Google’s Gemini AI has recently sparked outrage due to generating historically inaccurate imagery and biased results. The development of decentralized AI could offer a solution to ensure more transparent and unbiased outcomes.

According to Calanthia Mei, co-founder of Masa Network, while centralized AI solutions have been dominant in funding, decentralized alternatives are crucial for creating fairer and more transparent AI systems. Mei emphasizes that decentralized AI aims to rectify inherent flaws in AI, promoting fairness and safety.

Decentralized AI protocols based on blockchain technology offer benefits such as transparent decision-making, improved data privacy, and user-owned models where individuals can contribute data or computing resources in exchange for token rewards.

Past incidents, such as Google's AI image generator producing historically inaccurate and contentious images, highlight the risks of relying solely on centralized AI models. Decentralized AI could mitigate such biases by establishing transparent decision-making processes for algorithms.

Mei underscores that centralized AI exacerbates existing power imbalances and biases, as demonstrated by incidents like the Gemini AI debacle. Decentralized AI, on the other hand, provides transparency in verifying the origin of AI output data, which is critical for enhancing algorithm performance and fairness.

Masa Network, a prominent decentralized AI data and large language model platform, boasts over 1.58 million unique wallets contributing personal data. The network recently revealed its initial 13 AI developer partners, signaling a commitment to advancing decentralized AI capabilities with a $100,000 investment in MASA tokens.

Since its mainnet launch on April 11, Masa Network has attracted projects like CharacterX, a decentralized social network; Pond, a graph AI model for on-chain trading; and RootData, an AI-powered Web3 data layer.