{"title":"拥有社交和情商的智能家居","authors":"J. Hoey","doi":"10.1145/3134230.3134243","DOIUrl":null,"url":null,"abstract":"Pervasive intelligent assistive technologies promise to alleviate some of the increasing burden of care for persons with age-related cognitive disabilities, such as Alzheimer's disease. However, despite tremendous progress, many attempts to develop and implement real world applications have failed to become widely adopted. In this talk, I will argue that a key barrier to the adoption of these technologies is a lack of alignment, on a social and emotional level, between the technology and its users. I argue that products which do not deeply embed social and emotional intelligence will fail to align with the needs and values of target end-users, and will thereby have only limited utility. I will then introduce a socio-cultural reasoning engine called \"BayesACT\" that can be used to provide this level of affective reasoning. BayesACT is arises from the symbolic interactionist tradition in sociological social psychology, in which culturally shared affective and cognitive meanings provide powerful predictive insights into human action. BayesACT can learn these shared meanings during an interaction, and can tailor interventions to specific individuals in a way that ensures smoother and more effective uptake and response. I will give an introduction to this reasoning engine, and will discuss how affective reasoning could be used to create truly adaptive assistive technologies.","PeriodicalId":209424,"journal":{"name":"Proceedings of the 4th International Workshop on Sensor-based Activity Recognition and Interaction","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2017-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Smarter Smart Homes with Social and Emotional Intelligence\",\"authors\":\"J. Hoey\",\"doi\":\"10.1145/3134230.3134243\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Pervasive intelligent assistive technologies promise to alleviate some of the increasing burden of care for persons with age-related cognitive disabilities, such as Alzheimer's disease. However, despite tremendous progress, many attempts to develop and implement real world applications have failed to become widely adopted. In this talk, I will argue that a key barrier to the adoption of these technologies is a lack of alignment, on a social and emotional level, between the technology and its users. I argue that products which do not deeply embed social and emotional intelligence will fail to align with the needs and values of target end-users, and will thereby have only limited utility. I will then introduce a socio-cultural reasoning engine called \\\"BayesACT\\\" that can be used to provide this level of affective reasoning. BayesACT is arises from the symbolic interactionist tradition in sociological social psychology, in which culturally shared affective and cognitive meanings provide powerful predictive insights into human action. BayesACT can learn these shared meanings during an interaction, and can tailor interventions to specific individuals in a way that ensures smoother and more effective uptake and response. I will give an introduction to this reasoning engine, and will discuss how affective reasoning could be used to create truly adaptive assistive technologies.\",\"PeriodicalId\":209424,\"journal\":{\"name\":\"Proceedings of the 4th International Workshop on Sensor-based Activity Recognition and Interaction\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-09-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 4th International Workshop on Sensor-based Activity Recognition and Interaction\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3134230.3134243\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 4th International Workshop on Sensor-based Activity Recognition and Interaction","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3134230.3134243","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Smarter Smart Homes with Social and Emotional Intelligence
Pervasive intelligent assistive technologies promise to alleviate some of the increasing burden of care for persons with age-related cognitive disabilities, such as Alzheimer's disease. However, despite tremendous progress, many attempts to develop and implement real world applications have failed to become widely adopted. In this talk, I will argue that a key barrier to the adoption of these technologies is a lack of alignment, on a social and emotional level, between the technology and its users. I argue that products which do not deeply embed social and emotional intelligence will fail to align with the needs and values of target end-users, and will thereby have only limited utility. I will then introduce a socio-cultural reasoning engine called "BayesACT" that can be used to provide this level of affective reasoning. BayesACT is arises from the symbolic interactionist tradition in sociological social psychology, in which culturally shared affective and cognitive meanings provide powerful predictive insights into human action. BayesACT can learn these shared meanings during an interaction, and can tailor interventions to specific individuals in a way that ensures smoother and more effective uptake and response. I will give an introduction to this reasoning engine, and will discuss how affective reasoning could be used to create truly adaptive assistive technologies.