Disclosure: The views and opinions expressed here belong solely to the author and do not represent the views and opinions of crypto.news’ editorial. As AI is changing industries, data is more important than ever. But here’s the thing: the centralized systems we use today come with big ethical problems. From privacy breaches to monopolistic control, centralized data collection is a world of mistrust and opacity. You might also like: Governance, rewritten: DeAIOs go for decision-making without human limits | Opinion If we really want AI to be ethical and transparent, we need a new way. That’s where decentralized AI comes in—a game changer for collecting, managing, and using data ethically and fairly. Centralized systems have been the backbone of AI. Big companies hoard huge amounts of data to train their algorithms, but often with little transparency. This creates big problems. For one, privacy takes a hit. Think of all those data breaches you’ve heard about—like the Facebook-Cambridge Analytica scandal . These breaches expose the weaknesses of centralized systems and leave users with no control over their own data. Then there’s the concentration of power. A few tech giants hold the keys to most of the data and can, therefore, control AI innovation and shut out smaller players. This stifles creativity and puts a lot of decision-making power in the hands of a select few. Also, let’s not forget the dodgy data practices hidden in the fine print. Most users have no idea how their data is being collected or used, and so trust in the whole system erodes. Decentralized AI Decentralized AI turns this on its head. Instead of one entity controlling everything, it distributes power and responsibility across many. Using blockchain, federated learning, and edge computing, decentralized AI gives control back to the people whose data is being used. It’s simple: be transparent, protect privacy, and let people own their data. Blockchain creates a digital record that can’t be changed, so you always know how your data is being used. Federated learning means AI systems can train on your data without ever storing it in a central location, so your info is private. Of course, moving to a decentralized model isn’t without its challenges. The tech is complex and requires robust infrastructure. Because the regulatory landscape around decentralized systems is still evolving, it can be hard for businesses to know how to proceed. Adoption is another hurdle; many people and organizations are reluctant to leave behind the familiar centralized systems they are used to. Despite the hurdles, the potential is huge. To make it happen, we need collaboration between governments, industries, and innovators. Governments can help by creating laws that support data ownership and privacy. Companies and researchers need to work together to build the infrastructure and educate people about decentralized AI. Emerging technologies like web3 (a decentralized internet) can also play a big role in making this future possible. A path forward Centralized data collection got us here, but it’s not sustainable. Decentralized AI is a new way forward, one that’s fair, transparent, and empowering. It’s not just the ethical choice; it’s the smart one. The reason we need decentralized AI is the speed of AI growth and its growing impact on society. Every day, algorithms make decisions on healthcare and finance and often use data collected without proper oversight. By acting now, we can make sure AI evolves in a way that benefits everyone, protects individual rights, and unleashes the full power of technological progress. If we make this shift, we can have an AI that works for everyone, not just the privileged few. Now is the time to act. As data is the lifeblood of AI, adopting decentralized systems is our best bet for a trustworthy and transparent technological future. It’s not just about fixing the problems with centralized systems; it’s about rethinking data and technology altogether. Imagine a world where users have full control over their own data, where communities can decide how data is used, and where gatekeepers don’t block innovation. This isn’t just a tech evolution; it’s a cultural one. Decentralized systems match the growing demand for fairness and accountability in the digital age, and we’re seeing that ethical and efficient AI isn’t just possible—it’s inevitable. Read more: The path to AI: Decentralized, embodied, and on-chain | Opinion Author: Max (Chong) Li Max (Chong) Li is the founder and CEO of OORT, a cloud for decentralized AI. He is also a faculty member in the Department of Electrical Engineering at Columbia University. Dr. Li holds over 200 international and US patents and has published many academic papers in top-ranking journals like Proceedings of the IEEE, IEEE Transactions on Information Theory, IEEE Communications Magazine, Automatica, etc. Plus, he is the co-author of the book “ Reinforcement Learning for Cyber-physical Systems .” He serves as a reviewer, committee, and co-chair for most prestigious journals and conferences in blockchain, communications, and control societies.
