Blockchain Is Key to Data Transparency, but Just One Piece of the DeSci Tech Puzzle

• Decentralized Science (DeSci) poses an alternative to traditional research.
• The emerging DeSci technology stack incorporates blockchains and zero-knowledge proofs.
• Enhanced transparency and verifiability can help prevent academic fraud.

In recent years, the notion of decentralized science (DeSci) has emerged as a promising solution to some of the systemic challenges facing traditional scientific research.

Rooted in decentralized technologies, DeSci aims to democratize the research process, enhance transparency, and tackle challenges like academic fraud and paywalled knowledge.

The concept of decentralized science has roots in the broader decentralization movement championed by blockchain enthusiasts in the early 2010s.

While blockchains were initially associated with cryptocurrencies, like Bitcoin (BTC), their potential applications in other fields became evident with the rise of dynamic smart contract platforms, like Ethereum (ETH).

By 2018, the term DeSci began gaining traction as innovators recognized that decentralization could address some of the inefficiencies and inequities that plague the traditional scientific research process.

Notable Projects and Protocols

Several pioneering projects are leading the DeSci revolution.

For research funding, platforms like BIO Protocol, Molecule and VitaDAO present an alternative to the centralized, institutional system of grants and awards.

Discussing his hopes for the future of decentralized funding mechanisms, Professor David M. Wilson III, who serves as VitaDAO Advisor, explained: 

“I think decentralized funding simply provides everyone a chance to be a part of not only the drug development process but of the associated profits. It’s just one more piece of the puzzle to help facilitate the discovery of new therapies and interventions. Given the broad skepticism in today’s society, it provides a real opportunity for those that are motivated, by whatever reason, to get involved and experience first-hand the process of pharmaceutical discovery.”

Meanwhile, when it comes to scientific collaboration and resource sharing, projects, including LabDAO and the Open Science Framework, leverage decentralized networks to broaden access to data, knowledge and tools.

The New Norms of AI Research

From data collection to publication, blockchain-based DeSci solutions provide an immutable record of research activities. This transparency makes it harder to manipulate or falsify results, a problem that erodes trust in scientific findings.

The challenge is especially prominent in AI development, where commercial interests and a growing culture of secrecy have reshaped a research tradition that was traditionally committed to transparency and open-source code.

According to computer scientist Tiancheng Xie, although there are thousands of AI research papers published each year, the majority of the results can’t be verified, “either because it’s closed source or they have some private data that they don’t want to share.”

As such, a lot of AI research lacks the repeatability necessary for scientific rigor, undermining the process of peer review and increasing the risk of academic fraud, he explained.

“They are just claiming that my model or my algorithm gets performs well without reproducibility, so other people cannot verify that claim,” said the scientist.

Beyond Blockchain

While blockchains can increase data transparency, they aren’t the only component of the emerging DeSci technology stack.

For example, Xie’s research focuses on zero-knowledge (ZK) proofs, which he argued could solve the challenge of verifying results without compromising commercial secrets.

For now, the concept is mostly theoretical, he observed. But through the work of initiatives like Polyhedra Network, the combination of ZK proofs and blockchains is helping increase verifiability in AI development.