If we are increasingly willing to consign our fortunes to the advice of artificially intelligent financial advisers and place our mortal survival in the hands of robo surgeons and driverless cars, when should we entrust our legal rights to robo-lawyers?
This four-part series explores whether we want robo-lawyers and when they are likely to rise, what it will takes for a robo-lawyer to understand a human client and its legal issues, subtle legal skills we will need to develop in a robo-lawyer, and the deeper changes society will face before embracing robo-lawyers. Part 4 of this series also posits five questions you should ask your robo-lawyer before abandoning corporeal counsel.
The growth of artificial intelligence (AI), machine learning, speech recognition, big data, blockchain and other related technologies are making possible many new robo-professionals, from tax preparers to financial advisers, medical diagnosticians, surgeons and autonomous drivers. The pace of change is accelerating, such that there is now discussion about AI studying law, leading at least some to question whether there will be an Armageddon for lawyers as well.
Do we even want robo-lawyers? As access to legal service providers becomes quicker, easier and cheaper, better information should lead to better decision-making, which in the aggregate should then result in more predictable outcomes, less contentious work such as litigation, and greater client profits. Cheaper access to legal services also improves opportunities for those who cannot afford it or who otherwise do not easily appreciate the value of legal advice. If we can accept cars driving us, and robots operating on us, we will eventually come to accept robots practicing law for us.
The fullness of time probably renders this question irrelevant, or at least less interesting than the questions "how will we humans know when our time has come?" and "how should we assess the value of a robo-lawyer's legal advice until the change-over is complete?"
How long do we have? Speech recognition has been around for more than 60 years. Westlaw and Lexis-Nexis have been identifying useful case law for around 45 years, roughly half of those years using natural language searches. One of the more advanced AI approaching the bar right now goes by the name ROSS, powered by IBM Watson. ROSS claims to take in questions in natural language and output not only relevant case law and statutes, but also answers to some basic legal questions. ROSS began in the area of bankruptcy law, but its competencies will grow quickly. ROSS has a budding number of kindred e-spirits, which include Peter who verifies and organizes documents and document signings, an AI from Luminance operating in the mergers and acquisition space, LONALD, and nearly everyone's favorite DoNotPay, a bot for contesting parking tickets. These AI operate based on technology marketed as neural networks and deep learning, which 10 years ago beat human chess experts (Deep Blue by IBM), five years ago won at the TV show "Jeopardy" (Watson by IBM), and recently beat human experts at the game of Go (DeepMind by AlphaGo) and poker (Libratus).
In the next few years, AI will continue to accelerate downsizing in many areas of legal services, including those related to processing and filing documents, maintaining client bills, conducting and processing document discovery, interfacing with third-party service providers, and general law practice management. There is already a reduction in the number of billable hours lawyers and their assistants pass through to clients in relation to quasi-legal administrative matters and even basic legal research.
Present day software can ask a client questions and use the input to choose among pre-drafted contracts, wills and other agreements, and then modify them in simple, predictable ways. Sufficiently powerful computers like ROSS are beginning to review all prior legal decisions on a narrow legal issue and provide suggested answers, perhaps appended by a level of confidence and even a list of outlying data that cannot be harmonized with the advice. At the edge of what is conceivable with existing technology, we may start to see software that drafts very rough version of substantive legal correspondence, followed by portions of briefs, opinions and judicial decisions.
AI and big data will continue to improve the quality of predictions and client counselling in increasingly complex matters, so that cost and delays are reduced, or clients may use the law toward more strategic outcomes. Each of these improvements are likely to begin in stable or formulaic areas of law like traffic and parking violations, insurance claims, real estate (especially conveyancing), contracts and some areas of family law like drafting basic wills. Improvements will then move toward such things as jury selection and first drafts of trademark and later patent registration filings.
We can assume that the current trends of improved speech recognition, natural language parsing, and deep learning will continue, perhaps as Bill Gates suggests overestimating what is likely in the next few years, but underestimating what is likely in the next 10. •