scholarly journals ‘Alexa, I feel for you!’ Observers’ Empathetic Reactions towards a Conversational Agent

2021 ◽  
Vol 3 ◽  
Author(s):  
Astrid Carolus ◽  
Carolin Wienrich ◽  
Anna Törke ◽  
Tobias Friedel ◽  
Christian Schwietering ◽  
...  
Keyword(s):  
Emotional Reactions ◽  
Conversational Agent ◽  
Conversational Agents ◽  
Treatment Results ◽  
Media Equation ◽  
Social Actors ◽  
Trait Empathy ◽  
The Media ◽  
Single User ◽  
Computers As Social Actors

Conversational agents and smart speakers have grown in popularity offering a variety of options for use, which are available through intuitive speech operation. In contrast to the standard dyad of a single user and a device, voice-controlled operations can be observed by further attendees resulting in new, more social usage scenarios. Referring to the concept of ‘media equation’ and to research on the idea of ‘computers as social actors,’ which describes the potential of technology to trigger emotional reactions in users, this paper asks for the capacity of smart speakers to elicit empathy in observers of interactions. In a 2 × 2 online experiment, 140 participants watched a video of a man talking to an Amazon Echo either rudely or neutrally (factor 1), addressing it as ‘Alexa’ or ‘Computer’ (factor 2). Controlling for participants’ trait empathy, the rude treatment results in participants’ significantly higher ratings of empathy with the device, compared to the neutral treatment. The form of address had no significant effect. Results were independent of the participants’ gender and usage experience indicating a rather universal effect, which confirms the basic idea of the media equation. Implications for users, developers and researchers were discussed in the light of (future) omnipresent voice-based technology interaction scenarios.

A Theoretical Justification for Using Embodied Conversational Agents (ECAs) to Augment Accounting-Related Interviews

2013 ◽  
Vol 27 (2) ◽  
pp. 159-176 ◽  
Author(s):  
Matthew D. Pickard ◽  
Mary B. Burns ◽  
Kevin C. Moffitt
Keyword(s):  
Business Environment ◽  
Future Research ◽  
Embodied Conversational Agents ◽  
Conversational Agents ◽  
Accounting Firms ◽  
Self Disclosure ◽  
Social Actors ◽  
Advantages And Disadvantages ◽  
Rapport Building ◽  
Computers As Social Actors

ABSTRACT In today's increasingly complex business environment, accounting firms face additional pressures regarding cost reduction, engagement scope, and attention to quality. This paper proposes that embodied conversational agents (ECAs) are particularly well suited to automate and augment accounting interviews to save costs, streamline the interviewing process, and maintain quality. An ECA is an autonomous computer interface capable of human-like interactions such as interviews. This paper describes how an ECA can be used to augment accounting-related interviews and the advantages and disadvantages of doing so. This paper also presents the ECA Self-Disclosure Model with propositions of how self-disclosure can be influenced by an ECA through reciprocal behavior and rapport building. The model and propositions are supported by the computers-as-social-actors (CASA) paradigm (Reeves and Nass 1996). This paper concludes by discussing limitations of ECA use in the real world and by recommending how the model and propositions can be tested empirically in future research.

“It's okay, honey… shhh…” - The Media Equation and Computers-Are-Social-Actors-Hypothesis in Acute Care

2021 ◽  
Author(s):  
Anna Hohm ◽  
Oliver Happel ◽  
Jörn Hurtienne ◽  
Tobias Grundgeiger
Keyword(s):  
Acute Care ◽  
Media Equation ◽  
Social Actors ◽  
The Media

Knowledge-Based System supported by Chatbot to assist the Risk Classification Process of Patients in Hospital Emergency care (Preprint)

2021 ◽  
Author(s):  
Marciane Mueller ◽  
Rejane Frozza ◽  
Liane Mählmann Kipper ◽  
Ana Carolina Kessler
Keyword(s):  
Medical Care ◽  
Knowledge Base ◽  
Language Processing ◽  
Emergency Care ◽  
Risk Classification ◽  
Conversational Agent ◽  
Conversational Agents ◽  
Hospital Emergency ◽  
Knowledge Based System ◽  
Knowledge Based

BACKGROUND This article presents the modeling and development of a Knowledge Based System, supported by the use of a virtual conversational agent called Dóris. Using natural language processing resources, Dóris collects the clinical data of patients in care in the context of urgency and hospital emergency. OBJECTIVE The main objective is to validate the use of virtual conversational agents to properly and accurately collect the data necessary to perform the evaluation flowcharts used to classify the degree of urgency of patients and determine the priority for medical care. METHODS The agent's knowledge base was modeled using the rules provided for in the evaluation flowcharts comprised by the Manchester Triage System. It also allows the establishment of a simple, objective and complete communication, through dialogues to assess signs and symptoms that obey the criteria established by a standardized, validated and internationally recognized system. RESULTS Thus, in addition to verifying the applicability of Artificial Intelligence techniques in a complex domain of health care, a tool is presented that helps not only in the perspective of improving organizational processes, but also in improving human relationships, bringing professionals and patients closer. The system's knowledge base was modeled on the IBM Watson platform. CONCLUSIONS The results obtained from simulations carried out by the human specialist allowed us to verify that a knowledge-based system supported by a virtual conversational agent is feasible for the domain of risk classification and priority determination of medical care for patients in the context of emergency care and hospital emergency.

Think Tanks and Foreign Policy

2021 ◽  
Author(s):  
Stuti Bhatnagar
Keyword(s):  
Foreign Policy ◽  
Critical Role ◽  
Think Tanks ◽  
Think Tank ◽  
Political Issues ◽  
Social Actors ◽  
Policy Frames ◽  
Policy Actors ◽  
The Media ◽  
Intellectual Elites

The role of think tanks as policy actors has developed over time and created significant global scholarship. Widely understood as non-state policy actors, think tanks established either with or without the support of government have evolved in various political contexts with varied characteristics. They are avenues for the discussion of new policy ideas as well as used for the consolidation of existing understandings of global and national political issues. As ideational actors think tanks interact with policy frameworks at different levels, either in the framing stage or at the stage of consensus building towards certain policies. Intellectual elites at think tanks allow for the introduction of think tank ideas into the policy frames as well as the creation of public opinion towards foreign policy decisions. Think tank deliberations involve an interaction with policymakers, academic experts, business and social actors, as well as the media to disseminate ideas. Institutionally, think tanks in a wide variety of political contexts play a critical role in the making of foreign policy and bring closer attention to processes of state–society interactions in different political environments.

scholarly journals A Modular System Oriented to the Design of Versatile Knowledge Bases for Chatbots

2012 ◽  
Vol 2012 ◽  
pp. 1-10 ◽  
Author(s):  
Giovanni Pilato ◽  
Agnese Augello ◽  
Salvatore Gaglio
Keyword(s):  
Corpus Callosum ◽  
Knowledge Representation ◽  
User Behavior ◽  
Knowledge Bases ◽  
Modular System ◽  
Conversational Agent ◽  
Proof Of Concept ◽  
Conversational Agents ◽  
Specific Domain ◽  
Representation Techniques

The paper illustrates a system that implements a framework, which is oriented to the development of a modular knowledge base for a conversational agent. This solution improves the flexibility of intelligent conversational agents in managing conversations. The modularity of the system grants a concurrent and synergic use of different knowledge representation techniques. According to this choice, it is possible to use the most adequate methodology for managing a conversation for a specific domain, taking into account particular features of the dialogue or the user behavior. We illustrate the implementation of a proof-of-concept prototype: a set of modules exploiting different knowledge representation methodologies and capable of managing different conversation features has been developed. Each module is automatically triggered through a component, named corpus callosum, that selects in real time the most adequate chatbot knowledge module to activate.

A Procedure to Create a Pedagogic Conversational Agent in Secondary Physics and Chemistry Education

2013 ◽  
Vol 9 (4) ◽  
pp. 94-112 ◽  
Author(s):  
Diana Pérez-Marín ◽  
Antonio Boza
Keyword(s):  
Natural Language ◽  
Chemistry Education ◽  
Teaching Method ◽  
Computer Applications ◽  
Conversational Agent ◽  
Conversational Agents ◽  
Innovative Teaching ◽  
Language Support ◽  
Teachers And Students ◽  
Innovative Teaching Method

Pedagogic Conversational Agents are computer applications that can interact with students in natural language. They have been used with satisfactory results on the instruction of several domains. The authors believe that they could also be useful for the instruction of Secondary Physics and Chemistry Education. Therefore, in this paper, the authors present a procedure to create an agent for that domain. First, teachers have to introduce the exercises with their correct answers. Secondly, students will be presented the exercises, and if the students know the answer, and if it is correct, more difficult exercises will be presented. Otherwise, step-by-step natural language support will be provided to guide the student towards the solution. It is the authors’ hypothesis that this innovative teaching method will be satisfactory and useful for teachers and students, and that by following the procedure more computer programmers can be encouraged to develop agents for other domains to be used by teachers and students at class.

scholarly journals Changes to the Psychiatric Chatbot Landscape: A Systematic Review of Conversational Agents in Serious Mental Illness: Changements du paysage psychiatrique des chatbots: une revue systématique des agents conversationnels dans la maladie mentale sérieuse

2020 ◽  
pp. 070674372096642
Author(s):  
Aditya Nrusimha Vaidyam ◽  
Danny Linggonegoro ◽  
John Torous
Keyword(s):  
Mental Health ◽  
Systematic Review ◽  
Bipolar Disorder ◽  
Mental Illness ◽  
Serious Mental Illness ◽  
Therapeutic Efficacy ◽  
Digital Tools ◽  
Conversational Agent ◽  
Conversational Agents ◽  
Diagnostic Quality

Objective: The need for digital tools in mental health is clear, with insufficient access to mental health services. Conversational agents, also known as chatbots or voice assistants, are digital tools capable of holding natural language conversations. Since our last review in 2018, many new conversational agents and research have emerged, and we aimed to reassess the conversational agent landscape in this updated systematic review. Methods: A systematic literature search was conducted in January 2020 using the PubMed, Embase, PsychINFO, and Cochrane databases. Studies included were those that involved a conversational agent assessing serious mental illness: major depressive disorder, schizophrenia spectrum disorders, bipolar disorder, or anxiety disorder. Results: Of the 247 references identified from selected databases, 7 studies met inclusion criteria. Overall, there were generally positive experiences with conversational agents in regard to diagnostic quality, therapeutic efficacy, or acceptability. There continues to be, however, a lack of standard measures that allow ease of comparison of studies in this space. There were several populations that lacked representation such as the pediatric population and those with schizophrenia or bipolar disorder. While comparing 2018 to 2020 research offers useful insight into changes and growth, the high degree of heterogeneity between all studies in this space makes direct comparison challenging. Conclusions: This review revealed few but generally positive outcomes regarding conversational agents’ diagnostic quality, therapeutic efficacy, and acceptability, which may augment mental health care. Despite this increase in research activity, there continues to be a lack of standard measures for evaluating conversational agents as well as several neglected populations. We recommend that the standardization of conversational agent studies should include patient adherence and engagement, therapeutic efficacy, and clinician perspectives.

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