We assume that Western theory and practice of artificial intelligence are poorly defined and, consequently, poorly applied and sometimes misleading.

Figure 1 below illustrates how this theory is poorly defined and poorly applied.

Dear Ismail Abbas M. Abbas ,

Let's put it that AI is AI no matter where, so in that same lane, Western artificial intelligence (AI) theory and practice, while highly advanced, face several fundamental challenges and criticisms, particularly concerning bias, ethical oversight, commercial interests, and epistemological limitations.

AI models often reflect systemic biases due to training on datasets that lack diversity, leading to discriminatory outcomes in areas like hiring, policing, and healthcare. Additionally, AI development is largely driven by corporate interests, prioritizing profit over social good, which raises concerns about privacy, monopolization, and public accountability. The prevailing focus on narrow, data-driven intelligence results in systems that excel in pattern recognition but lack contextual reasoning, causality, and human-like understanding.

Moreover, Western AI prioritizes full automation over human augmentation, fueling fears of job displacement and economic inequality instead of fostering AI as a collaborative tool. Geopolitically, Western AI frameworks often dominate the global discourse, marginalizing non-Western languages, ethical perspectives, and alternative cognitive models, reinforcing digital colonialism. Addressing these issues requires a shift toward ethically pluralistic, globally inclusive, and human-centered AI development, ensuring AI serves broader societal needs rather than reinforcing power imbalances.

We must put an end to the current chaos surrounding artificial intelligence.

Everyone is creating a learning database, for example by imitating or modeling human behavior in certain situations, thus claiming to provide a form of global AI.

By the end of 2025, we will have thousands of different types of global AI, with no possible logical classification.

Deep learning, machine learning, chatGPT, image processing, etc. are not artificial intelligence, but we call them a form of storage intelligence.

*In short,

Cairo Intelligence Techniques = Natural Intelligence = Concrete and Narrow Artificial Intelligence = Unified Field Theory.