The fourth Party to the Dispute.
Based on new legal technologies (LawTech), such as artificial intelligence (AI), Internet of Things (IoT) and Blockchain.
Predictive or Quantitative Justice where assessments are made of probability for success/failure, strategy and outcome before a particular tribunal.
Equator AI Blockchain technology removes the need to have a trusted third party, for example by acting as custodian or escrow agent for records or assets and thereby creating transparency.
Equator AI designs the system on the following inputs. Such inputs are different for different countries, types of disputes etc.
Case-based Reasoning—a form of so-called expert systems that bases decision-making on prior case experience, instead of on a pre-defined rule set.
Machine Learning—is a type of AI program with the ability to learn without explicit programming, and can change when exposed to new data. Subdivisions include
Supervised learning—is the task of inferring a function from labelled training data, where training data consist of a set of training examples.
Unsupervised learning—is the task of inferring a function to describe hidden structure from unlabelled data.
Equator justice delivery services include natural language processing (NLP) and sentiment analysis:
NLP—the application of computational techniques to the analysis and synthesis of natural language and speech.
Sentiment analysis—the process of computationally identifying and categorising opinions expressed in a piece of text.
The Key attributes
For Equator AI justice delivery blockchains, the key attributes are
(a) Resilience—blockchains operate as decentralised networks as opposed to a central server with a single point of failure;
(b) Integrity—blockchains operate using distributed open-source protocols removing the need to trust a third party for execution;
(c) Transparency—public blockchains have inherent transparency features, since all changes are visible by all parties; and
(d) Unchangeable—records in a distributed public blockchain are largely ‘immutable’, allowing applications and users to operate with a good degree of confidence.
The core technologies
Artificial Intelligence (AI)—
systems able to perform tasks normally requiring human intelligence.
Big Data Analytics—
the analysis of large and varied data sets to uncover hidden patterns, unknown correlations, customer preferences, etc. to help make informed decisions
technology underpinning digital currencies and transactions that secures, validates and processes transactional data.
As we know, AI provides computers with the ability to make decisions and learn without explicit programming. There are two main branches:
Knowledge-based systems (KBS)—are computer programs that reason, and knowledge is explicitly represented as ontologies or rules rather than implicitly via code. KBS can be subdivided into
Rule-based systems—is one whose knowledge base contains the domain knowledge coded in the form of IF-THEN or IF-THEN-ELSE rules.
Big Data Analytics and Argumentation
Another influential technology is ‘argumentation’. In AI and related fields, argumentation is a way of dealing with contentious information and draws conclusions from it. Interestingly, argumentation is used in law, for example in trials, in preparing an argument to be presented to a court, and in testing the validity of certain kinds of evidence.
Efforts have been made within the field of AI to perform and analyse the act of argumentation with computers. Computational argumentation systems have found particular application in domains where formal logic and classical decision theory are unable to capture the richness of reasoning, domains such as law and medicine.
The combination of key attributes as set out above allows blockchain to introduce trust to all transactions and is therefore viewed as integral to any algorithmic dispute resolution platform.
Elements of blockchain technology originally conceived for Bitcoin and other cryptocurrencies are now recognised to have far-reaching potential in other areas. Blockchains are a way to order transactions in a distributed ledger, a record of consensus with a cryptographic audit trail maintained and validated by multiple nodes. Blockchain technology allows many distrusting parties to converge on a common protocol that can track assets in a dynamic fashion. Using this technology, many processes and third-party solutions are streamlined or collapsed entirely. The core technologies are
Distributed Ledger (DL)—a decentralised database where transactions are kept in a shared, replicated, synchronised, distributed bookkeeping record, which is secured by cryptographic sealing. The key distinction between ‘distributed ledgers’ and ‘distributed databases’ is that nodes of the DL cannot/do not trust other nodes—and so must independently verify transactions before applying them.
Smart Contracts—are simply the rules that participants have collectively signed up to that govern the evolution of the ‘facts’ in the distributed ledger. Possibly computer programs that attempt to codify transactions and contracts with the intent that the records managed by the distributed ledger are authoritative with respect to the existence, status and evolution of the underlying legal agreements they represent.