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ORIGINAL RESEARCH article

Front. Comput. Sci.
Sec. Human-Media Interaction
Volume 6 - 2024 | doi: 10.3389/fcomp.2024.1459807
This article is part of the Research Topic Artificial Intelligence: The New Frontier in Digital Humanities View all 4 articles

An Ethical Framework for Trustworthy Neural Rendering applied in Cultural Heritage and Creative Industries

Provisionally accepted
Lorenzo Stacchio Lorenzo Stacchio 1Emanuele Balloni Emanuele Balloni 2*Lucrezia Gorgoglione Lucrezia Gorgoglione 2Adriano Mancini Adriano Mancini 2Benedetta Giovanola Benedetta Giovanola 1Simona Tiribelli Simona Tiribelli 1Primo Zingaretti Primo Zingaretti 2
  • 1 University of Macerata, Macerata, Italy
  • 2 Marche Polytechnic University, Ancona, Italy

The final, formatted version of the article will be published soon.

    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.

    Keywords: artificial intelligence, Neural rendering, Neural Radiance Fields, 3D Gaussian Splatting, Ethics

    Received: 04 Jul 2024; Accepted: 20 Sep 2024.

    Copyright: © 2024 Stacchio, Balloni, Gorgoglione, Mancini, Giovanola, Tiribelli and Zingaretti. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Emanuele Balloni, Marche Polytechnic University, Ancona, Italy

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