Building Trust in AI: The Case for Decentralization

A decade ago, the concept of Bitcoin seemed like a niche experiment, much like the early days of the internet. However, it has now become a central topic of discussion on Capitol Hill. Today, people can invest in Bitcoin through various accounts, and the U.S. has established a Strategic Bitcoin Reserve. The shift in perception of Bitcoin was not accidental; it gained momentum due to its core values of open access, transparency, and distributed control, which provided an alternative when trust in traditional finance was dwindling. A similar pattern is emerging with artificial intelligence. AI is rapidly advancing, but concerns about who controls it are also growing. Many wonder where their data goes when using chatbots, who benefits from it, and why they must sacrifice their privacy. According to a recent Harris poll, 74% of U.S. respondents believe AI would benefit more people if it were not controlled by a few big companies, and 65% do not trust elected officials to guide AI's development. The public is enthusiastic about AI's potential but distrusts those in charge. This trust gap is not new, and Bitcoin addressed it through decentralization. When trust in institutions erodes, the solution is not to introduce more gatekeepers but to build systems that do not require them. Decentralized technologies restore trust by removing human intermediaries, who are often biased, error-prone, or self-interested, and eliminating single points of control. By replacing these flawed gatekeepers with transparent, distributed systems, decentralization offers a more reliable and accountable foundation for trust and confidence, rooted in transparency, resilience, and user-aligned governance. This shift from human-controlled to technologically decentralized systems is what makes trust possible again. Decentralized AI, or deAI, is built, trained, and operated across a distributed network, preventing any single party from controlling the system. DeAI flips the script on traditional AI by empowering users, not corporations. Networks like Bittensor are leading the way by enabling open, permissionless access to AI infrastructure, where anyone can contribute models, computing power, or data. This approach levels the playing field for students, startups, and independent developers who would otherwise be excluded from today's centralized AI giants. Instead of gatekeepers, Bittensor coordinates contributions transparently across a global network, using blockchain to embed trust and reward real value. The result is AI that is more open, resilient, and fair, with incentives based on merit, not monopolies. Voters are ahead of lawmakers in recognizing the benefits of decentralized AI. A Harris poll of 2,000 U.S. adults found that three out of four respondents believe decentralized AI drives more innovation than closed AI, and 71% think it offers stronger protection for personal data. What consumers using AI lack is transparency and control; they want to know they are not just training someone else's profit engine. Policy cannot ignore the importance of infrastructure and ownership in AI development. Even with strong public support, the promise of decentralized AI depends on whether policymakers understand that the structure of a system determines its behavior and outcomes. However, the regulatory conversation around AI is still catching up and often misses the point about how the foundational structure of these systems impacts trust. A centralized model run by a few powerful players is inherently vulnerable, opaque, and exclusionary, ultimately eroding trust. To encourage trust, technological adoption, and innovation, policymakers should prioritize private sector innovation and decentralized development, laying the groundwork for a more open and resilient AI future. Decentralized AI is a forward-looking solution to one of the most urgent challenges of our time: ensuring AI serves the public, not just the powerful. Just as Bitcoin moved from the margins to the mainstream, decentralized AI is quickly becoming the foundation for a more open, secure, and competitive AI ecosystem. The public understands this; now policymakers must catch up. The choice is clear: protect open networks, reward real builders, and defend the freedom to innovate, or hand the future of intelligence to a few corporate gatekeepers. Decentralized AI is not fringe; it is the foundation for a freer, fairer digital future. We must not miss this moment.