Despite significant progress in machine translation, Arabic remains a formidable challenge for AI systems. This article explores the linguistic complexities that make Arabic particularly difficult for automated translation.
Root-Based Morphology
Arabic's tri-consonantal root system forms the foundation of its lexicon. A single root can generate numerous words, each with distinct but related meanings. For instance, the root k-t-b (ك-ت-ب) produces words like:

kataba (كَتَبَ) - he wrote
kitāb (كِتَاب) - book
maktab (مَكْتَب) - office
kātib (كَاتِب) - writer

This intricate system requires AI to grasp complex morphological relationships.
Affixation and Infixation
Arabic employs prefixes, suffixes, and infixes to modify words and convey grammatical information. Consider these variations of "travel":

sāfara (سَافَرَ) - he traveled
yusāfiru (يُسَافِرُ) - he travels/is traveling
musāfir (مُسَافِر) - traveler
sa'usāfiru (سَأُسَافِرُ) - I will travel

Accurate translation demands precise identification and interpretation of these elements.
Plural Formation
Arabic features both regular and broken plurals. Broken plurals involve internal word structure changes:

kitāb (كِتَاب) / kutub (كُتُب) - book / books
qalam (قَلَم) / aqlām (أَقْلَام) - pen / pens

This variability poses challenges for consistent AI-generated translations.
Grammatical Gender Agreement
Arabic enforces grammatical gender agreement across nouns, adjectives, and verbs:

al-waladu aṣ-ṣaghīru nāma. (الولد الصغير نام.) - The small boy slept.
al-bintu aṣ-ṣaghīratu nāmat. (البنت الصغيرة نامت.) - The small girl slept.

This level of agreement, absent in English, significantly impacts translation accuracy.
Additional Complexities

Case system (nominative, accusative, genitive)
Dual form for pairs
Multiple verb forms (up to 15 per root)
Phonetic changes in the definite article "al-"

These linguistic features create a multifaceted challenge for machine translation. Accurate English-to-Arabic translation requires not only conveying core meaning but also navigating intricate grammatical and morphological aspects.
Conclusion
The complexities of Arabic—its root-based morphology, intricate affixation system, diverse plural forms, and strict grammatical agreements—present significant hurdles for AI translation. While current AI systems struggle with these nuances, the field is rapidly evolving. Future advancements in machine learning and natural language processing may eventually overcome these challenges.
However, the depth and subtlety of Arabic linguistics underscore the continued importance of human expertise in translation. As AI capabilities grow, the role of human translators is likely to shift towards fine-tuning, contextual interpretation, and handling the most nuanced aspects of language.
Looking ahead, the most effective approach to Arabic translation will likely involve a synergy between AI and human translators. This collaboration has the potential to combine the efficiency and consistency of machine translation with the cultural awareness and linguistic intuition of human experts, ultimately leading to more accurate and nuanced translations of this rich and complex language.

Khaled Hassan (Halit HASANOGLU)