How AI-based information systems can increase the accessibility of justice
To improve the accessibility of justice to citizens, one of the central responsibilities of modern technology is to improve the quality of legal information available to the litigants. Currently, even though online dispute resolution systems are on the rise, there is still a complete absence of information systems that can empower citizens with basic information about the legal environment of their cases.
Having this basic knowledge is essential for citizens to move forward in their “justice journey”. Indian citizens today lack even the most elementary tools to understand their own case better — to gain a basic, low-resolution understanding of the legal environment surrounding their case.
Despite the fact that legal information is complex and technical in nature, there is still a need to provide litigants the ways and means to be able to seek and understand their own cases better, so that they can develop a basic contextual overview of their case and make strategic, financial, and process-related decisions. This enables citizens to have more agency and participation in their journey to justice.
In the absence of such basic affordances, even the most proactive, intelligent, and tech-savvy litigants can not make any helpful assessments about their future course of action, and are put in a position of helplessness from the moment a dispute has arisen.
It may be helpful at this point to clarify that what is being lamented in the above paragraphs is not that litigants cannot self-represent themselves throughout the entire lifecycle of a dispute. It would be unreasonable to make such a case, since a legal case has various nuances, complexities, and applications which cannot simply be programmed by a rule-based system, owing to the open-texture of legal language.
Instead, what is being referred to here is the first stage after a dispute has arisen, which necessarily occurs before a litigant hires a lawyer to represent them. In the timeline of events, there are several crucial decisions that need to be made by the litigant after a dispute has arisen and before a lawyer is approached. These are basic pieces of information that are relevant both to their case (for example, is there even a legal issue involved? Have any of my rights been violated? What kind of remedies are available to people in these situations? What are the options ahead, roughly speaking?), as well as to the larger judicial process should the individual decide to go down the path of litigation.
The question we are investigating, then, is whether technology can help in a prima facie diagnosis of legal issues for a citizen, and therefore enable them to choose a direction in an informed manner. More particularly, we review below some use cases of how artificial intelligence can be leveraged to facilitate this assessment of a case, and assist in a preliminary diagnosis of legal issues involved.
Better functioning legal search engines
The first step that is taken by most Indian litigants after occurrence of a dispute is a quest to search for answers. At this stage, the litigant is typically not searching for a lawyer, but is looking for answers to basic questions such as the laws that are applicable to its situation, articles, guides, and whether there is any preliminary information that can confirm to them they indeed have an actionable right.
At this point, a litigant typically searches for answers from interpersonal connections or (increasingly) by searching on a general search engine such as Google. In both cases, the quality of legal information expected to be received from such sources suffers a high risk of inaccuracy, insufficiency, and sometimes it is just plain incorrect to the extent of being dangerous and harmful.
A recent example of this can be seen from this Tweet, where incorrect medical advice shows up on a Google search snippet based on an inaccurate reading of an actual article.
One might be tempted to argue that there are specific legal search engines available such as Manupatra and SCCOnline that should be used to do legal research. However, these search engines are predominantly designed with legal professionals in mind. Even if they were affordable for an average citizen with a single case, it is almost impossible for a litigant to be able to effectively use these search engines to develop an understanding of the environment that their legal case is operating in considering that these platforms present various information asymmetries and barriers for an average citizen.
What is required therefore are user-friendly search engines that are designed for legal research, and which are accessible enough to be able to be used by litigants to educate themselves about their case. There is also a need for these legal search engines to be intelligent, since in the absence of such intelligence, the search engine would simply point the user to a heap of information instead of providing helpful context for that case. That would not be helpful.
An example of such search engines is the French legal search engine Doctrine.fr, which uses machine learning to bring focused searches relevant to the case. The search engine relies heavily on mapping the doctrinal, legislative, and jurisprudential of a case, to give a “complete vision of the legal environment of your file”.
In India, there are various AI-based legal search engines that are now available that aim to present legal information in a more structured and visual manner, creating helpful contexts that can aid decision-making in the initial steps. Though most of these search engines are again designed with lawyers in mind, they present some helpful inspiration of what more accessible legal search engines may be able to do for litigants.
Advisory tools are considered to be a vital part for building intelligent ODR systems. The purpose of Advisory Tools in the context of dispute resolution is to provide the litigant a guided journey in which they can share details about their case by specific question prompts, and receive helpful information, resources, and connections based on the details entered by the litigant.
Perhaps the most widely acclaimed Advisory Tool is the Dutch justice platform Rechtwijzer, a justice platform that “builds on the actual behaviour of people with a legal problem”. It’s built on the widely accepted premise that people with legal problems typically look for information about their problem, rights, obligations, and options, in an attempt to first try to solve their problem themselves, and seek help if that doesn’t work.
A walkthrough of Rechtwijzer
To get a broad understanding of how these Advisory Tools work, let’s take the example of Rechtwijzer.
When a user starts their journey on the site, they are first presented with the opening screen which asks the user to choose the most appropriate situation. For example, if the user has selected their type of problem as a marital / relationship issue, they will be asked to select whether they have already decided to separate, or if they intend to split, or if they have already split but there are new issues.
Then, after a series of questions such as marital status, details of children, marriage agreements if any, and financial details, the user is presented with a set of choices that apply to the user in that situation, such as conciliation or litigation.
The process further assesses the user’s level of comfort with the chosen option, and important details such as how confident they feel about the implications of their choice. Based on a factor analysis of these choices, the platform then connects the user to an appropriate lawyer referral service or legal aid centre, and aids them further through the journey.
Another example of Advisory Tools similar to Rechtwijzer is the British Columbia Civil Resolution Tribunal.
Advisory Tools such as these can be instrumental in enabling access to justice to citizens, especially self-representing litigants.
Decision Support Systems
Decision support systems (DSS for short) are computer programmes that utilise artificial intelligence and / or game theory to facilitate trade-offs.
DSSs can be incredibly helpful in coming up with a framework-led decision-making analysis between two conflicting parties, and therefore recommended to be included in intelligent ODR systems. Decision Support Systems can be useful even in the presence of lawyers or representatives since even specialist experts need deep analysis and powerful insight generation capabilities to connect the dots among all the data points available in the human decision-making process.
An example of such Decision Support Tools is Adjusted Winner, a game-theory based resource division framework that produces “envy-free” and equitable allocation of goods between two parties.
Another example is SmartSettle.
Decision support systems are another important tool that should be considered to be embedded in intelligent ODR systems that can help litigants understand their options through helpful graphical frameworks such as decision trees, probability metrics, and path costs.
Much of the access to justice crisis can be attributed simply to the complete absence of an information system that can provide the right information at the right time to a citizen looking for answers. Oftentimes, the answers being sought are not even legal questions, but juridical in nature, with the citizen trying to understand how the juridical process works. Solving these vast information asymmetries is central to bridging the justice gap in India, and artificial intelligence already has proven to be successful in various industries and use cases that are similar to these problems faced by the law and justice sector.
Further, the trend of citizens becoming more proactive in trying to resolve their own disputes (self-representing litigants) is getting stronger on a global scale. Developing automated systems which can provide helpful guidance through intelligent systems such as lawbots, walkthroughs, and comprehensive AI guides is the need of the hour and can go a long way in making justice more accessible in India.