The rise of Artificial Intelligence (AI) combined with blockchain technology is revolutionizing scientific research by addressing longstanding challenges in data integrity.
Improving Data Safety
Blockchain’s power lies in its public ledger, where each added information becomes an irrevocable permanent record. All transactions and data entries are recorded with a time and date cryptographic seal, so records can be relied upon and any changes made are self-evident. Blockchain integration is necessary for the trustworthiness of research data and helps with reproducibility. For example, Microsoft’s study, Sharing Updatable Models (SUM) on Blockchain, aimed to explore how decentralized systems can facilitate the secure and transparent updating of machine learning models. The researchers developed a framework in which machine learning models could be constantly improved while ensuring all updates were recorded immutably on a blockchain. This approach keeps tampering away, maintains an auditable history of model updates, and guarantees that data records are always trustworthy throughout the process.
Improving Contribution to Research through Decentralization
Both blockchain and AI add something unique to scientific exploration. AI improves data analysis with the identification of patterns, automatic processing, and enhanced decision-making, whereas blockchain ensures data security, integrity, and transparency through a decentralized and permanent ledger. Together, the technologies enable research platforms to be decentralized where data, models, and findings are securely exchanged regardless of a central controlling power.
A notable example of this is Sahara AI, which is a project that uses blockchain to form tokenized, decentralized networks of AI. This process enables users to build and sell AI models and datasets in a trustless environment, having contributions stored immutably and access granted transparently. By combining the analytical power of AI with the secure network of blockchain, platforms such as Sahara AI build an open collaboration while maintaining data ownership and integrity.
Streamlining Research Processes with Smart Contracts
Smart contracts - self-executing contracts with terms encoded directly into computer code - may automate much of research administration. They may regulate intellectual property rights, release grant funding based on predetermined milestones, and manage data access permissions. Such automation removes administrative burdens and ensures that agreements are enforced openly. For example, the application of smart contracts in research can facilitate automatic release of funds on achievement of specific research milestones, thereby improving efficiency and confidence among stakeholders.
Ensuring Ethical AI Development
Blockchain ensures transparent records of training data, algorithms, and decision-making processes in AI development by tracking metadata such as data sources and version changes. Transparency ensures accountability and facilitates the auditing of AI systems to prevent biases and unethical actions. A paper titled "Is Your AI Truly Yours? Leveraging Blockchain for Copyrights, Provenance, and Lineage" describes how blockchain can be utilized to keep the provenance and history of ownership of AI models intact such that they are created and utilized ethically.
Challenges and Future Directions
While the union of blockchain and AI is promising, many issues like scalability and energy consumption persist. Research and development continue to work on these issues to unlock the full potential of this convergence in revolutionizing research collaboration.
In short, the convergence of blockchain and AI technologies is ushering in a more collaborative, secure, and efficient research space. With these technologies, the scientific community can break through existing barriers and set the pace of innovation.
References
https://www.microsoft.com/en-us/research/project/decentralized-collaborative-ai-on-blockchain https://saharalabs.ai/
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Winston Wong (article author) is a Business student at Western University and is a myLaminin intern in the University's WMA program.
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