| Title | Human-Centered and Sustainable Artificial Intelligence in Industry 5.0: Challenges and Perspectives |
|---|---|
| ID_Doc | 12863 |
| Authors | Martini, B; Bellisario, D; Coletti, P |
| Title | Human-Centered and Sustainable Artificial Intelligence in Industry 5.0: Challenges and Perspectives |
| Year | 2024 |
| Published | Sustainability, 16.0, 13 |
| Abstract | The aim of this position paper is to identify a specific focus and the major challenges related to the human-centered artificial intelligence (HCAI) approach in the field of Industry 5.0 and the circular economy. A first step towards the opening of a line of research is necessary to aggregate multidisciplinary and interdisciplinary skills to promote and take into consideration the different aspects related to this topic, from the more technical and engineering aspects to the social ones and the repercussions in terms of sustainability. The proposal and vision of this preliminary work is to identify and discuss a suitable field for such interaction. This field has been identified, specifically, within additive manufacturing (AM) in the context of Industry 5.0. Additive manufacturing (AM), is a disruptive opportunity for more sustainable production systems that can be better optimized with AI, becoming an ideal platform for interconnection between different levels of application and integration of HCAI concepts, and at the same time able to prove them. In this context, two prospective areas with a high application impact of HCAI are those of AM-oriented supply chain and product customization in the AM field, enabled by a plethora of recently emerging technologies such as the internet of things, cloud and edge computing, and next-generation networks (5G). The paper concludes with the challenges HCAI poses to public policymakers, who face significant policy challenges in regulating artificial intelligence, and addressing the socioeconomic and technological impacts. Decision-makers are required to address these challenges by adopting some tentative policy recommendations. |
| https://doi.org/10.3390/su16135448 |
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