Matches in SemOpenAlex for { <https://semopenalex.org/work/W3156383530> ?p ?o ?g. }
Showing items 1 to 70 of
70
with 100 items per page.
- W3156383530 endingPage "559" @default.
- W3156383530 startingPage "547" @default.
- W3156383530 abstract "Affect and emotions play a crucial role in any human experience. However, these components are often overlooked in the design of user experiences with virtual AI agents. In this paper, we investigate the possibility of AI agents - in particular virtual assistants, to adapt to users’ emotional states in different interaction scenarios. Currently, AI agents such as Google Home, Alexa, and Siri, support very limited forms of affective interactions, despite showing great potentials for their implementation. This gap reflects the lack of specific theoretical models for affective and empathetic interactions with AI assistants, as well as current technological limitations. In this work, we address the first issues, i.e. the lack of theoretical models, from an experience design perspective. We present the Adaptive Affective Loop, a revised version of the Affective Loop model from social robotics, where we introduce two new concepts. First, the use of distributed interfaces for AI agents, where all IoT elements controlled by the agent can be leveraged to generate affective interactions. Second, the integration of learning and adaptive features, which allow the AI agent to assess the effectiveness of its affective response, and to adapt it over time, in order to generate custom empathetic responses for each user. We apply the model to three interaction scenarios: direct, pre-defined, and indirect interactions with the AI agent. We discuss benefits and limits of our model, and we address the challenges designers will face while envisioning experiences for such new affective scenarios." @default.
- W3156383530 created "2021-04-26" @default.
- W3156383530 creator A5059150290 @default.
- W3156383530 creator A5089045703 @default.
- W3156383530 creator A5089242554 @default.
- W3156383530 date "2021-01-01" @default.
- W3156383530 modified "2023-09-23" @default.
- W3156383530 title "The Adaptive Affective Loop: How AI Agents Can Generate Empathetic Systemic Experiences" @default.
- W3156383530 cites W1500689121 @default.
- W3156383530 cites W1520861770 @default.
- W3156383530 cites W1867691547 @default.
- W3156383530 cites W1985855315 @default.
- W3156383530 cites W2006740592 @default.
- W3156383530 cites W2271194730 @default.
- W3156383530 cites W2294294917 @default.
- W3156383530 cites W2871950322 @default.
- W3156383530 cites W2943399188 @default.
- W3156383530 cites W2943488796 @default.
- W3156383530 cites W2946526173 @default.
- W3156383530 cites W4230277160 @default.
- W3156383530 doi "https://doi.org/10.1007/978-3-030-73100-7_39" @default.
- W3156383530 hasPublicationYear "2021" @default.
- W3156383530 type Work @default.
- W3156383530 sameAs 3156383530 @default.
- W3156383530 citedByCount "0" @default.
- W3156383530 crossrefType "book-chapter" @default.
- W3156383530 hasAuthorship W3156383530A5059150290 @default.
- W3156383530 hasAuthorship W3156383530A5089045703 @default.
- W3156383530 hasAuthorship W3156383530A5089242554 @default.
- W3156383530 hasBestOaLocation W31563835302 @default.
- W3156383530 hasConcept C107457646 @default.
- W3156383530 hasConcept C12713177 @default.
- W3156383530 hasConcept C154945302 @default.
- W3156383530 hasConcept C15744967 @default.
- W3156383530 hasConcept C2776035688 @default.
- W3156383530 hasConcept C2780626000 @default.
- W3156383530 hasConcept C2983409430 @default.
- W3156383530 hasConcept C41008148 @default.
- W3156383530 hasConcept C46312422 @default.
- W3156383530 hasConcept C6438553 @default.
- W3156383530 hasConceptScore W3156383530C107457646 @default.
- W3156383530 hasConceptScore W3156383530C12713177 @default.
- W3156383530 hasConceptScore W3156383530C154945302 @default.
- W3156383530 hasConceptScore W3156383530C15744967 @default.
- W3156383530 hasConceptScore W3156383530C2776035688 @default.
- W3156383530 hasConceptScore W3156383530C2780626000 @default.
- W3156383530 hasConceptScore W3156383530C2983409430 @default.
- W3156383530 hasConceptScore W3156383530C41008148 @default.
- W3156383530 hasConceptScore W3156383530C46312422 @default.
- W3156383530 hasConceptScore W3156383530C6438553 @default.
- W3156383530 hasLocation W31563835301 @default.
- W3156383530 hasLocation W31563835302 @default.
- W3156383530 hasOpenAccess W3156383530 @default.
- W3156383530 hasPrimaryLocation W31563835301 @default.
- W3156383530 hasRelatedWork W1735294828 @default.
- W3156383530 hasRelatedWork W2057491235 @default.
- W3156383530 hasRelatedWork W2066070356 @default.
- W3156383530 hasRelatedWork W2186554966 @default.
- W3156383530 hasRelatedWork W3014541371 @default.
- W3156383530 hasRelatedWork W3107474891 @default.
- W3156383530 hasRelatedWork W3156383530 @default.
- W3156383530 hasRelatedWork W4313224425 @default.
- W3156383530 hasRelatedWork W4313227616 @default.
- W3156383530 hasRelatedWork W72015656 @default.
- W3156383530 isParatext "false" @default.
- W3156383530 isRetracted "false" @default.
- W3156383530 magId "3156383530" @default.
- W3156383530 workType "book-chapter" @default.