The Looming Ethical Issues for Legal Analytics

February 18th, 2014

In this post, I want to address at a very high level what I see to be four ethical issues looming over the horizon for legal analytics firms. I define legal analytics broadly, without regard to any particular company, as a service that offers personalized, legal advice based on data, that is not provided through the attorney-client relationship. I am not talking about traditional legal research tools, such as WestLaw or Lexis. If a user can perform a simple query, and get back a set of pre-determined results based on a keyword search, there are no issues here. As Legal Techies are wont to point out, there is not much of a difference between the old reporters of old, and WestLaw Next, beyond the medium. Both rely on the keynote system to identify cases.

What I am talking about, with respect to legal analytics, are firms that can provide customized answers based on specific questions clients (both lawyers and nonlawyers alike) may raise. For example, if a firm provides an analysis on whether a firm should file a suit in a certain way, file a suit in a certain venue, or move to change venue, or advise a client on the opponent’s settlement history. There is a very fine line between the old-fashioned form of legal research, and the new forms of legal analytics. In other works I will try to define these terms with more detail, but for here this definition will have to suffice.

I see four main looming problems. The first is well-discussed. How are these data analytic firms structured? Specifically, do they run afoul of Rule 5.4, which blocks ownership of law firms by non-lawyers. The answer to this issue will depend on whether the nature of the activities these analytic firms are perform are considered legal services. If no legal services are being provided, RUle 5.4 doesn’t apply. If there are legal services being provided, until the rules are changed, Rule 5.4 applies. It is only a matter of time before several players in the field who are coy about the manner in which they are structured are going to have to deal with this. I’ll leave that issue here for now.

Second, these data analytics firms, whether deemed law firms or not, will have to confront potential conflicts of interests. Most small startups likely won’t have this problem, but as they advance and develop, they will need to put safeguards into place to ensure that they are not offering advice to adverse parties, or more likely, clients who may have interests adverse to another client. What complicates this issue further, going back to issue 1, is if these data analytic firms are funded by outside investors, there will be many harder-to-detect conflicts of interest. (This is, in part, what Rule 5.4 is aimed at preventing).

Big data further compounds the conflicts problem. As data analytics advances, firms will start to use data about all of their clients to improve their algorithms. Google uses the searches from millions of people to improve their algorithms. The same goes for data analytics firm. For example, a predictive coding company could analyze all of the different searches its customers perform, in order to improve its search mechanisms. Although the data would probably be anonymized, I would imagine some clients may be adverse to a firm sharing their search techniques–albeit indirectly–with their opponents. Think about this issue for a bit. It gets complicated very quickly.

The third issue concerns legal malpractice. Let’s consider the same scenario, both with old-fashioned legal advice and through data analytics. Old school: a lawyer tells a client to change venue, because a different venue may offer a better jury verdict. This advice proves to not only be wrong (verdicts are lower), but as a result of the change of venue, the case is now subject to a rule of law that is directly adverse to the client’s case. By any objective measure, staying in the original jurisdiction would have been better. This is a ripe case for legal malpractice. Assume the same scenario, but the advice comes from a docket analysis tool that predicts that a different forum has higher verdicts (but doesn’t consider the rule of law issues).

Consider another example. Imagine a small startup business without a general counsel is sued, and instead of paying an expensive retainer, sends some queries about potential exposure to a legal analytics company. The analytics says to ignore the suit, because the plaintiff is just trying to extort a settlement, and never goes to court. This advice turns out to be wrong, and the company is ruined by the bad advice. What happens? As it stands now, if a lawyer provides incompetent services, the client can sue for legal malpractice. In most jurisdictions, active lawyers are required to maintain some level of malpractice insurance to protect against this. To my knowledge, there are no insurance companies that provide this type of product, beyond some super-expensive umbrella policy. Malpractice could be extremely cost-prohibitive, and devastating sources of exposure for startups.

The fourth issue, and the other elephant in the room, is Unauthorized Practice of Law (UPL). Reading graphs to offer advice on how a case should settle, or where it should transfer to, is at its heart the practice of law. That an algorithm spit it out doesn’t really matter. Non-lawyers, or even lawyers not working for a law firm, are unable to give this type of advice. Data analytics firms should tread carefully about handing out this type of personalized advice outside the context of the attorney client relationship.

Though, for the time being, I’m not too worried about this final issue The vast majority of the UPL problems are obviated when a law firm, or a general counsel, serves as an intermediary between a data analytics firm, and a client (non-lawyer). As long as a lawyer somewhere in the pipeline independently reviews the data analytics recommendations, and blesses it, I don’t see any of these as significant problems (though bad advice may result in a malpractice suit). I’m working on another paper that analyzes the law of paralegals (this is actually a thing), and what kind of legal tasks can be delegated to paralegals under the supervision of a lawyer.

But, when data analytics firms try to expand to serve consumers directly–like LegalZoom–we hit this problem hard. When there is no lawyer in the pipeline, things get difficult very quickly.

I will expand on these four items in time. I highlight these topics not to cast a dark cloud on data analytics. I am a big fan of the industry, and am excited for the innovations it can bring to the delivery of legal services. Instead, I get the sense that many in the field are willing to either openly flout the rules, ignore the rules, or take the “sue us” mentality. I may be totally wrong about all four of these items. Maybe everyone will remain so happy with these services, that there won’t be a need of a lawsuit. Perhaps these industries are so well-funded that they can fight back any law suits. It could be the case that the state bars will suddenly realize that these firms are significant, and that the rules should change them. (As an aside, people in the field should be joining state ethics committees to try to change the rules from the inside).

But, I’m pessimistic. The history of the law has been, at every stage, opposition to new entrants that can take away from marketshare–for both good (protect quality of service) and bad (protectionism) reasons. I don’t see the future of legal analytics much differently.