RYEL: An Experimental Study in the Behavioral Response of Judges Using a Novel Technique for Acquiring Higher-Order Thinking Based on Explainable Artificial Intelligence and Case-Based Reasoning
The need for studies connecting machine explainability with human behavior is essential, especially for a detailed understanding of a human’s perspective, thoughts, and sensations according to a context. A novel system called RYEL was developed based on Subject-Matter Experts (SME) to investigate ne...
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doaj-d8c8d5030d0549a58fe3ff2c189c60662021-07-01T00:46:06ZengMDPI AGElectronics2079-92922021-06-01101500150010.3390/electronics10121500RYEL: An Experimental Study in the Behavioral Response of Judges Using a Novel Technique for Acquiring Higher-Order Thinking Based on Explainable Artificial Intelligence and Case-Based ReasoningLuis Raúl Rodríguez Oconitrillo0Juan José Vargas1Arturo Camacho2Álvaro Burgos3Juan Manuel Corchado4School of Computer Science and Informatics, Universidad de Costa Rica (UCR), Ciudad Universitaria Rodrigo Facio Brenes, San José 11501-2060, Costa RicaSchool of Computer Science and Informatics, Universidad de Costa Rica (UCR), Ciudad Universitaria Rodrigo Facio Brenes, San José 11501-2060, Costa RicaSchool of Computer Science and Informatics, Universidad de Costa Rica (UCR), Ciudad Universitaria Rodrigo Facio Brenes, San José 11501-2060, Costa RicaLaw School, Universidad de Costa Rica (UCR), Ciudad Universitaria Rodrigo Facio Brenes, San José 11501-2060, Costa RicaBisite Research Group, Universidad de Salamanca, 37008 Salamanca, SpainThe need for studies connecting machine explainability with human behavior is essential, especially for a detailed understanding of a human’s perspective, thoughts, and sensations according to a context. A novel system called RYEL was developed based on Subject-Matter Experts (SME) to investigate new techniques for acquiring higher-order thinking, the perception, the use of new computational explanatory techniques, support decision-making, and the judge’s cognition and behavior. Thus, a new spectrum is covered and promises to be a new area of study called Interpretation-Assessment/Assessment-Interpretation (IA-AI), consisting of explaining machine inferences and the interpretation and assessment from a human. It allows expressing a semantic, ontological, and hermeneutical meaning related to the psyche of a human (judge). The system has an interpretative and explanatory nature, and in the future, could be used in other domains of discourse. More than 33 experts in Law and Artificial Intelligence validated the functional design. More than 26 judges, most of them specializing in psychology and criminology from Colombia, Ecuador, Panama, Spain, Argentina, and Costa Rica, participated in the experiments. The results of the experimentation have been very positive. As a challenge, this research represents a paradigm shift in legal data processing.https://www.mdpi.com/2079-9292/10/12/1500interpretation-assessment/assessment-interpretation (IA-AI)hybrid artificial intelligence systemmixture of experts (MOE)explainable case-based reasoning (XCBR)explainable artificial intelligence (XAI)semantic networks (SN) |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Luis Raúl Rodríguez Oconitrillo Juan José Vargas Arturo Camacho Álvaro Burgos Juan Manuel Corchado |
spellingShingle |
Luis Raúl Rodríguez Oconitrillo Juan José Vargas Arturo Camacho Álvaro Burgos Juan Manuel Corchado RYEL: An Experimental Study in the Behavioral Response of Judges Using a Novel Technique for Acquiring Higher-Order Thinking Based on Explainable Artificial Intelligence and Case-Based Reasoning Electronics interpretation-assessment/assessment-interpretation (IA-AI) hybrid artificial intelligence system mixture of experts (MOE) explainable case-based reasoning (XCBR) explainable artificial intelligence (XAI) semantic networks (SN) |
author_facet |
Luis Raúl Rodríguez Oconitrillo Juan José Vargas Arturo Camacho Álvaro Burgos Juan Manuel Corchado |
author_sort |
Luis Raúl Rodríguez Oconitrillo |
title |
RYEL: An Experimental Study in the Behavioral Response of Judges Using a Novel Technique for Acquiring Higher-Order Thinking Based on Explainable Artificial Intelligence and Case-Based Reasoning |
title_short |
RYEL: An Experimental Study in the Behavioral Response of Judges Using a Novel Technique for Acquiring Higher-Order Thinking Based on Explainable Artificial Intelligence and Case-Based Reasoning |
title_full |
RYEL: An Experimental Study in the Behavioral Response of Judges Using a Novel Technique for Acquiring Higher-Order Thinking Based on Explainable Artificial Intelligence and Case-Based Reasoning |
title_fullStr |
RYEL: An Experimental Study in the Behavioral Response of Judges Using a Novel Technique for Acquiring Higher-Order Thinking Based on Explainable Artificial Intelligence and Case-Based Reasoning |
title_full_unstemmed |
RYEL: An Experimental Study in the Behavioral Response of Judges Using a Novel Technique for Acquiring Higher-Order Thinking Based on Explainable Artificial Intelligence and Case-Based Reasoning |
title_sort |
ryel: an experimental study in the behavioral response of judges using a novel technique for acquiring higher-order thinking based on explainable artificial intelligence and case-based reasoning |
publisher |
MDPI AG |
series |
Electronics |
issn |
2079-9292 |
publishDate |
2021-06-01 |
description |
The need for studies connecting machine explainability with human behavior is essential, especially for a detailed understanding of a human’s perspective, thoughts, and sensations according to a context. A novel system called RYEL was developed based on Subject-Matter Experts (SME) to investigate new techniques for acquiring higher-order thinking, the perception, the use of new computational explanatory techniques, support decision-making, and the judge’s cognition and behavior. Thus, a new spectrum is covered and promises to be a new area of study called Interpretation-Assessment/Assessment-Interpretation (IA-AI), consisting of explaining machine inferences and the interpretation and assessment from a human. It allows expressing a semantic, ontological, and hermeneutical meaning related to the psyche of a human (judge). The system has an interpretative and explanatory nature, and in the future, could be used in other domains of discourse. More than 33 experts in Law and Artificial Intelligence validated the functional design. More than 26 judges, most of them specializing in psychology and criminology from Colombia, Ecuador, Panama, Spain, Argentina, and Costa Rica, participated in the experiments. The results of the experimentation have been very positive. As a challenge, this research represents a paradigm shift in legal data processing. |
topic |
interpretation-assessment/assessment-interpretation (IA-AI) hybrid artificial intelligence system mixture of experts (MOE) explainable case-based reasoning (XCBR) explainable artificial intelligence (XAI) semantic networks (SN) |
url |
https://www.mdpi.com/2079-9292/10/12/1500 |
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