Limitations of Traditional AI in Education

Despite technical advances, current AI solutions have several limitations in addressing global educational challenges:

Limitations of Centralized Structures

• Scalability Challenges: Centralized control of AI models by a single entity introduces bias in data and decision-making, limiting adaptability to diverse user needs and posing significant barriers to global scalability.

• Data Sovereignty Issues: Centralized AI systems raise data sovereignty and privacy concerns, especially as educational data reveals sensitive insights into personal growth and achievement.

• Difficulty Localizing: A single AI model struggles to accommodate diverse educational systems, cultural contexts, and linguistic characteristics needs, as centralized decision-making restricts the creation of region-specific solutions.

Constraints on Innovation and Value Distribution

• Innovation Barriers: Closed systems limit participation from diverse educational experts, small startups, and individuals, slowing the advancement of educational AI development.

• Unequal Value Distribution: In the educational ecosystem, contributors such as data providers, creators, and teachers often lack fair compensation, while benefits remain concentrated among a few entities.

• Commercialization Bias: Development efforts prioritize commercially attractive education sectors, sidelining socially important but less commercial domains.

In response to these challenges, XIIID proposes a blockchain-based decentralized AI platform to achieve global scalability, foster innovation, and ensure equitable value distribution.