# Explainability as the key ingredient for AI adoption in Industry 5.0 settings

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/explainability-as-the-key-ingredient-for-ai-adoption-in-industry-5-0-settings/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Carlos Agostinho,Zoumpolia Dikopoulou,Eleni Lavasa,Κonstantinos Perakis,Stamatis Pitsios,Rui Branco,Sangeetha Reji,Jonas Hetterich,Evmorfia Biliri,Fenareti Lampathaki,Silvia Rodríguez Del Rey,Vasileios Gkolemis |
| Citations | 31 |
| DOI | 10.3389/frai.2023.1264372 |
| Fields | Business, Management and Accounting,Computer Science |
| Open Access | true |
| OA Status | gold |
| OA URL | https://www.frontiersin.org/articles/10.3389/frai.2023.1264372/pdf?isPublishedV2=False |
| OpenAlex ID | https://openalex.org/W4389570202 |
| PMID | 38146276 |
| Type | article |
| Year | 2023 |

## Paper authors

- [Carlos Agostinho](https://scholariq.org/researchers/carlos-agostinho/)
- [Evmorfia Biliri](https://scholariq.org/researchers/evmorfia-biliri/)
- [Κonstantinos Perakis](https://scholariq.org/researchers/onstantinos-perakis/)
- [Zoumpolia Dikopoulou](https://scholariq.org/researchers/zoumpolia-dikopoulou/)
- [Fenareti Lampathaki](https://scholariq.org/researchers/fenareti-lampathaki/)

## Paper funders

- [European Commission](https://scholariq.org/funders/european-commission/)

## Paper journal

- [Frontiers in Artificial Intelligence](https://scholariq.org/journals/frontiers-in-artificial-intelligence/)

## Paper primary topic

- [Explainable Artificial Intelligence (XAI)](https://scholariq.org/topics/explainable-artificial-intelligence-xai/)

## Paper topics

- [Explainable Artificial Intelligence (XAI)](https://scholariq.org/topics/explainable-artificial-intelligence-xai/)
- [Big Data and Business Intelligence](https://scholariq.org/topics/big-data-and-business-intelligence/)
- [Anomaly Detection Techniques and Applications](https://scholariq.org/topics/anomaly-detection-techniques-and-applications/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.