A Review of Multimodal Artificial Intelligence: Ethical Challenges and Practical Benefits in Content Generation
DOI:
https://doi.org/10.46842/ipn.cien.v29n2a08Keywords:
Multimodal AI, AI-generated content, Ethical challenges, Automation EfficiencyAbstract
This systematic review examines 23 peer‑reviewed studies published since 2020 to delineate the principal technical and ethical risks, synthesize key benefits, and identify future research avenues for AI‑driven multimodal content creation. Employing a PRISMA‑guided protocol, we screened five major digital libraries and applied rigorous inclusion/exclusion criteria alongside an adapted CASP checklist, yielding a final corpus that spans visual art, education, marketing, healthcare, disaster response, architectural design, communication, and sports entertainment. We classified these works into four functional categories, Creation and Design, Communication and Analysis, Automation and Detection, and Interaction and Teaching, and quantified their emphases: 30 % of studies prioritized automation efficiency, 26 % highlighted personalized outputs, and 18 % reported enhanced content diversity. Crucially, our review also catalogs significant risks, misinformation, modality‑alignment failures, algorithmic bias, and privacy breaches, underscoring the need for transparent algorithms, bias‑monitoring protocols, and privacy‑by‑design frameworks. We conclude by advocating the development of interpretable models, standardized ethical data‑handling methodologies, and real‑time mitigation tools, as well as interdisciplinary collaborations to advance robust, responsible, and scalable multimodal AI systems.References
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Copyright (c) 2025 German Cuaya Simbro, Wendy Garcia Tapia, María F. Avila Vargas, Pedro Aarón Hernández Ávalos (Autor/a)
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