Uncovering Politically Driven AI Algorithms in Italian Grammar Education: An Ideological Outcome-Based Study

The advent of artificial intelligence (AI) is reshaping many facets of daily life, including education. As AI technologies become more advanced and accessible, their application in teaching and learning processes has accelerated. However, AI systems are frequently designed with politically influenced algorithms that may impact educational content and outcomes. This study examines the influence of a specific AI system on the teaching and learning of Italian grammar. Through a qualitative approach, it investigates whether AI can deliver standard Italian grammar in its authentic form or if its outputs are significantly altered by these underlying algorithms. This research focuses on MAIA, the first generative and personalized AI system entirely developed in Italy, assessing its capacity to accurately distinguish between masculine and feminine forms in Italian nouns and adjectives. Findings indicate that MAIA’s algorithms modify traditional gender distinctions by implementing “inclusive” grammar rules that lack endorsement from prominent linguistic authorities. By disregarding conventional gender differences and proposing new grammar rules aligned with a left-leaning, progressive societal perspective, the MAIA AI system affects both linguistic proficiency and the cultural development of learners, ultimately challenging foundational grammatical standards for ideological purposes. This study underscores the necessity of human expertise in preserving the integrity of Italian grammar instruction.

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Publication Details

Journal
International Journal of Research and Innovation in Social Science
Published
2025-01-01
DOI
https://doi.org/10.47772/ijriss.2025.9020267
Primary Topic
Second Language Learning and Teaching
Type
article
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article

Uncovering Politically Driven AI Algorithms in Italian Grammar Education: An Ideological Outcome-Based Study

Muhammad Alhakeem Husain, Suhardi Kram, A. De Min, Piermauro Catarinella
International Journal of Research and Innovation in Social Science
Second Language Learning and Teaching
article

Uncovering Politically Driven AI Algorithms in Italian Grammar Education: An Ideological Outcome-Based Study

Muhammad Alhakeem Husain, Suhardi Kram, A. De Min, Piermauro Catarinella
article en

Abstract

The advent of artificial intelligence (AI) is reshaping many facets of daily life, including education. As AI technologies become more advanced and accessible, their application in teaching and learning processes has accelerated. However, AI systems are frequently designed with politically influenced algorithms that may impact educational content and outcomes. This study examines the influence of a specific AI system on the teaching and learning of Italian grammar. Through a qualitative approach, it investigates whether AI can deliver standard Italian grammar in its authentic form or if its outputs are significantly altered by these underlying algorithms. This research focuses on MAIA, the first generative and personalized AI system entirely developed in Italy, assessing its capacity to accurately distinguish between masculine and feminine forms in Italian nouns and adjectives. Findings indicate that MAIA’s algorithms modify traditional gender distinctions by implementing “inclusive” grammar rules that lack endorsement from prominent linguistic authorities. By disregarding conventional gender differences and proposing new grammar rules aligned with a left-leaning, progressive societal perspective, the MAIA AI system affects both linguistic proficiency and the cultural development of learners, ultimately challenging foundational grammatical standards for ideological purposes. This study underscores the necessity of human expertise in preserving the integrity of Italian grammar instruction.

International Journal of Research and Innovation in Social ScienceVol. IX(II)
Openalex Percentile: Top 95%
Second Language Learning and Teaching
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Uncovering Politically Driven AI Algorithms in Italian Grammar Education: An Ideological Outcome-Based Study — Muhammad Alhakeem Husain, Suhardi Kram, et al. · International Journal of Research and Innovation in Social Science (2025) | TGRS Research Map | TGRS