As analytical tools develop, more companies are pushing out product (see the ‘Know your provider’ panel), but it raises questions, not just for law firms, but also for society.
Big data
The PA push is being driven by ‘big data’, which in turn is driven by lower costs in artificial intelligence (AI) and computing power that can run algorithms to get real-time solutions in ways that could not be achieved until relatively recently.
This holds an obvious appeal for lawyers, though arguably provides more benefits in some areas rather than others. In case-law research and e-discovery, for instance, considerable benefits can be seen.
Brian McElligott (partner, Mason Hayes & Curran) says: “The best application is in niche-driven, repetitive tasks – for example, insurance.”
However, it also offers threats, because clients can do the work instead of law firms. Certainly, we will see more cases like JPMorgan Chase, which reduced some 360,000 billable hours at an average of $200 an hour, resulting in $72 million of legal fees evaporating.
Opportunity
Equally, there are opportunities for firms to use PA to identify new business, to cross-sell and upsell to existing clients, and to be more effective in bringing new clients on board. Currently, firms in Ireland are making limited use of PA.
McElligott says: “Predictive analytics are used in Ireland, but I think it is a little more basic at the moment. One major use in firms is to increase their ability to reach out to lukewarm contacts, rather than cold contacts.”
Creating better metrics, enhancing partner profitability, matching lawyers to client need, using ‘gig lawyers’ or other consultants, and more creative fee structures are all ways we can expect to see PA growing in use.
Evolution of lawyers
What may be happening is an evolution of lawyers – raising them to new levels of service – with the expensive labour-intensive tasks for firm and client alike drastically reduced.
Providers are also pioneering PA to help provide robustness in creating legal strategy. PA can help lawyers assess the merits of a client’s case, and provide analysis for offering sound legal advice.
Unique and proprietary data – such as case notes, records, models, resources, and expert profiles – can be leveraged to create an effective team, with the right data collated to tackle the workload.
Best representation
Just as important as detecting trends and highlighting data patterns is the choice of who can best represent a client. PA can be used to decide the optimal composition of teams and ensure that all needs are covered by relevant expertise.
This can include deciding on what outside counsel, consulting, strategic partnership, or individual best fits the client’s needs.
PA in the hiring process can help match the right candidates to the firm, as well as selecting individuals both for ad hoc projects and long-term relationships. The emergence of ‘gig lawyers’ will also expedite new ways of building teams.
Threat
There are, however, certainly three areas of concern, which also relate to broader social concerns. A fundamental – but long-term – concern relates to training.
PA is taking over some of the tasks traditionally undertaken by juniors to hone their craft. Opinion is divided on the issue, with PA proponents saying that the training benefits of such tasks are overstated.
Impact on training
Dr Jennifer Cobbe, coordinator of the British-based Trust & Technology Initiative, and a researcher in the Compliant and Accountable Systems Group in the Department of Computer Science and Technology, University of Cambridge, disagrees: “There is an impact on the training of young lawyers.”
Dr Cobbe says: “A good analogy is banking, where, as banks moved into automation, basic functions like cashiers were phased out, but this was the route for many to get into the industry, and this has been shut down.”
Cobbe also sees the impact as an access-to-justice issue: “This is a fundamental concern that is not much discussed.” For markets like Ireland, where there are many sole practitioners and small firms, “this creates a talent-feed issue”, she says.
“It is not discussed as much as should be, but it is an access-to-justice issue.”
Judicial analysis
A second area of concern is judicial research. At the forefront of PA are products that track the litigation history of judges, lawyers, and law firms, including their win/loss rates for trials benchmarked against competitors.
PA can be used to track the success rates of different types of motion in individual courts and keep a database of who sues and gets sued most frequently. The products offer analyses of similar briefs filed by other firms, relevant case history, and judges’ citations, often down to the most cited paragraph.
French ban
A possible crucible for social debate comes, surprisingly, from France, where PA has been banned.
The country recently enacted a law that bans legaltech companies from identifying judges or magistrates in connection with statistical analyses or predictions about their future actions. The law stipulates a maximum penalty of five years in prison for those who breach the rule.
In addition, a 15 June 2019 resolution has been issued by the Conseil National des Barreaux (CNB), the domestic bar council, calling for an extension of the ban to include lawyers, so that they would also be excluded from the statistical analysis of their actions in court.
In addition to guaranteeing lawyers the same access to the flow of legal decisions that judges have, the bar opined that “identical treatment” protecting the personal identifying data of lawyers in such decisions, released for open data, is “the only way to guarantee the equality of arms under the European Convention on Human Rights”.
Such a ban would essentially make it a crime to interpret lawyers’ patterns of behaviour in court. If successful, this would mean that France would be the first country in the world where litigation analysis and predictive modelling falls under a comprehensive ban.
Open data
What would still be permitted in France is a more limited analysis of how certain legal arguments played out in court, what claimants could expect to be paid, and how many claims of a certain type usually win – but without inclusion of the names of the professional parties or judges involved.
Experts in France have said that they are surprised by the move, given that the CNB held a very different view just three years ago, when France first moved ahead with its ‘Open Data’ project to make all public data available online for all to see, including court data.
A recent IFOP poll commissioned by Doctrine, an AI-based legal research and litigation analytics company, revealed that 87% of French lawyers were against anonymisation of judges’ names and that 63% of young lawyers wanted to increase their online visibility.
Looking at the French tradition, this should, perhaps, not completely surprise, since secrecy has been something of a trademark of French law.
Filtering out bias
A third danger in PA is one of bias. ‘Big data’ applications do not usually revolve around individual profiles, but around group profiles. Nor does it revolve around retrospective analyses, but around probability and predictive applications, with a margin of error.
Even with its celebrated objectivity, elements of potential bias remain in PA, and a good strategy needs to excise such bias to avoid incompetence and error being built into the strategy.
The data we choose to use or exclude is critical, and data-mining in law firms requires interrogating big data-sets such as docket data, legislation, case law, client contracts, and property titles.
Making simple correlations, or assessing averages thrown up by the data, still requires lawyers to interpret the meaning of such correlations, causal relationships, context and human behaviour.
Dynamic relationship
PA research is a rationalising process that puts technology and people into a dynamic relationship, underpinned by clean and enriched data.
PA supports quantitative research, making sense of big data and unwieldy data-sets, which can then support qualitative data using statistics, algorithms, and heuristics to predict outcomes.
But the courts will take into account more than the rational, as they also include human behaviour and emotion. In case management, lawyers often seek to second-guess the best time to file a case, which jurisdiction to use, or which judge might be more sympathetic – but also to understand the human task of legal reasoning by judges.
The problem is that people do not behave optimally and, indeed, often behave irrationally, emotionally and against their interests – one of the primary reasons we need lawyers!
Second-guessing PA
Second-guessing the future of PA, in light of the French experience, is not straightforward. PA is part of the commoditisation, increased offshoring, or ‘Amazonification’ of the business of law.
PA tools may form part of the transformation, reducing costs by replacing mundane tasks, but not necessarily lawyers’ skills.
Dr Cobbe warns: “We need to ask, what is the goal of automating law? Is it efficiency and costs? Competitive advantage? Something else? I would be worried about going too far into the market without these questions being answered.”
How can the profession in Ireland make use of PA? McElligott says: “There are a few issues. First, the conservatism of Irish firms. They will ask what is required? What are the benefits? Second, no-one wants to be first. The product exists, but lawyers like to use something when it has become a standard.”
Cascade effect
Once it is seen to work, McElligott says that “firms will adopt quickly, because once there are a few products out there being used, there will be a cascade effect, and people will get on board. The bigger firms, those with the resources, will do it first”.
However, Cobbe cautions that big data and PA throw up broader issues for law and society: “If we look at law as a societal construct, it not only reflects theory, what is decided, but has an impact on society. Social values are reflected in the legal system, what it should be about, how it should work.
“When this is automated, we can ask whose interests are being served? The big law firms? A middle class, white, narrow section of society? What about those who don’t have access to big law firms?”
There are many applications, and the future offers expanding opportunities. However, the critical step is to develop a successful strategy for predictive analytics, which means, it seems, finding a balance between big data and people, for the sake of both firms and society.