Joy O. Egede, Dominic Price, D. Krishnan, S. Jaiswal, Natasha Elliot, R. Morriss, Maria Jose Galvez Trigo, N. Nixon, P. Liddle, C. Greenhalgh, M. Valstar
Virtual human technologies are now being widely explored as therapy tools for mental health disorders including depression and anxiety. These technologies leverage the ability of the virtual agents to engage in naturalistic social interactions with a user to elicit behavioural expressions which are indicative of depression and anxiety. Research efforts have focused on optimising the human-like expressive capabilities of the virtual human, but less attention has been given to investigating the effect of virtual human mediation on the expressivity of the user. In addition, it is still not clear what an optimal task is or what task characteristics are likely to sustain long term user engagement. To this end, this paper describes the design and evaluation of virtual human-mediated tasks in a user study of 56 participants. Half the participants complete tasks guided by a virtual human, while the other half are guided by text on screen. Self-reported PHQ9 scores, biosignals and participants' ratings of tasks are collected. Findings show that virtual-human mediation influences behavioural expressiveness and this observation differs for different depression severity levels. It further shows that virtual human mediation improves users' disposition towards tasks.
{"title":"Design and Evaluation of Virtual Human Mediated Tasks for Assessment of Depression and Anxiety","authors":"Joy O. Egede, Dominic Price, D. Krishnan, S. Jaiswal, Natasha Elliot, R. Morriss, Maria Jose Galvez Trigo, N. Nixon, P. Liddle, C. Greenhalgh, M. Valstar","doi":"10.1145/3472306.3478361","DOIUrl":"https://doi.org/10.1145/3472306.3478361","url":null,"abstract":"Virtual human technologies are now being widely explored as therapy tools for mental health disorders including depression and anxiety. These technologies leverage the ability of the virtual agents to engage in naturalistic social interactions with a user to elicit behavioural expressions which are indicative of depression and anxiety. Research efforts have focused on optimising the human-like expressive capabilities of the virtual human, but less attention has been given to investigating the effect of virtual human mediation on the expressivity of the user. In addition, it is still not clear what an optimal task is or what task characteristics are likely to sustain long term user engagement. To this end, this paper describes the design and evaluation of virtual human-mediated tasks in a user study of 56 participants. Half the participants complete tasks guided by a virtual human, while the other half are guided by text on screen. Self-reported PHQ9 scores, biosignals and participants' ratings of tasks are collected. Findings show that virtual-human mediation influences behavioural expressiveness and this observation differs for different depression severity levels. It further shows that virtual human mediation improves users' disposition towards tasks.","PeriodicalId":148152,"journal":{"name":"Proceedings of the 21st ACM International Conference on Intelligent Virtual Agents","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124984869","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jacky Casas, Timo Spring, Karl Daher, E. Mugellini, Omar Abou Khaled, P. Cudré-Mauroux
Conversational agents are getting increasingly popular and find applications in health and customer services. Conversations in these fields are often emotionally charged. It is, therefore, necessary to handle the conversation with some degree of empathy to be effective. In this work, we leverage advances in the field of natural language processing to create a dialogue system that can convincingly generate empathic responses to text-based messages. To improve the system's ability to converse with empathy, we train the language model on empathic conversations and inject additional emotional information in the response generation. We propose two chatbots: a benchmark bot and an empathic bot. Additionally, we implement an emotion classifier that allows us to predict the emotional state of text-based messages. We evaluate both chatbots in quantitative studies and compare them with human responses in qualitative studies involving human judges. Our evaluation shows that our empathic chatbot outperforms the benchmark bot and even the human-generated responses in terms of perceived empathy. Additionally, we achieve state-of-the-art results in terms of response quality using transformer-based language models. Finally we report that we can double the initial performance of the emotion classifier using undersampling techniques, yielding a final F1-score of 0.81 in six basic emotions.
{"title":"Enhancing Conversational Agents with Empathic Abilities","authors":"Jacky Casas, Timo Spring, Karl Daher, E. Mugellini, Omar Abou Khaled, P. Cudré-Mauroux","doi":"10.1145/3472306.3478344","DOIUrl":"https://doi.org/10.1145/3472306.3478344","url":null,"abstract":"Conversational agents are getting increasingly popular and find applications in health and customer services. Conversations in these fields are often emotionally charged. It is, therefore, necessary to handle the conversation with some degree of empathy to be effective. In this work, we leverage advances in the field of natural language processing to create a dialogue system that can convincingly generate empathic responses to text-based messages. To improve the system's ability to converse with empathy, we train the language model on empathic conversations and inject additional emotional information in the response generation. We propose two chatbots: a benchmark bot and an empathic bot. Additionally, we implement an emotion classifier that allows us to predict the emotional state of text-based messages. We evaluate both chatbots in quantitative studies and compare them with human responses in qualitative studies involving human judges. Our evaluation shows that our empathic chatbot outperforms the benchmark bot and even the human-generated responses in terms of perceived empathy. Additionally, we achieve state-of-the-art results in terms of response quality using transformer-based language models. Finally we report that we can double the initial performance of the emotion classifier using undersampling techniques, yielding a final F1-score of 0.81 in six basic emotions.","PeriodicalId":148152,"journal":{"name":"Proceedings of the 21st ACM International Conference on Intelligent Virtual Agents","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128640673","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Joy O. Egede, Maria Jose Galvez Trigo, Adrian Hazzard, Martin Porcheron, Edgar Bodiaj, J. Fischer, C. Greenhalgh, M. Valstar
Access to healthcare advice is crucial to promote healthy societies. Many factors shape how access might be constrained, such as economic status, education or, as the COVID-19 pandemic has shown, remote consultations with health practitioners. Our work focuses on providing pre/post-natal advice to maternal women. A salient factor of our work concerns the design and deployment of embodied conversation agents (ECAs) which can sense the (health) literacy of users and adapt to scaffold user engagement in this setting. We present an account of a Wizard of Oz user study of 'ALTCAI', an ECA with three modes of interaction (i.e., adaptive speech and text, adaptive ECA, and non-adaptive ECA). We compare reported engagement with these modes from 44 maternal women who have differing levels of literacy. The study shows that a combination of embodiment and adaptivity scaffolds reported engagement, but matters of health-literacy and language introduce nuanced considerations for the design of ECAs.
{"title":"Designing an Adaptive Embodied Conversational Agent for Health Literacy: a User Study","authors":"Joy O. Egede, Maria Jose Galvez Trigo, Adrian Hazzard, Martin Porcheron, Edgar Bodiaj, J. Fischer, C. Greenhalgh, M. Valstar","doi":"10.1145/3472306.3478350","DOIUrl":"https://doi.org/10.1145/3472306.3478350","url":null,"abstract":"Access to healthcare advice is crucial to promote healthy societies. Many factors shape how access might be constrained, such as economic status, education or, as the COVID-19 pandemic has shown, remote consultations with health practitioners. Our work focuses on providing pre/post-natal advice to maternal women. A salient factor of our work concerns the design and deployment of embodied conversation agents (ECAs) which can sense the (health) literacy of users and adapt to scaffold user engagement in this setting. We present an account of a Wizard of Oz user study of 'ALTCAI', an ECA with three modes of interaction (i.e., adaptive speech and text, adaptive ECA, and non-adaptive ECA). We compare reported engagement with these modes from 44 maternal women who have differing levels of literacy. The study shows that a combination of embodiment and adaptivity scaffolds reported engagement, but matters of health-literacy and language introduce nuanced considerations for the design of ECAs.","PeriodicalId":148152,"journal":{"name":"Proceedings of the 21st ACM International Conference on Intelligent Virtual Agents","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116487509","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Tessa Beinema, Daniel P. Davison, D. Reidsma, O. Baños, Merijn Bruijnes, B. Donval, Álvaro Fides Valero, D. Heylen, Dennis Hofs, Gerwin Huizing, Reshamashree B. Kantharaju, R. Klaassen, Jan Kolkmeier, Kostas Konsolakis, A. Pease, C. Pelachaud, Donatella Simonetti, Mark Snaith, V. Traver, Jorien van Loon, J. Visser, M. Weusthof, Fajrian Yunus, H. Hermens, H. O. D. Akker, Merijn Brui, R. Kantharaju
The development of applications with intelligent virtual agents (IVA) often comes with integration of multiple complex components. In this article we present the Agents United Platform: an open source platform that researchers and developers can use as a starting point to setup their own multi-IVA applications. The new platform provides developers with a set of integrated components in a sense-remember-think-act architecture. Integrated components are a sensor framework, memory component, Topic Selection Engine, interaction manager (Flipper), two dialogue execution engines, and two behaviour realisers (ASAP and GRETA) of which the agents can seamlessly interact with each other. This article discusses the platform and its individual components. It also highlights some of the novelties that arise from the integration of components and elaborates on directions for future work.
具有智能虚拟代理(IVA)的应用程序的开发通常伴随着多个复杂组件的集成。在本文中，我们将介绍Agents United Platform:这是一个开源平台，研究人员和开发人员可以将其作为建立自己的多iva应用程序的起点。新平台以“感知-记忆-思考-行动”的架构为开发人员提供了一组集成组件。集成组件包括传感器框架、内存组件、主题选择引擎、交互管理器(Flipper)、两个对话执行引擎和两个行为实现器(ASAP和GRETA)，其中代理之间可以无缝交互。本文将讨论该平台及其各个组件。它还强调了由于组件集成而产生的一些新奇之处，并详细说明了未来工作的方向。
{"title":"Agents United: An Open Platform for Multi-Agent Conversational Systems","authors":"Tessa Beinema, Daniel P. Davison, D. Reidsma, O. Baños, Merijn Bruijnes, B. Donval, Álvaro Fides Valero, D. Heylen, Dennis Hofs, Gerwin Huizing, Reshamashree B. Kantharaju, R. Klaassen, Jan Kolkmeier, Kostas Konsolakis, A. Pease, C. Pelachaud, Donatella Simonetti, Mark Snaith, V. Traver, Jorien van Loon, J. Visser, M. Weusthof, Fajrian Yunus, H. Hermens, H. O. D. Akker, Merijn Brui, R. Kantharaju","doi":"10.1145/3472306.3478352","DOIUrl":"https://doi.org/10.1145/3472306.3478352","url":null,"abstract":"The development of applications with intelligent virtual agents (IVA) often comes with integration of multiple complex components. In this article we present the Agents United Platform: an open source platform that researchers and developers can use as a starting point to setup their own multi-IVA applications. The new platform provides developers with a set of integrated components in a sense-remember-think-act architecture. Integrated components are a sensor framework, memory component, Topic Selection Engine, interaction manager (Flipper), two dialogue execution engines, and two behaviour realisers (ASAP and GRETA) of which the agents can seamlessly interact with each other. This article discusses the platform and its individual components. It also highlights some of the novelties that arise from the integration of components and elaborates on directions for future work.","PeriodicalId":148152,"journal":{"name":"Proceedings of the 21st ACM International Conference on Intelligent Virtual Agents","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125671125","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
P. Feijóo-García, Mohan S Zalake, A. G. de Siqueira, Benjamin C. Lok, Felix G. Hamza-Lup
In the context of mental wellness support, trust and intimacy between a counselor and a patient are necessary to converge healing processes positively. However, convincing students to trust a virtual human for topics regarding mental wellness is a complex problem that requires understanding students' experiences. Based on research that discusses mental health as a concerning topic regarding Computer Science (CS) students, this paper investigates how undergraduate computing-related students perceive virtual humans' expertise on mental wellness support based on demographic resemblance on spoken accent and gender. Four virtual human counselors were developed to conduct the study, as 58 undergraduate computing-related students from two North American universities were recruited and assessed. Our findings suggest that students were less inclined to interact with a male virtual human than a female one. Also, that spoken accents can impact students' perceptions of expertise under students' multilingualism.
{"title":"Effects of Virtual Humans' Gender and Spoken Accent on Users' Perceptions of Expertise in Mental Wellness Conversations","authors":"P. Feijóo-García, Mohan S Zalake, A. G. de Siqueira, Benjamin C. Lok, Felix G. Hamza-Lup","doi":"10.1145/3472306.3478367","DOIUrl":"https://doi.org/10.1145/3472306.3478367","url":null,"abstract":"In the context of mental wellness support, trust and intimacy between a counselor and a patient are necessary to converge healing processes positively. However, convincing students to trust a virtual human for topics regarding mental wellness is a complex problem that requires understanding students' experiences. Based on research that discusses mental health as a concerning topic regarding Computer Science (CS) students, this paper investigates how undergraduate computing-related students perceive virtual humans' expertise on mental wellness support based on demographic resemblance on spoken accent and gender. Four virtual human counselors were developed to conduct the study, as 58 undergraduate computing-related students from two North American universities were recruited and assessed. Our findings suggest that students were less inclined to interact with a male virtual human than a female one. Also, that spoken accents can impact students' perceptions of expertise under students' multilingualism.","PeriodicalId":148152,"journal":{"name":"Proceedings of the 21st ACM International Conference on Intelligent Virtual Agents","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122163980","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Immersive virtual worlds are increasingly being used for education, training, and entertainment, and virtual humans that can interact with human users in these worlds play many important roles. Understating the emotional constructs of the user and generating multimodal forms of communications that are aligned with the user's needs and input is key to designing AI agents. Most virtual agents and communicative systems lack the ability to understand enthusiasm or generate multimodal enthusiastic communicative presentations. In this work, we argue for the importance of including enthusiasm in the design of human-AI collaboration and communication and review the existing datasets and models that can be used to bridge the gap in this area.
{"title":"Towards Designing Enthusiastic AI Agents","authors":"Carla Viegas, Malihe Alikhani","doi":"10.1145/3472306.3478366","DOIUrl":"https://doi.org/10.1145/3472306.3478366","url":null,"abstract":"Immersive virtual worlds are increasingly being used for education, training, and entertainment, and virtual humans that can interact with human users in these worlds play many important roles. Understating the emotional constructs of the user and generating multimodal forms of communications that are aligned with the user's needs and input is key to designing AI agents. Most virtual agents and communicative systems lack the ability to understand enthusiasm or generate multimodal enthusiastic communicative presentations. In this work, we argue for the importance of including enthusiasm in the design of human-AI collaboration and communication and review the existing datasets and models that can be used to bridge the gap in this area.","PeriodicalId":148152,"journal":{"name":"Proceedings of the 21st ACM International Conference on Intelligent Virtual Agents","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123571462","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
L. Dupuy, E. D. Sevin, J. Micoulaud-Franchi, P. Philip
The COVID-19 crisis has generated an increase of sleep problems in the general population. Digital technologies can help dealing with mental health repercussions of COVID-19 but their acceptance by the population need to be better understood. KANOPEE is a smartphone application providing interactions with a virtual companion to screen and deliver personalized advices to deal with sleep problems. In this study we tried to highlight the factors associated with acceptance of this app, among factors including user characteristics, perceived trustworthiness of the virtual companion and context of use. 3,479 users answered the acceptance questionnaires, with a very positive attitude towards the app. Results indicate that age, education, familiarity with technologies, trustworthiness of the virtual agent and length of interaction are significantly associated with acceptance of the app. To conclude, this study is one of the first to measure acceptance of a virtual companion providing support during the COVID-19 crisis, and provide avenues of research for design and evaluation of intelligent virtual agents for health.
{"title":"Factors associated with acceptance of a virtual companion providing screening and advices for sleep problems during COVID-19 crisis","authors":"L. Dupuy, E. D. Sevin, J. Micoulaud-Franchi, P. Philip","doi":"10.1145/3472306.3478334","DOIUrl":"https://doi.org/10.1145/3472306.3478334","url":null,"abstract":"The COVID-19 crisis has generated an increase of sleep problems in the general population. Digital technologies can help dealing with mental health repercussions of COVID-19 but their acceptance by the population need to be better understood. KANOPEE is a smartphone application providing interactions with a virtual companion to screen and deliver personalized advices to deal with sleep problems. In this study we tried to highlight the factors associated with acceptance of this app, among factors including user characteristics, perceived trustworthiness of the virtual companion and context of use. 3,479 users answered the acceptance questionnaires, with a very positive attitude towards the app. Results indicate that age, education, familiarity with technologies, trustworthiness of the virtual agent and length of interaction are significantly associated with acceptance of the app. To conclude, this study is one of the first to measure acceptance of a virtual companion providing support during the COVID-19 crisis, and provide avenues of research for design and evaluation of intelligent virtual agents for health.","PeriodicalId":148152,"journal":{"name":"Proceedings of the 21st ACM International Conference on Intelligent Virtual Agents","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133533920","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
There is a new crisis emerging in human-agent interaction research: Instead of using validated questionnaires, individual studies are creating new questionnaires that claim to measure identical constructs. This makes replication studies and comparisons between studies near to impossible. In turn, meta-analyses to determine which characteristics are important to create agents that the user experiences as being intelligent are difficult to conduct. As part of the attempt to battle this crisis, in this current paper, we suggest the use of a Theory of Mind task to measure the implicit social behaviour users exhibit towards a virtual agent. In a two-part study, we present findings that suggest that participants conduct this Theory of Mind task as expected: participants adapt towards our virtual agent more than when they conduct the task alone. We additionally present preliminary results correlating performance in the Theory of Mind task to validated constructs. Unfortunately, our current results do not correlate significantly to the existing constructs. Data-collection is ongoing and hence no firm conclusions can be made about this second set of results. However, our data suggest that it is important to become aware that the existing validated constructs used in HCI research may not be tapping into what the researchers assume, and hence provide a basis for important discussions about these implications.
{"title":"Linking Theory of Mind in Human-Agent Interactions to Validated Evaluations: Can Explicit Questionnaires Measure Implicit Behaviour?","authors":"Evelien Heyselaar, T. Bosse","doi":"10.1145/3472306.3478343","DOIUrl":"https://doi.org/10.1145/3472306.3478343","url":null,"abstract":"There is a new crisis emerging in human-agent interaction research: Instead of using validated questionnaires, individual studies are creating new questionnaires that claim to measure identical constructs. This makes replication studies and comparisons between studies near to impossible. In turn, meta-analyses to determine which characteristics are important to create agents that the user experiences as being intelligent are difficult to conduct. As part of the attempt to battle this crisis, in this current paper, we suggest the use of a Theory of Mind task to measure the implicit social behaviour users exhibit towards a virtual agent. In a two-part study, we present findings that suggest that participants conduct this Theory of Mind task as expected: participants adapt towards our virtual agent more than when they conduct the task alone. We additionally present preliminary results correlating performance in the Theory of Mind task to validated constructs. Unfortunately, our current results do not correlate significantly to the existing constructs. Data-collection is ongoing and hence no firm conclusions can be made about this second set of results. However, our data suggest that it is important to become aware that the existing validated constructs used in HCI research may not be tapping into what the researchers assume, and hence provide a basis for important discussions about these implications.","PeriodicalId":148152,"journal":{"name":"Proceedings of the 21st ACM International Conference on Intelligent Virtual Agents","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125316644","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Emmanuel Johnson, J. Gratch, Jill Boberg, D. DeVault, Peter Kim, Gale M. Lucas
Women earn less than men in technical fields. Competing theories have been offered to explain this disparity. Some argue that women underperform in negotiating their salary, in-part due to language in job descriptions, called gender triggers, which leave women feeling disadvantaged in salary negotiations. Others point to structural and institutional bias: i.e., recruiters make better offers to men even when women exhibit equal negotiation skills. As a final salary is co-constructed though an interaction between employees and recruiters, it is difficult to disentangle these views. Here, we discuss how intelligent virtual agents serve as powerful methodological tools that lend new insight into this psychological debate. We use virtual negotiators to examine the impact of gender triggers on computer science (CS) undergraduates that engaged in a simulated salary negotiation with an automated recruiter. We find that, regardless of gender, CS students are reluctant to negotiate, and this hesitancy likely lowers their starting salary. Even when they negotiate, students show little skill in discovering tradeoffs that could enhance their salary, highlighting the need for negotiation training in technical fields. Most importantly, we find little evidence that gender triggers impact women's negotiated outcomes, at least within the field of CS. We argue that findings that emphasize women's individual deficits may reflect a lack of experimental control, which intelligent agents can help correct, and that structural and institutional explanations of inequity deserve greater attention.
{"title":"Using Intelligent Agents to Examine Gender in Negotiations","authors":"Emmanuel Johnson, J. Gratch, Jill Boberg, D. DeVault, Peter Kim, Gale M. Lucas","doi":"10.1145/3472306.3478348","DOIUrl":"https://doi.org/10.1145/3472306.3478348","url":null,"abstract":"Women earn less than men in technical fields. Competing theories have been offered to explain this disparity. Some argue that women underperform in negotiating their salary, in-part due to language in job descriptions, called gender triggers, which leave women feeling disadvantaged in salary negotiations. Others point to structural and institutional bias: i.e., recruiters make better offers to men even when women exhibit equal negotiation skills. As a final salary is co-constructed though an interaction between employees and recruiters, it is difficult to disentangle these views. Here, we discuss how intelligent virtual agents serve as powerful methodological tools that lend new insight into this psychological debate. We use virtual negotiators to examine the impact of gender triggers on computer science (CS) undergraduates that engaged in a simulated salary negotiation with an automated recruiter. We find that, regardless of gender, CS students are reluctant to negotiate, and this hesitancy likely lowers their starting salary. Even when they negotiate, students show little skill in discovering tradeoffs that could enhance their salary, highlighting the need for negotiation training in technical fields. Most importantly, we find little evidence that gender triggers impact women's negotiated outcomes, at least within the field of CS. We argue that findings that emphasize women's individual deficits may reflect a lack of experimental control, which intelligent agents can help correct, and that structural and institutional explanations of inequity deserve greater attention.","PeriodicalId":148152,"journal":{"name":"Proceedings of the 21st ACM International Conference on Intelligent Virtual Agents","volume":"129 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132149725","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Negotiation is a social interaction aimed at reaching a mutually beneficial agreement among all participants in a conflict situation. Unfortunately, parties often find negotiations threatening or aversive, undermining the chances of reaching good agreements. Politeness strategies are means of communicating one's demands to a counterpart without threatening the counterpart's "face" by using tactical phrasing. Politeness strategies are classified into positive, negative, and off-record strategies depending on how they avoid face-threatening acts. In the present study, we investigated whether differences in the politeness strategies used by a virtual agent impact negotiated outcomes in a non-zero-sum situation. The participants (n=106) engaged in an online multi-issue negotiation with one of three agents (using the positive, off-record, or no politeness strategies, while the negative strategy was excluded because of validation failure). The results showed that the agents who used the off-record strategy were able to extract greater concessions from their human partners, whereas positive politeness, which does not threaten the other's face, led to fairer negotiated agreements. The human participants were comfortable exploiting agents who failed to adopt any politeness in their language. Politeness is a part of the toolbox that people use to manage the social rewards and punishments associated with all interactions, and our work highlights that agents can use this important social tool.
{"title":"Effect of politeness strategies in dialogue on negotiation outcomes","authors":"K. Terada, Mitsuki Okazoe, J. Gratch","doi":"10.1145/3472306.3478336","DOIUrl":"https://doi.org/10.1145/3472306.3478336","url":null,"abstract":"Negotiation is a social interaction aimed at reaching a mutually beneficial agreement among all participants in a conflict situation. Unfortunately, parties often find negotiations threatening or aversive, undermining the chances of reaching good agreements. Politeness strategies are means of communicating one's demands to a counterpart without threatening the counterpart's \"face\" by using tactical phrasing. Politeness strategies are classified into positive, negative, and off-record strategies depending on how they avoid face-threatening acts. In the present study, we investigated whether differences in the politeness strategies used by a virtual agent impact negotiated outcomes in a non-zero-sum situation. The participants (n=106) engaged in an online multi-issue negotiation with one of three agents (using the positive, off-record, or no politeness strategies, while the negative strategy was excluded because of validation failure). The results showed that the agents who used the off-record strategy were able to extract greater concessions from their human partners, whereas positive politeness, which does not threaten the other's face, led to fairer negotiated agreements. The human participants were comfortable exploiting agents who failed to adopt any politeness in their language. Politeness is a part of the toolbox that people use to manage the social rewards and punishments associated with all interactions, and our work highlights that agents can use this important social tool.","PeriodicalId":148152,"journal":{"name":"Proceedings of the 21st ACM International Conference on Intelligent Virtual Agents","volume":"270 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133491108","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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