus limiting the practical usability of these models. The article reviews the literature on group affiliation and hierar-chy in agent-based models. It gives pointers as to which developments seem promising for advancing MAS and social simulation. It discusses the potential of complementary roles in agent-based models for formal organisation and hu-man social nature. The MAIA meta-model for social simulation [7] serves as an example

A Complex Systems Approach to the Exploration of Environmental Ideologies

Understanding that the current socio-ecological challenges create a need for large scale technological, institutional and ideological changes, this research explores environmental ideologies. Starting with a review of literature into ideologies, emerging research into ideologies from complex systems theorists, and studies into environmental ideologies to illuminate ways to investigate environmental ideologies as complex representational adaptive systems. Environmental ideologies in Canada are used to target the study through a review of environmental literature, questionnaires of environmental students and experts, and discourse analysis of annual reports and about sections from major environmental organizations. These results were used to create cognitive affective maps and state space descriptions for seven environmental ideologies: market liberalism, environmental conservatism, institutionalism, bioenvironmentalism social greens, religious environmentalism, and ecologism. Despite some concerns around sampling for the questionnaires, these results highlighted key aspects of environmentalism as a major ideology, three categories of sub-ideologies and the ways that the above ideologies interact at the periphery. Finally, it is argued that the public communication from Canada’s large environmental organizations reflect an institutionalist environmentalism

Emotion-Aware and Human-Like Autonomous Agents

In human-computer interaction (HCI), one of the technological goals is to build human-like artificial agents that can think, decide and behave like humans during the interaction. A prime example is a dialogue system, where the agent should converse fluently and coherently with a user and connect with them emotionally. Humanness and emotion-awareness of interactive artificial agents have been shown to improve user experience and help attain application-specific goals more quickly. However, achieving human-likeness in HCI systems is contingent on addressing several philosophical and scientific challenges. In this thesis, I address two such challenges: replicating the human ability to 1) correctly perceive and adopt emotions, and 2) communicate effectively through language. Several research studies in neuroscience, economics, psychology and sociology show that both language and emotional reasoning are essential to the human cognitive deliberation process. These studies establish that any human-like AI should necessarily be equipped with adequate emotional and linguistic cognizance. To this end, I explore the following research directions. - I study how agents can reason emotionally in various human-interactive settings for decision-making. I use Bayesian Affect Control Theory, a probabilistic model of human-human affective interactions, to build a decision-theoretic reasoning algorithm about affect. This approach is validated on several applications: two-person social dilemma games, an assistive healthcare device, and robot navigation. - I develop several techniques to understand and generate emotions/affect in language. The proposed methods include affect-based feature augmentation of neural conversational models, training regularization using affective objectives, and affectively diverse sequential inference. - I devise an active learning technique that elicits user feedback during a conversation. This enables the agent to learn in real time, and to produce natural and coherent language during the interaction. - I explore incremental domain adaptation in language classification and generation models. The proposed method seeks to replicate the human ability to continually learn from new environments without forgetting old experiences

Creating a World for Socio-Cultural Agents

Creating agents that are capable of emulating similar socio-cultural dynamics to those found in human interaction remains as one of the hardest challenges of artificial intelligence. This problem becomes particularly important when considering embodied agents that are meant to interact with humans in a believable and empathic manner. In this article, we introduce a conceptual model for socio-cultural agents, and, based on this model, we present a set of requirements for these agents to be capable of showing appropriate socio-cultural behaviour. Our model differentiates between three levels of instantiation: the interaction level, consisting of elements that may change depending on the people involved, the group level, consisting of elements that may change depending on the group affiliation of the people involved, and the society level, consisting of elements that may change depending on the cultural background of those involved. As such, we are able to have culture alter agents’ social relationships rather than directly determining actions, allowing for virtual agents to act more appropriately in any social or cultural context

Creating a world for socio-cultural agents

Creating agents that are capable of emulating similar socio-cultural dynamics to those found in human interaction remains as one of the hardest challenges of artificial intelligence. This problem becomes particularly important when considering embodied agents that are meant to interact with humans in a believable and empathic manner. In this article, we introduce a conceptual model for socio-cultural agents, and, based on this model, we present a set of requirements for these agents to be capable of showing appropriate socio-cultural behaviour. Our model differentiates between three levels of instantiation: the interaction level, consisting of elements that may change depending on the people involved, the group level, consisting of elements that may change depending on the group affiliation of the people involved, and the society level, consisting of elements that may change depending on the cultural background of those involved. As such, we are able to have culture alter agents’ social relationships rather than directly determining actions, allowing for virtual agents to act more appropriately in any social or cultural context