Decentralized AI is key to more unbiased AI algorithms — Masa co-founder

As someone who has closely followed the developments in artificial intelligence (AI) and its potential implications, I firmly believe that decentralized AI is a crucial step forward for creating safer and unbiased AI algorithms. The experiences we’ve had with centralized AI solutions have shown us that they can lead to significant inaccuracies and biases, as seen in instances like Google’s image generator.

Developing artificial intelligence (AI) decentrally is important for creating safer and more impartial AI systems. This means that instead of having a single, centralized entity controlling the development of AI, it is distributed among various entities or individuals. By doing so, we can reduce the risks of bias and ensure greater safety in AI algorithms.

Decentralized AI solutions, as opposed to their centralized counterparts, are expected to play a significant role in developing more transparent and impartial artificial intelligence systems, according to Calanthia Mei, the co-founder of Masa Network. Mei shared this perspective during an interview with CryptoMoon.

“Decentralized AI attempts to address the existential flaws in AI, ensuring a more unbiased and safer AI.”

The founder highlighted the primary advantages of decentralized AI on the blockchain: clearer decision-making processes due to transparency, stronger data protection, and user-controlled models that empower individuals to share their data or computing power for reward in the form of tokens.

I’ve noticed that some widely used centralized AI models have generated inaccuracies and sparked social media backlash in the past. For instance, in February, Google had to take down its AI image generator due to historically inaccurate and controversial images it produced. This incident raised serious questions about the decision-making process of these advanced technologies.

“Decentralized AI is essential for overcoming bias in algorithmic outputs, such as that encountered with Gemini AI. This is achieved by fostering greater transparency in the decision-making processes of these algorithms,” Mei explained to CryptoMoon.

“Centralized AI amplifies pre-existing power imbalances, privacy concerns and biases at an unprecedented pace, as exemplified by the Google Gemini AI incident where the AI depicted U.S. founding fathers as people of color, possibly as an overcorrection to long-standing racial bias problems in AI.”

Using a blockchain and decentralized AI protocol ensures data origin transparency for AI results. This transparency is essential because an AI’s quality depends on its training data. As stated by Mei, “An AI’s effectiveness relies heavily on the data it is given to learn from.”

“The quality, diversity and representativeness of the data directly influence the performance and fairness of AI systems. Biased or limited data can lead to skewed and biased results, compromising the reliability of AI-driven decisions.”

Masa Network is among the largest decentralized AI data and large language model protocols aiming to offer more reliable data to AI applications.

Approximately 1.58 million distinct wallets have shared their personal information with Masa Network as reported by Dune.

Decentralized AI is key to more unbiased AI algorithms — Masa co-founder

On April 25, Masa Network announced the initial 13 AI development partners working on their platform, which is based on decentralized infrastructure. To support these builders in expanding the potential of decentralized AI, Masa Network has allocated $100,000 worth of MASA tokens for this purpose.

On April 11, the mainnet went live for the network along with its MASA token, marking the beginning of operations. Among the initial 13 projects under Masa’s umbrella are CharacterX, a decentralized social media platform, Pond, which is a graph AI model designed for on-chain trading, and RootData, an intelligent data infrastructure tailored for Web3 applications.

Read More

2024-04-25 17:05