Wednesday, July 19, 2017

What is Law? - part 15

Previously: What is Law? - part 14.

In part one of this series, a conceptual model of legal reasoning was outlined based on a “black box” that can be asked legal type questions and give back legal type answers/opinions. I mentioned an analogy with the “Chinese Room” used in John Searle's famous Chinese Room thought experiment[1] related to Artificial Intelligence.

Simply put, Searle imagines a closed room into which symbols (Chinese language ideographs) written on cards, can be inserted via a slot. Similar symbols can also emerge from the room.

To a Chinese speaking person outside the room inserting cards and and receiving cards back, whatever is inside the room appears to understand Chinese. However, inside the box is simply a mechanism that matches input symbols to output symbols, with no actual understanding of Chinese at all.

Searle's argument is that such a room can manifest “intelligence” to a degree, but that it is not understanding what it is doing in the way a Chinese speaker would.

For our purposes here, we imagine the symbols entering/leaving the room as being legal questions. We can write a legal question on a card, submit it into the room and get an opinion back. At one end of the automation spectrum, the room could be the legal research department shared by partners in a law firm. Inside the room could be lots of librarians, lawyers, paralegals etc. taking cards, doing the research, and writing the answer/opinion cards to send back out. At the other end of the spectrum, the room could be a fully virtual room that partners interact with via web browsers or chat-bots or interactive voice assistants.

Regardless of where we are on that spectrum, the law firm partners will judge the quality of such a room by its outputs. If the results meet expectations, then isn't it a moot point whether or not the innards of the room in some sense “understand” the law?

Now let us imagine that we are seeing good results come from the room and we wish to probe a little to get to a level of comfort about the good results we are seeing. What would we do to get to a level of comfort? Well, most likely, we would ask the virtual box to explain its results. In other words, we would do exactly what we would do with any person in the same position. If the room can explain its reasoning to our satisfaction, all is good, right?

Now this is where things get interesting. Imagine that each legal question submitted to the room generates two outputs rather than one. The first being the answer/opinion in a nutshell (“the parking fine is invalid : 90% confident.”). The second being the explanation “The reasoning as to why the parking fine is invalid is as follows....”). If the explanation we get is logical i.e. it proceeds from facts through inferences to conclusions, weighing up the pros and cons of each possible line of reasoning....we feel good about the answer/opinion.

But how can we know that the explanation given is actually the reasoning that was used in arriving at the answer/opinion? Maybe the innards of the room just picked a conclusion based on its own biases/preferences and then proceeded to back-fill a plausible line of reasoning to defend the answer/opinion it had already arrive at?

Now this is where things may get a little uncomfortable. How can we know for sure that a human presenting us with a legal opinion and an explanation to back it up, is not doing exactly the same thing?

This is an old old nugget in jurisprudence, re-cast into today's world of legal tech and Artificial Intelligence. Legal scholars refer to it as the conflict between so-called rationalist and realist models of legal reasoning. It is a very tricky problem because recent advances in cognitive science have shone a somewhat uncomfortable light on what actually goes on in our mental decision making processes.

Very briefly, we are not necessarily the bastions of cold hard logic that we might think we are. This is not just true in the world of legal reasoning, by the way. The same is true for all forms of reasoning including – shock! - mathematicians.

Recent research[2][3] suggests that human legal reasoning is best viewed as a bi-directional process that oscillates between working forward from premises/facts and working backwards from conclusions to supporting premises/facts.

Mention was previously made of the feature of law whereby different legal minds can look at the same corpus and come up with different conclusions. In this respect, our virtual legal reasoning room is just another source of a legal opinion. Another legal “mind” if you will. The quality of the opinions produced are judged on their merits – the explanations - not on its actual means of production of answers/opinions.

To this way of thinking, lawyers should enthusiastically embrace these new virtual research assistants that are emerging. Who wouldn't see benefit from being able to get other legal “minds” to look at a legal question and offer opinions. Who wouldn't see benefit from being able to ask such a virtual research assistant to argue for and against a given assertion to help sharpen a line of reasoning for use in a legal opinion or in a court room?

Some see problems with the modern machine learning approach to legal AI because of the inability of these systems to explain their conclusions in the form of classic forward-chaining logic. I do not see this being a problem in practice because these systems will develop ways to explain their opinions. They will most likely do it as a completely separate activity. We may know for a fact that they  are reasoning "backwards" but we can never know if the same isn't true for the opinions given by our fellow humans – including the opinions we provide to ourselves!

We have a tendency to get caught up in the notion of intelligent machines replacing humans. We look at the incredible progress machines have made in playing Chess of Go, identifying faces in photographs etc. and some wonder how long it will be before the machines replace the lawyers. I believe there is a qualitative difference between practicing law and, say, playing chess that gets glossed over in the excitement about AI in law.

In chess, there is a small number of variables and a huge, huge set of permutations/combinations of possible moves. Moreover, the key variables can all be encoded for the machine to work with. This makes this sort of game-playing a great candidate for complete mechanisation. i.e. getting to the point where the machine can play the game unaided.

Not so with law. A lawyer's reasoning processes invariable are a lot more expansive covering variables such as the overall goals of the client, trade offs between time and opportunity cost, reputational risk factors, budget constraints, team dynamics etc. etc. On top of these, I have argued in previous posts that the entire legal system is not and cannot be, reduced to a set of rules – no matter how large the set of rules might be envisaged to be.

Rather than think of machines are replacements for lawyers, better to think of machines as augmenting lawyers in my opinion. Machines are no longer confined to document management and mechanical search&retrieval. Machines are increasingly offering opinions as to what is relevant. They have been doing that for quite some time - from the dawn of search result ranking - but in recent years their role as sources of opinion has grown significantly. This trend will continue apace in my opinion. I think we will soon see the day when every lawyer in private practice has access to legal virtual assistants that can provide answers/opinions to supplement the lawyers own research/experience and that of their colleagues.

If I were a professional chess player, I would be a lot more worried about career viability in the age of intelligent machines than I would be as an lawyer, or an accountant or a medical doctor. Yes, intelligent machines will impact these professions as more and more of the mechanizable tasks become mechanized. But the machines can only compute with what they have visibility of and it is in all the stuff that the machines cannot have visibility of that the 21st Century professionals will live.

A good example of this can be found in the world of contracts and in particular, the emerging world of “smart contracts” which is where we will turn to next.