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Ross: Attorney built on top of IBM's Watson

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Re: Ross: Attorney built on top of IBM's Watson

#111

Earlier quoted context omitted.

Its not meant to replace humans. Its meant to reduce the amount of tedious research work they need to do. If you reduce the vast tedium of researching stuff in Westlaw/LexisNexis, you can spend more time on your research memo. You can do more actual analysis work. Thus firms can reduce the number of associates they need on staff, because the associates won't be wasting time on wrangling research results. Yes, you sti…

Perhaps, if you are the 1% of lawyers who are associates at big law firms doing appellate-level research. They basically the same job as law students do in LRW class, pulling hundreds of quasi-relevant caselaw from a massive database. That side of things has, in recent years, been outsourced overseas. See companies like http://www.legalsupportglobal.com/

You don't have to be doing appellate level research to have a need for pulling tons of caselaw.

I doubt much of that has been actually outsourced.

But its just not a huge part of the junior associate responsibilities. It is probably 1/10th or less of the job.

Re: Ross: Attorney built on top of IBM's Watson

#112
post #72

Love the idea and execution, but this is less an attorney and more a legal librarian. Attorneys spend most of their time on the facts of the case. In law school, most lawyers are taught to present each argument in a standard format called IRAC: Issue, Rule, Analysis, Conclusion. The issue is like the question presented on the front page here: "can courts pierce the corporate veil where a corporation has misappropriat…

Interesting, IRAC sounds a lot like SOAP (subjective, objective, assessment, plan) notes used in medicine.

Probably very similar. It's designed to make lawyers think methodically about a problem to avoid errors of logic and construction.

Re: Ross: Attorney built on top of IBM's Watson

#113
post #72

Love the idea and execution, but this is less an attorney and more a legal librarian. Attorneys spend most of their time on the facts of the case. In law school, most lawyers are taught to present each argument in a standard format called IRAC: Issue, Rule, Analysis, Conclusion. The issue is like the question presented on the front page here: "can courts pierce the corporate veil where a corporation has misappropriat…

Great comment. What ROSS does in addition to what you've described is ask questions against the context of a case. The case facts (inputed by users) will be factored into the queries so as to produce the most relevant information (rules, precedents and other connections across a vast body law) that would take an associate (especially a junior) many hours to unlock. And absolutely, ROSS is not the end. The quality of…

Sounds awesome. What sort of computational cost does each query take?

Re: Ross: Attorney built on top of IBM's Watson

#114

Earlier quoted context omitted.

>that's not how that works

So why can't they apply Watson to the challenge of improving Watson?

I used a sharp piece of flint to carve out an even sharper piece of flint. But it didn't become sentient. :-(

Re: Ross: Attorney built on top of IBM's Watson

#115

I'm impressed, and I'd love to see it in action. But I'm also worried that this is going in the wrong direction. If the law is getting too complex for humans to handle, the solution is not to create supercomputers that help us. The solution should be to simplify the law.

This seems similar to attempts to rewrite a complex code base to be simpler, more consistent, and easier to understand. In practice, a lot of the quirky, wonky code is there to fix an actual bug that was encountered, and taking it out re-introduces the bug. How do we know eliminating some of the complexities of current laws won't re-introduce some of the problems those complexities were trying to solve?

> How do we know eliminating some of the complexities of current laws won't re-introduce some of the problems those complexities were trying to solve?

The other side of that coin is: are the bad outcomes produced by the current codebase bad enough that we will replace them and accept the risk of re-introducing the other bugs?

Alternatively, the entire codebase is in English (+/-) so one could document the bugs that changes are attempting to address.

Re: Ross: Attorney built on top of IBM's Watson

#116
post #72

Love the idea and execution, but this is less an attorney and more a legal librarian. Attorneys spend most of their time on the facts of the case. In law school, most lawyers are taught to present each argument in a standard format called IRAC: Issue, Rule, Analysis, Conclusion. The issue is like the question presented on the front page here: "can courts pierce the corporate veil where a corporation has misappropriat…

Right now, there are a lot of billable hours for what Ross can do in seconds. I don't think it's unfair to say that this is replacing a substantial portion of _some_ lawyer's jobs.

[deleted]

Re: Ross: Attorney built on top of IBM's Watson

#117
post #72

Love the idea and execution, but this is less an attorney and more a legal librarian. Attorneys spend most of their time on the facts of the case. In law school, most lawyers are taught to present each argument in a standard format called IRAC: Issue, Rule, Analysis, Conclusion. The issue is like the question presented on the front page here: "can courts pierce the corporate veil where a corporation has misappropriat…

Yes, e-discovery is definitely the missing piece here. At the end of the day, lawyers need to be empowered by technology to do their job better, and ultimately make the legal system better. And it should be called RICK.

E-discovery has already gone through an impressive cost deflation with the application of more sophisticated scanning, OCR, and search algorithms that recently (in the past decade) came onto the market. I've seen more than a few law firms that developed an over-dependency upon discovery-related fees in their business model either drastically downsize, abruptly change, or in one case shutter their doors entirely (after a painful circling the drain).

If deep learning technology like Watson deflates further the remaining e-discovery market as well as the initial case research billables, it will be interesting to watch how law firms adjust their business models. For those that can stand out with consistently innovative, novel and creative legal services delivery (like nearly always coming up with newly-accepted interpretations of case law) that depends upon people, I could easily see rates for those attorneys go dramatically up, partly to backfill the revenue gap that is created in the wake of automation of these aspects of legal services business models, partly due to an exacerbation of the bifurcation effect automation seems to have upon labor markets.

Re: Ross: Attorney built on top of IBM's Watson

#118

Earlier quoted context omitted.

Right now, there are a lot of billable hours for what Ross can do in seconds. I don't think it's unfair to say that this is replacing a substantial portion of _some_ lawyer's jobs.

I'd like to see a concrete description of the difference between what ROSS gives you versus what, say, LexisNexis does. If its just giving you a simple answers and not actually producing the kind of research results a research attorney using traditional research tools would -- where the simple answer would be part of the heading, but sources and analysis would be part of the report -- its not going to be useful excep…

My guess is that it's roughly analogous to the difference between Wolfram and Google.

One is actually computing on the data to combine it in novel ways.

The other is the one I use.

(Snarky, but as much as I try, the only thing I've found WA useful is for COLA comps)

Re: Ross: Attorney built on top of IBM's Watson

#119
post #47

Does anyone know of in-depth articles that explain Watson internals (or even general such as what family of algorithms they're using) ? A friend of mine got to visit their R&D department a few years ago, and told me they basically explained nothing at all and remained on the marketing level. But there's got to be something somewhere, like previous research articles by the team's members, right ?

http://nlp.cs.rpi.edu/course/spring14/nlp.html
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