Blockchain for Business: Next-Generation Enterprise Artificial Intelligence Systems

Abstract

Abstract This chapter discusses Blockchain distributed ledgers in the context of public and private Blockchains, enterprise Blockchain deployments, and the role of Blockchains in next-generation artificial intelligence systems, notably deep learning Blockchains. Blockchain technology is a software protocol for the secure transfer of unique instances of value (e.g., money, property, contracts, and identity credentials) via the Internet without requiring a third-party intermediary such as a bank or government. Public Blockchains such as Bitcoin and Ethereum are trustless (human counterparties and intermediaries do not need to be trusted, just the software) and permissionless (open use), whereas private Blockchains are trusted and permissioned. Enterprise Blockchains are private (trusted, not trustless) immutable decentralized ledgers, with varying methods of reaching consensus (validating and recording transactions). Four enterprise systems are examined: R3’s Corda, Ethereum Quorum, Hyperledger Fabric, and Ripple. New business analytics and data science methods are needed such as next-generation artificial intelligence solutions in the form of deep learning algorithms together with Blockchains. The hidden benefit of Blockchain for data analytics is its role in creating “clean data”: validated, trustable, interoperable, and standardized data. Business Blockchains may develop across industry supply chains with shared business logic and processes, and shared financial ledgers. Payment channels and smart contract asset pledging may allow net settlement across supply chains and reduce debt and working capital obligations. Specific use cases are considered in global automotive supply chains, healthcare, digital identity credentialing, higher education, digital collectibles (CryptoKitties), and asset tokens (Primalbase).