Finding ways to improve efficiencies in a law firm – no matter the size – is a constant battle, but never has it been so important to address than in a COVID world.
Narrow AI/machine learning
Fortunately, this is where ‘lawtech’, or legal tech, can help. Recent developments in ‘narrow artificial intelligence’ or ‘machine-learning technologies’ aim to promote greater efficiency, transparency, and better outcomes for those working in and accessing the justice system.
These developments have been made possible by ‘big data’. Business-intelligence data or (BI) derived from big data and predictive data analysis, together with advanced search technologies that handle natural language queries, are a natural jumping-off point for legal AI, because they are capable of interrogating large data sets quickly and presenting the results in ways that support the decision-making process.
These new technologies very much belong to the ‘narrow AI’ sphere. They are intelligent systems that have been taught, not programmed, to carry out tasks – otherwise known as machine-learning technology.
It is an application of AI where systems are provided with the ability to automatically learn and improve from experience, without being explicitly programmed – a far cry from the adaptable intelligence found in humans, which safely remains within the realms of sci-fi culture, for now!
Augmenting legal services
Lawtech should be considered as a means of augmenting legal services as opposed to replacing them. (No signs of a HAL9000 robo-lawyer just yet.)
From a solicitor’s perspective, positive examples of lawtech in action can:
- Increase efficiency, productivity and growth,
- Reduce workloads and carry out more mundane tasks,
- Liberate more junior lawyers to do more interesting and value-added work,
- Reduce costs, and
- Institutionalise know-how.
From a client perspective it:
- Delivers results faster,
- Increases transparency both from a billing and case-management perspective, and
- Increases satisfaction.
Uptake of lawtech
The uptake in the legal industry appears to have been lower than fintech, martech or medtech. There may be institutional barriers (for example, eCommerce Act prohibitions on digital signatures for certain types of transactions) or some innate conservatism.
From an access-to-justice perspective, it is not always easy for those coming from lower socio-economic backgrounds to get access to the right information on what legal services they need.
In a post-COVID world and, indeed, one that is more technologically driven, lawtech presents a way forward for lawyers to embrace a more agile, client-driven approach to work. With around US$1 billion having been invested in lawtech since 2018, it is an industry that is growing rapidly, and one we need to better explore, and assess what value it can bring to our legal practices.
Health warning
Lawtech should never be seen to be the ‘silver bullet’. Technology in isolation is never the answer.
You should consider assessing the processes already in use within your practice. Then see if there are any lawtech products that could assist or take over some of those processes, from a cost/benefit analysis that makes sense for your practice.
To that end, let us take a look at what lawtech products are out there and what, if any, could be of use to you in your sole-practitioner, small-to-medium, or large-scale law firm.
As a committee, we do not endorse or recommend products, but simply hope to raise awareness of products that we know are being used in this space right now. We would always recommend that you try and speak to another lawyer who is already using the technology, and the software provider should be able to assist in this.
You still need to read and understand the T&Cs. In particular, ‘trial periods’ and ‘jurisdiction of stored data’ are recurring themes for us all.
Chatbots
DoNotPay (donotpay.com) is a simple chat-based interface to guide users through a range of basic questions to establish if an appeal on their parking ticket is possible. It was launched in 2015 and created by then 20-year-old Joshua Browder.
He created the site by scanning thousands of documents released under freedom of information legislation, under the guidance of a traffic lawyer. By mid-2018, the site estimated that it had saved 375,000 people around $9 million on parking tickets.
Expert systems
Neota Logic (www.neotalogic.com) is a coded AI automation platform, providing professionals with a range of easy-to-use tools to rapidly build applications that automate any aspect of their services:
- Client onboarding,
- New business intake and analysis,
- Triage and routing,
- Expert decisioning,
- Self-service legal and policy advice,
- Business-process automation,
- Document drafting, and
- Data analytics and reporting.
Practice-management
Apperio (www.apperio.com) is a cloud-based software-as-a service analytics solution. It is a legal-spend smart dashboard that gives in-house lawyers better insights into their external legal spend across the business.
Brightflag (brightflag.com) is an Irish-based AI-powered e-billing, matter-management, and analytics platform used by innovative corporate legal departments across the globe to manage their legal spend. The main technologies used are ‘natural language processing’ and ‘machine learning’.
Brightflag’s machine learning technology is reading and understanding legal-spend data, which gives in-house legal teams the ability to drive substantial savings, automate large portions of workflow, and generate powerful data for resourcing decisions and reporting.
Predictive AI
Premonition (premonition.ai) is an AI system that mines the information in big data to determine the effectiveness of individual lawyers, and possesses the largest litigation database in the world. The analysis conducted by Premonition provides information relative to litigators’ winning percentages before specific judges, including case type, case value, and duration.
This provides information about which lawyers win in front of which judges on which matter types, but also who is ‘running the clock’ on cases in terms of duration (and who resolves quickly). Premonition’s function is to spot trends and outliers, which it does well, as data is ‘smoothed out’ over thousands of cases.
Lex Machina (lexmachina.com) mines litigation data, revealing insights available about judges, lawyers, parties, and the subjects of the cases themselves, culled from millions of pages of litigation information. It:
- Analyses judges and courts,
- Sizes up opposing counsel,
- Evaluates parties in your matter,
- Crafts winning case-strategy, and
- Analyses litigation across different venues.
Legal research
ROSS (www.rossintelligence.com) is built on the IBM Watson cognitive computing platform. It is a legal-research tool that will enable law firms to cut the time spent on research, while improving results. It can understand questions in natural language and respond with a hypothesis, backed by references and citations. It provides only the most highly relevant answers, rather than thousands of results.
Vizlegal (www.vizlegal.com) is an Irish-based, subscription-based platform that helps with searching, tracking and saving judgments, filings and more. Via an API (application programming interface) integration, you can get access to more than 400,000 judgments and decisions (IE, UK, CJEU and SCOTUS). You can search and track Irish High Court cases, fully consolidated Irish High Court rules and practice directions, and it is mobile and tablet (Android and iOS) accessible.
Contract automation
Juro (www.juro.com) is a next-generation contract workflow platform, headquartered in London. It offers contract authoring, negotiation, and e-signing tools, while delivering AI-level analytics and data-extraction capabilities.
Founded by an ex-Magic Circle lawyer, the platform covers the end-to-end contract process, whether through the Juro interface or via API. A key selling-point is combining the power of AI with a design-first approach – powerful technology that anyone, whether in a legal, sales or HR role, can use.
Due diligence
Kira Systems (kirasystems.com/solutions/due-diligence) undertakes M&A due diligence by identifying and analysing clauses in company documents.
It uses machine-learning technology to automatically identify and extract information from contracts, and it is constantly increasing speed, accuracy and competency as a consequence of its experience and user feedback. It speeds up deals and give firms a competitive edge over others, especially in the bid process.
LONald is a robotic contract lawyer from Berwin Leighton Paisner (BLP) that supports the firm’s real-estate practice, handling due diligence on property transactions. It’s a software application that automates an aspect of legal work that was previously handled by junior associates or paralegals.
Powered by RAVN’s ‘applied cognitive engine’ (ACE), it automatically reads documents and unstructured data and extracts and summarises key information. It connects with the British Land Registry website and verifies the property details for large portfolio transactions, collating its findings in Excel spreadsheets.
In just seconds, it completes work that would take an associate or paralegal days or weeks. It runs in the cloud, so lawyers interact with it directly without involving the firm’s IT department. It learns and evolves with interactions and feedback from the user.