Justification, Conversation, and Folk Psychology

The aim of this paper is to offer a version of the so-called conversational hypothesis of the ontogenetic connection between language and mindreading (Harris 1996, 2005; Van Cleave and Gauker 2010; Hughes et al. 2006). After arguing against a particular way of understanding the hypothesis (the communicative view), I will start from the justificatory view in philosophy of social cognition (Andrews 2012; Hutto 2004; Zawidzki 2013) to make the case for the idea that the primary function of belief and desire attributions is to justify and normalize deviant patterns of behaviour. Following this framework, I elaborate upon the idea that development of folk psychological skills requires the subjects to engage in conversationally mediated joint and cooperative activities in order to acquire the conceptual capacity of ascribing propositional attitudes. After presenting the general version of the hypothesis, I present several testable sub-hypotheses and some psychological studies that give empirical plausibility to the hypothesis

Collaborating on Referring Expressions

This paper presents a computational model of how conversational participants collaborate in order to make a referring action successful. The model is based on the view of language as goal-directed behavior. We propose that the content of a referring expression can be accounted for by the planning paradigm. Not only does this approach allow the processes of building referring expressions and identifying their referents to be captured by plan construction and plan inference, it also allows us to account for how participants clarify a referring expression by using meta-actions that reason about and manipulate the plan derivation that corresponds to the referring expression. To account for how clarification goals arise and how inferred clarification plans affect the agent, we propose that the agents are in a certain state of mind, and that this state includes an intention to achieve the goal of referring and a plan that the agents are currently considering. It is this mental state that sanctions the adoption of goals and the acceptance of inferred plans, and so acts as a link between understanding and generation.Comment: 32 pages, 2 figures, to appear in Computation Linguistics 21-

CoachAI: A Conversational Agent Assisted Health Coaching Platform

Poor lifestyle represents a health risk factor and is the leading cause of morbidity and chronic conditions. The impact of poor lifestyle can be significantly altered by individual behavior change. Although the current shift in healthcare towards a long lasting modifiable behavior, however, with increasing caregiver workload and individuals' continuous needs of care, there is a need to ease caregiver's work while ensuring continuous interaction with users. This paper describes the design and validation of CoachAI, a conversational agent assisted health coaching system to support health intervention delivery to individuals and groups. CoachAI instantiates a text based healthcare chatbot system that bridges the remote human coach and the users. This research provides three main contributions to the preventive healthcare and healthy lifestyle promotion: (1) it presents the conversational agent to aid the caregiver; (2) it aims to decrease caregiver's workload and enhance care given to users, by handling (automating) repetitive caregiver tasks; and (3) it presents a domain independent mobile health conversational agent for health intervention delivery. We will discuss our approach and analyze the results of a one month validation study on physical activity, healthy diet and stress management