Hawzah News Agency- In a keynote address at the second session of the “Artificial Intelligence and Digital Quranic Studies” series, organized by the Computer Research Center of Islamic Sciences (Noor Center) at the Tehran International Quran Exhibition, Hojatoleslam Dr. Seyed Saeed Reza Ameli, head of the Faculty of World Studies at the University of Tehran and member of the Supreme Council of the Cultural Revolution, explained how Quranic modes of reasoning could guide the development of AI systems with normative independence.
“The Quran provides structured patterns of thought that can inspire novel cognitive models, enabling artificial intelligence not only to process information but to ‘understand’ in a manner aligned with ethical and conceptual frameworks,” Dr. Ameli said.
Human Neural Networks and AI: Two Paths to Quran-Inspired Intelligence
Dr. Ameli discussed the parallels between the human neural network and the artificial neural network, highlighting two approaches for integrating AI with Quranic knowledge.
1. Data Analysis Approach: AI can serve as a powerful tool to analyze Quranic content, uncovering conceptual links, statistical patterns in vocabulary, structural features of surahs, and latent textual patterns. With the growing capacity of databases in Quranic and Hadith studies, such computational exploration is increasingly feasible.
2. Cognitive Inspiration Approach: A deeper and more forward-looking strategy seeks to identify patterns within the Quran that AI can emulate to generate new models—particularly linguistic and cognitive models. Quranic concepts such as “understanding”, “knowledge”, “reasoning”, “reflection”, and “contemplation” provide algorithmically rich domains for AI development.
“This approach goes beyond mere data analysis,” Dr. Ameli explained. “It seeks to simulate the fundamental laws and reasoning patterns that govern reality as articulated in the Quran: ‘Indeed, this Quran guides to that which is most upright’ (Al-Isra, 9).”
Modeling Thought and Reasoning in AI
Dr. Ameli proposed that Quranic concepts like thinking can be translated into iterative optimization algorithms. In traditional exegesis, thinking is a dynamic movement from known knowledge to unknown truths, relying on repeated engagement with initial information to uncover insights. In AI, this mirrors iterative algorithms that adjust internal weights step by step to reach an optimal solution.
“The continuity and feedback inherent in thinking align closely with the iterative optimization processes of artificial intelligence,” he noted. “This is not a superficial analogy—it reflects a structural equivalence expressed in mathematical language. AI can, therefore, be trained to think according to these principles.”
Reasoning and Normative Constraints
Dr. Ameli described reasoning as more complex than thinking because it involves self-regulation and alignment with ethical principles. The Quran emphasizes mastery over desires to remain on the path of reason. Similarly, AI models can drift if they maximize statistical probabilities without normative or ethical constraints. By embedding secondary Quranic principles as constraints in AI learning processes, models can approach reasoning while avoiding unethical or inaccurate outputs.
Reflection for Normative Independence
The scholar also highlighted reflection as a conceptual model that encourages long-term awareness and foresight, comparable to multi-step dependencies and temporal modeling in AI. By using Quranic structures of truth and coherence, AI can achieve normative independence, preventing it from becoming a mere imitator of training data.
“Reflection provides a framework for AI to assess knowledge within a stable truth-based structure,” Dr. Ameli explained. “It enables machines to reason independently while remaining anchored in ethical and cognitive foundations.”
Two Stages of the Digital Revolution
Dr. Ameli concluded by outlining the two stages of the digital revolution:
- Datafication: Converting information into structured, analyzable data, which many countries have achieved.
- From Data to Understanding: Transforming data into actionable understanding and performance—an area where Quran-inspired AI could play a transformative role.
The session drew wide interest from scholars and technologists interested in the intersection of Islamic sciences and artificial intelligence. It concluded with a Q&A session, where Dr. Ameli addressed practical challenges and the future prospects of AI systems modeled on human-like neural architectures guided by Quranic reasoning.
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