Artificial Intelligence and Computational Psychological Science Connections

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F46747885%3A24620%2F23%3A00012549" target="_blank" >RIV/46747885:24620/23:00012549 - isvavai.cz</a>

Výsledek na webu

<a href="https://journals.tultech.eu/index.php/qr/article/view/3" target="_blank" >https://journals.tultech.eu/index.php/qr/article/view/3</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.15157/QR.2023.1.1.1-12" target="_blank" >10.15157/QR.2023.1.1.1-12</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Artificial Intelligence and Computational Psychological Science Connections

Popis výsledku v původním jazyce

Computational Psychological Science (CPS) is a rapidly growing field that uses computational models to study human behaviour and cognition. The development of artificial intelligence (AI) algorithms has greatly expanded the potential of CPS by providing powerful tools for modelling complex and dynamic processes in the brain. One area where AI has had a major impact on CPS is in the field of emotion recognition. Researchers can now collect large datasets of emotional facial expressions and use AI algorithms, such as convolutional neural networks (CNNs), to learn how to recognize different emotions from these images. These models can be used to generate predictions about how emotions are represented in the brain and how they are influenced by social and contextual factors. AI algorithms can also be used to optimize the parameters of computational models and improve their accuracy and predictive power. For example, evolutionary algorithms can be used to search for the set of model parameters that best fit the experimental data, while reinforcement learning algorithms can be used to optimize the model‘s decision-making policies in complex and dynamic environments. In addition to emotion recognition, AI has also been used in CPS to model other cognitive processes, such as decision-making, learning, and memory. For example, deep learning algorithms have been used to develop models of how the brain learns and represents visual and auditory stimuli, while reinforcement learning algorithms have been used to model how the brain makes decisions in uncertain and changing environments. Overall, the connection between AI and CPS has the potential to provide new insights into the computational basis of human behaviour and cognition and to develop new interventions and technologies that can improve human well-being. However, this field also raises important ethical and social issues, such as the potential impact of AI on privacy, social inequality, and the future of work. As AI and CPS continue to develop, it is important to carefully consider these issues and ensure that these technologies are used in ways that benefit society as a whole.

Název v anglickém jazyce

Artificial Intelligence and Computational Psychological Science Connections

Popis výsledku anglicky

Computational Psychological Science (CPS) is a rapidly growing field that uses computational models to study human behaviour and cognition. The development of artificial intelligence (AI) algorithms has greatly expanded the potential of CPS by providing powerful tools for modelling complex and dynamic processes in the brain. One area where AI has had a major impact on CPS is in the field of emotion recognition. Researchers can now collect large datasets of emotional facial expressions and use AI algorithms, such as convolutional neural networks (CNNs), to learn how to recognize different emotions from these images. These models can be used to generate predictions about how emotions are represented in the brain and how they are influenced by social and contextual factors. AI algorithms can also be used to optimize the parameters of computational models and improve their accuracy and predictive power. For example, evolutionary algorithms can be used to search for the set of model parameters that best fit the experimental data, while reinforcement learning algorithms can be used to optimize the model‘s decision-making policies in complex and dynamic environments. In addition to emotion recognition, AI has also been used in CPS to model other cognitive processes, such as decision-making, learning, and memory. For example, deep learning algorithms have been used to develop models of how the brain learns and represents visual and auditory stimuli, while reinforcement learning algorithms have been used to model how the brain makes decisions in uncertain and changing environments. Overall, the connection between AI and CPS has the potential to provide new insights into the computational basis of human behaviour and cognition and to develop new interventions and technologies that can improve human well-being. However, this field also raises important ethical and social issues, such as the potential impact of AI on privacy, social inequality, and the future of work. As AI and CPS continue to develop, it is important to carefully consider these issues and ensure that these technologies are used in ways that benefit society as a whole.

Druh

J_ost - Ostatní články v recenzovaných periodicích

CEP obor

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OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2023

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Quanta Research :

ISSN

2806-3279

e-ISSN

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Svazek periodika

1

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

EE - Estonská republika

Počet stran výsledku

12

Strana od-do

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Kód UT WoS článku

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EID výsledku v databázi Scopus

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