Generative AI (IAG)
Systems generating novel content (text, images, audio, code).
How the laws define this
Both regulatory instruments agree that Generative AI (IAG) consists of systems or models trained on data to generate or create novel content, specifically highlighting formats such as text, images, audio, and code. However, they diverge significantly in their regulatory focus and context. Under Decreto 2726/2025 – Protocolo para la Adopción y Uso de Tecnologías de Inteligencia Artificial Generativa en la Administración Pública (Provincia de Santa Fe), the concept is narrowed to govern downstream deployment within public administration, framing these technologies as non-binding assistive tools subject to usage rules, risk classification, transparency obligations, and mandatory human validation. Conversely, Provvedimento n.329 (20 May 2024) - Nota informativa su web scraping per finalità di addestramento di intelligenza artificiale generativa (Garante per la protezione dei dati personali) applies the term upstream to the data collection phase, using it to frame the types of AI systems for which large-scale scraped datasets are assembled for training purposes.
Synthesised from the 2 statutory definitions below. Each one is quoted in full, with its source.
Definitions (2)
Generative AI (IAG) denotes AI systems whose primary function is to create novel content (text, images, audio, code) based on training data; treated by the Protocol as assistive tools whose outputs are non‑binding and require human validation. The definition narrows the category for purposes of usage rules, risk classification and transparency obligations within the public administration.
Models and systems trained on large-scale datasets to generate new content (text, images, code, audio, etc.); in the note, this term frames the types of AI systems for which scraped datasets are often assembled.
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