The convergence of AI and Blockchain: what’s the deal? - Part I
By Francesco Corea, Ph.D. | May 21, 2018
Columnist Francesco Corea is a Complexity Scientist, Tech Investor, Data Strategist and AI Advisor
It is undeniable that AI and blockchain are two of the major technologies that are catalyzing the pace of innovation and introducing radical shifts in every industry. Each technology has its own degree of technical complexity as well as business implications but the joint use of the two may be able to redesign the entire technological (and human) paradigm from scratch.
This article aims to give a flavor of the potentialities realized at the intersection of AI and Blockchain and discuss standard definitions, challenges, and benefits of this alliance, as well as some interesting players in the space.
I. Setting the stage
However, I haven't touched upon blockchain and cryptocurrencies so far, so I will dedicate this first block to describe what it is and how it works.
A blockchain is a secure distributed immutable database shared by all parties in a distributed network where transaction data can be recorded (either on-chain for basic information or off-chain in case of extra attachments) and easily audited.
Put simply (with Bank of England’s words), the blockchain is “a technology that allows people who don’t know each other to trust a shared record of events”.
The data are stored in rigid structures called blocks, which are connected to each other in a chain through a hash (each block also includes a timestamp and a link to the previous block via its hash). The blocks have a header, which includes metadata, and content, which includes the real transaction data. Since every block is connected to the previous one, as the number of participants and blocks grow, it is extremely hard to modify any information without having the network consensus.
The network can validate the transaction through different mechanisms, but mainly through either a “proof-of-work” or a “proof-of-stake.” A proof-of-work (Nakamoto, 2008) asks the participants (called “miners”) to solve complex mathematical problems in order to add a block, which in turn require a ton of energy and hardware capacity to be decoded. A proof-of-stake (Vasin, 2014) instead tries to solve this energy efficiency issue attributing (roughly) more mining power to participants who own more coins (there are many variations of it and some skepticism around its famous “nothing at stake” problem — see Buterin’s blog post to understand more on this).
Additional mechanisms are the Byzantine-fault-tolerant algorithm (Castro and Liskov, 2002), the Quorum slicing (Mazieres, 2016), as well as variations of the proof-of-stake (Mingxiao et al., 2017), but we will not get into those now.
The final characteristic that needs to be explained is the category of blockchain based on the different network access permission, i.e., whether it is free for anyone to view it (permission less vs. permissioned) or to participate in the consensus formation (public vs. private). In the former case, anyone can access and read or write data from the ledger, while in the latter one, predetermined participants have the power to join the network (and of course only in the public permission less case, a reward structure for miners has been designed).
It should be clear by now the intrinsic power of this technology, which is not simply a disruptive innovation but rather a foundational technology that aims to “change the scope of intermediation” (Catalini and Gans, 2017). Distributed ledger technologies will indeed reduce both the costs of verification and networking, influencing then the market structure and eventually allowing the creation of new marketplaces. Iansiti and Lakhani (2017) also drew a brilliant parallel between blockchain and TCP/IP in a recent work (which I highly recommend), showing how blockchain is slowly going through the four phases that identify previous foundational technologies such as the TCP/IP, i.e., single-use, localized use, substitution, and transformation. As they explained, the “novelty” of such a technology makes it harder for people to understand the solution domain, while its “complexity” requires a larger institutional change to foster easy adoption.
However, it is also true that blockchain is shifting the traditional business models distributing value in an opposite way with respect to previous stacks: if it made more sense to invest in applications rather than protocol technologies fifteen years ago, in a blockchain world the value is concentrated in the shared protocol layer and only marginally at the application level (see the “Fat Protocol” theory by Joel Monegro).
To conclude this introductory section, I will just mention on the fly the possibility for the blockchain to not simply allow for transactions but also the possibility to create (smart) contracts that are triggered by specific events and threshold that are traceable and auditable without effort. Stay tuned; more to come.
Series: The convergence of AI and Blockchain: what’s the deal?
This series was originally published in December, 2017 on Medium and will appear in a forthcoming book edited by Spriger (2019).