Abstract
Currently, pioneer companies are working hard to construct applied ethical frameworks in different sectors for using AI components that generate trust in their clients and workforce. However, independent of these few companies, there is still a considerable gap between understanding the impact of using responsible AI components, the implications of the lack of use, and what is currently applied in the industrial sector. Given that industry has shown an increased commitment to incorporating AI components, works focus on broadening the understanding of manufacturing sector stakeholders of what approaches could be considered within AI life-cycle, reducing the gap between principles and actionable requirements, and defining fundamental considerations based on risk management for incorporating, and managing, AI-based on responsible AI are required. In this work, we present a summary of the most suitable approaches that can be used for implementation and the lessons learned from a European Funded project (ASSISTANT).
| Original language | English |
|---|---|
| Pages (from-to) | 377-382 |
| Number of pages | 6 |
| Journal | IFAC-PapersOnLine |
| Volume | 55 |
| Issue number | 10 |
| DOIs | |
| Publication status | Published - 2022 |
| Event | 10th IFAC Conference on Manufacturing Modelling, Management and Control, MIM 2022 - Nantes, France Duration: 22 Jun 2022 → 24 Jun 2022 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 9 Industry, Innovation, and Infrastructure
Keywords
- AI
- AI en manufacturing
- AI ethics
- design methodology for HMS
- Human centered automation
- responsible AI
- standardisation
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