Three levels at which the user's cognition can be represented in artificial intelligence
Artificial intelligence (AI) plays an important role in modern society. AI applications are omnipresent and assist many decisions we make in daily life. A common and important feature of such AI applications are user models. These models allow an AI application to adapt to a specific user. Here, we...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2023-01-01
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| Series: | Frontiers in Artificial Intelligence |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/frai.2022.1092053/full |
| _version_ | 1797954005734785024 |
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| author | Baptist Liefooghe Leendert van Maanen |
| author_facet | Baptist Liefooghe Leendert van Maanen |
| author_sort | Baptist Liefooghe |
| collection | DOAJ |
| description | Artificial intelligence (AI) plays an important role in modern society. AI applications are omnipresent and assist many decisions we make in daily life. A common and important feature of such AI applications are user models. These models allow an AI application to adapt to a specific user. Here, we argue that user models in AI can be optimized by modeling these user models more closely to models of human cognition. We identify three levels at which insights from human cognition can be—and have been—integrated in user models. Such integration can be very loose with user models only being inspired by general knowledge of human cognition or very tight with user models implementing specific cognitive processes. Using AI-based applications in the context of education as a case study, we demonstrate that user models that are more deeply rooted in models of cognition offer more valid and more fine-grained adaptations to an individual user. We propose that such user models can also advance the development of explainable AI. |
| first_indexed | 2024-04-10T23:10:56Z |
| format | Article |
| id | doaj.art-3545f3be892e4385b4ea329c656c9cb1 |
| institution | Directory Open Access Journal |
| issn | 2624-8212 |
| language | English |
| last_indexed | 2024-04-10T23:10:56Z |
| publishDate | 2023-01-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Artificial Intelligence |
| spelling | doaj.art-3545f3be892e4385b4ea329c656c9cb12023-01-13T05:28:13ZengFrontiers Media S.A.Frontiers in Artificial Intelligence2624-82122023-01-01510.3389/frai.2022.10920531092053Three levels at which the user's cognition can be represented in artificial intelligenceBaptist LiefoogheLeendert van MaanenArtificial intelligence (AI) plays an important role in modern society. AI applications are omnipresent and assist many decisions we make in daily life. A common and important feature of such AI applications are user models. These models allow an AI application to adapt to a specific user. Here, we argue that user models in AI can be optimized by modeling these user models more closely to models of human cognition. We identify three levels at which insights from human cognition can be—and have been—integrated in user models. Such integration can be very loose with user models only being inspired by general knowledge of human cognition or very tight with user models implementing specific cognitive processes. Using AI-based applications in the context of education as a case study, we demonstrate that user models that are more deeply rooted in models of cognition offer more valid and more fine-grained adaptations to an individual user. We propose that such user models can also advance the development of explainable AI.https://www.frontiersin.org/articles/10.3389/frai.2022.1092053/fullhuman cognitionuser modelexplainable AIcognitive modelinghuman behavior |
| spellingShingle | Baptist Liefooghe Leendert van Maanen Three levels at which the user's cognition can be represented in artificial intelligence Frontiers in Artificial Intelligence human cognition user model explainable AI cognitive modeling human behavior |
| title | Three levels at which the user's cognition can be represented in artificial intelligence |
| title_full | Three levels at which the user's cognition can be represented in artificial intelligence |
| title_fullStr | Three levels at which the user's cognition can be represented in artificial intelligence |
| title_full_unstemmed | Three levels at which the user's cognition can be represented in artificial intelligence |
| title_short | Three levels at which the user's cognition can be represented in artificial intelligence |
| title_sort | three levels at which the user s cognition can be represented in artificial intelligence |
| topic | human cognition user model explainable AI cognitive modeling human behavior |
| url | https://www.frontiersin.org/articles/10.3389/frai.2022.1092053/full |
| work_keys_str_mv | AT baptistliefooghe threelevelsatwhichtheuserscognitioncanberepresentedinartificialintelligence AT leendertvanmaanen threelevelsatwhichtheuserscognitioncanberepresentedinartificialintelligence |