What is Blockchain’s Potential for Managing Data, Compute, and Models for AI?
Rapidly evolving AI, and humans’ experience with it, unearths a litany of economic and societal issues related to intellectual property rights, individual privacy, transparency, security and other ethical pillars on a continuous basis.
The convergence of blockchain and artificial intelligence (AI) may be a very promising opportunity for groundbreaking advancements in AI data management, computation, and model distribution related to the critical economic and societal issues. As people become increasingly better at using AI and adoption increases, the need for secure, transparent, and efficient systems to manage data, compute resources, and AI models has never been more pressing.
Blockchain technology, which offers a decentralized and immutable ledger system, holds immense potential for revolutionizing how we handle AI-powered technologies, systems, and processes. Renowned to date for its role in enabling cryptocurrencies like Bitcoin, is essentially a distributed ledger system that records transactions across a network of computers. Each transaction is encrypted, time-stamped, and linked to the previous one, creating a chain of blocks that cannot be altered retroactively. This inherent transparency and security make blockchain an ideal solution for managing sensitive data and ensuring the integrity of AI models and computations.
Smart contracts are digital contracts stored on a blockchain that are automatically executed when predetermined terms and conditions are met. They are an invaluable feature of blockchain and provide a reliable framework for distributing and monetizing AI models.
By leveraging smart contracts, AI assets can be securely marketed and distributed to users while ensuring fair compensation to their owners. This opens up new avenues for monetization and collaboration in the AI ecosystem, empowering investors, developers, and users with a means to manage their intellectual property, private and public data, and compute resources. This also creates avenues for commercialization that don’t exist today, and which can stimulate innovations and contribute to the further advancement of AI technologies.
A solution to big data and compute resource challenges
One of the key challenges in AI development is the infrastructural governance and management of vast amounts of data. Traditional centralized systems often struggle with issues such as data silos, privacy concerns, and data ownership disputes. Blockchain’s decentralized nature offers a solution, enabling secure data sharing and collaborative model training while safeguarding privacy through techniques like homomorphic encryption and zero-knowledge proofs. By leveraging blockchain, AI researchers gain access to diverse datasets without compromising data security or ownership, fostering a collaborative ecosystem conducive to innovation.
Blockchain technology also facilitates the efficient allocation and utilization of compute resources for AI tasks. Cryptocurrency investors have already begun investing in the development of blockchain-based platforms that provide access to a decentralized network of computing power, eliminating the need for expensive hardware investments and reducing computational bottlenecks. This democratization of compute resources enables greater scalability and flexibility in AI development, allowing researchers and organizations to tackle complex problems with ease.
AI is becoming increasingly integrated into technologies at the edge of networks, in contrast to a centralized cloud location where many of today’s AI applications run. For this reason, blockchain is a natural complement given its fully decentralized nature that puts data, compute, and models all within the edge devices and connected through the internet of things (IoT).
Users want their AI to provide personalized, private, and integrated experiences with the growing number of these technologies that are always or often by our side. Blockchain will allow them to have that.
Despite this immense potential, the integration of blockchain with AI is not without its challenges. Scalability, interoperability, and regulatory concerns are among the key hurdles that must be addressed to realize the full benefits.
However, with ongoing investment in research and development efforts, these challenges can be overcome, and pave the way for a future where blockchain-governed AI systems drive greater access, collaboration, and innovation across society.
–Michael A. Cohen