Artificial Intelligence (AI) has revolutionized various sectors, including Cultural Heritage (CH) and Creative Industries (CI), defining novel opportunities and challenges in preserving tangible and intangible human productions. In such a context, Neural Rendering (NR) paradigms play the pivotal role of 3D reconstructing objects or scenes by optimizing images depicting them. However, there is a lack of work examining the ethical concerns associated with its usage. Those are particularly relevant in scenarios where NR is applied to items protected by intellectual property rights, UNESCO-recognized heritage sites, or items critical for data-driven decisions. For this, we here outline the main ethical findings in this area and place them in a novel framework to guide stakeholders and developers through principles and risks associated with the use of NR in CH and CI. Such a framework examines AI's ethical principles, connected to NR, CH, and CI, supporting the definition of novel ethical guidelines.
Stacchio, L., Balloni, E., Gorgoglione, L., Mancini, A., Giovanola, B., Tiribelli, S., et al. (2024). An ethical framework for trustworthy Neural Rendering applied in cultural heritage and creative industries. FRONTIERS IN COMPUTER SCIENCE, 6, 1-13 [10.3389/fcomp.2024.1459807].
An ethical framework for trustworthy Neural Rendering applied in cultural heritage and creative industries
Stacchio L.;
2024
Abstract
Artificial Intelligence (AI) has revolutionized various sectors, including Cultural Heritage (CH) and Creative Industries (CI), defining novel opportunities and challenges in preserving tangible and intangible human productions. In such a context, Neural Rendering (NR) paradigms play the pivotal role of 3D reconstructing objects or scenes by optimizing images depicting them. However, there is a lack of work examining the ethical concerns associated with its usage. Those are particularly relevant in scenarios where NR is applied to items protected by intellectual property rights, UNESCO-recognized heritage sites, or items critical for data-driven decisions. For this, we here outline the main ethical findings in this area and place them in a novel framework to guide stakeholders and developers through principles and risks associated with the use of NR in CH and CI. Such a framework examines AI's ethical principles, connected to NR, CH, and CI, supporting the definition of novel ethical guidelines.| File | Dimensione | Formato | |
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