Explainable artificial intelligence for education and training
| Autor: | Waldemar Karwowski, Farzad V. Farahani, Krzysztof Fiok, Tareq Z. Ahram |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
0303 health sciences
Computer science business.industry User perception 02 engineering and technology Human-centered computing Training (civil) 03 medical and health sciences Software Action (philosophy) Modeling and Simulation 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Artificial intelligence business Engineering (miscellaneous) 030304 developmental biology |
| Zdroj: | The Journal of Defense Modeling and Simulation: Applications, Methodology, Technology. 19:133-144 |
| ISSN: | 1557-380X 1548-5129 |
| Popis: | Researchers and software users benefit from the rapid growth of artificial intelligence (AI) to an unprecedented extent in various domains where automated intelligent action is required. However, as they continue to engage with AI, they also begin to understand the limitations and risks associated with ceding control and decision-making to not always transparent artificial computer agents. Understanding of “what is happening in the black box” becomes feasible with explainable AI (XAI) methods designed to mitigate these risks and introduce trust into human-AI interactions. Our study reviews the essential capabilities, limitations, and desiderata of XAI tools developed over recent years and reviews the history of XAI and AI in education (AIED). We present different approaches to AI and XAI from the viewpoint of researchers focused on AIED in comparison with researchers focused on AI and machine learning (ML). We conclude that both groups of interest desire increased efforts to obtain improved XAI tools; however, these groups formulate different target user groups and expectations regarding XAI features and provide different examples of possible achievements. We summarize these viewpoints and provide guidelines for scientists looking to incorporate XAI into their own work. |
| Databáze: | OpenAIRE |
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