Is the age of legal data coming?

The big data age is making the law ever more powerful, in today's digital age, big data is extremely important, especially for law firms, where legal business may eventually be driven by data, when we can judge whether he or she is a good lawyer through the ability of a lawyer to sift through thousands of potentially relevant cases.

With the acquisition of massive amounts of data, analysis is becoming more important. New tools to validate legal information, organize, and even visualize legal information are helping legal workers to gain access to vast amounts of court information, and the built-in intelligence of these tools is likely to be a key differentiator in future digital law searches as storage becomes cheaper and processors become faster. This article is for days with CTO Hu Qingping, I black horse sharing this article hope to help.

Article one: The three major changes in the legal profession in the age of large data

Author: Zhongguancun

In the face of new technology, legal professionals are usually one of the most conservative, but in the big data age, lawyers and law firms want to stand out from the crowd and use big data technology as quickly as possible.

Since the 2008 financial crisis, the legal profession has experienced a long period of low tide, more and more enterprise customers can not afford high lawyer fees, resulting in the law firm layoffs, the scale is shrinking. And the industry-leading firms are starting to embrace "lean companies", and the charging model has been adjusted from past fixed rates to on-demand services.

But the "lean law Firm" is not a fundamental solution, and law firms must use large data to drastically reduce information processing costs and improve digital competitiveness. Gigaom columnist Derrickharris wrote recently that law firms need to focus on three issues when they are optimized for processes based on large data.

One, the automation creates "the piercing eyes"

Document retrieval may be the area where large data has the greatest impact on legal work. Law firms typically store large amounts of unstructured electronic documents, including e-mail, Office documents, PDF documents, and so on, and retrieving case-related documents from terabytes of data is a lawyer's nightmare, time-consuming, laborious and inaccurate. Through large data intelligent analysis software, the law firm can greatly improve the efficiency of document retrieval. For example, large data start-up company Recommind development of large data software can be a machine learning algorithm for "predictive coding", greatly improve the efficiency of legal document retrieval. Another noteworthy enterprise-purediscovery Semantic Analysis technology can greatly improve the efficiency of document retrieval.

It is noteworthy that Recommind is also constantly developing new product hypergraph (Super Atlas), such as helping lawyers find the function of associating relationships between people, topics, timelines, and unstructured data (Editor's note: A similar Atlas analysis). Recommind in this area are facing competitors including ZyLAB, EMC and IBM.

Second, everything can be digitized

There are a lot of documents in the lawsuit, and the data contained in these documents have a high reference value to the later case defense and trial.

The target clients of the big data start-up, Lex Machina, are IP attorneys, who provide them with decision-making support for data-statistics services. Lex Machina has quantified many of the more obscure qualitative data in the past, such as "The judge is very bad for the defendant", "the case of such claims is usually won" or "the lawyer has the highest experience in such technology". Lex Machina's data source mainly comes from the open pacer (Federal Court database), where Pacer's data is always there, but Machina is the first company to "Taobao" from technology such as machine learning and natural language processing.

Notably, Machina's predecessor was a non-profit project, the Stanford Intellectual Property Law Settlement Center, which also recruited Stanford University's machine learning and natural language processing expert Andrew Ng and christophermanning. There is an excellent report on Machina on IEEE spectrum.

Self-help and innovation in the application of large data age

Instead of waiting indefinitely for big data vendors to develop useful lawyers, lawyers need to do it themselves, creatively using a variety of off-the-shelf large data tools and data sources. For example, a lawyer can use tools such as Scraperwiki to analyze a witness's Twitter contact network and activity record.

Lawyers can also use free tools such as ETCML (corresponding paid services such as ALCHEMYAPI) to analyze various texts, including tweets and emails, to discover key concepts or make tendentious judgments. A tool such as petty import.io extracts data from a Web site (such as real estate price historical data) and makes a chart.

In addition, lawyers should learn to grasp the current more popular data visualization tools.

Article two: Will the robot steal your job?

Translator: Ya Ya Ya

Over the past few years, the legal profession has witnessed the rapid development of technological innovation, thanks to the increasing ability of computers to translate and understand written documents. Many law firms now use "electronic forensics" tools to search for facts and figures of interest from a large amount of evidence. The firm also has a software program that can draft legal documents, which takes only a fraction of the human race. This automated technology will bring legal services to the masses.

Imagine you're facing a lawsuit right now. Your new company has created a very popular applet, and your top competitor, "Tiny soft" international, is suing you for patent infringement. If the "Tiny soft" company wins, you'll have to pay tens of millions of dollars.

So you consulted your in-house lawyer and he recommended you hire a patent expert from a rich, limited-liability partnership. The next day, a group of rich-company lawyers came into your company and listed all your options. The defence of a lawsuit against a "tiny soft" company is expensive--not counting the time charged for a case-appointed lawyer, and you need to hire expert witnesses and jury-appointed experts and pay for their travel and litigation costs. Total, you need about 5 million dollars, but the senior partner at the elder level of the company, Mr. Pocketbook, assures you that the money is worth it-he has dealt with many of these cases and he winked at you and his gut tells him that he will win.

Your other option is to settle out of court with a "tiny soft" company. You need to pay a 10 million-dollar licence fee, which is not a small amount, but it is still available to your company-then you can continue to do your business.

What are you going to do?

It's not easy to make a choice. In the age of the company, the law industry was one of the few areas that relied primarily on human experience. Anyone who gets involved in a which millions of-dollar case will ask a few basic questions--what are my chances of winning? How good is my lawyer??—— none of these questions have a definite answer. "The legal profession has a cultural heritage. Daniel Katz, an assistant professor of law at Michigan State University, says he is one of the pioneer law researchers who are committed to introducing empiricism and artificial intelligence into the law. Daniel Katz "Humans have a lot to take for granted, and people tend to think that legal knowledge applies only to humans, and that data, computers and automation equipment are not suitable for this." ”

Katz is studying his "quantitative legal projections." In the United States, thousands of patent cases are recorded every year. So it's possible that the "tiny soft" company suing your case is similar to a whole bunch of other cases. What if you could carefully analyze the key features of the "tiny soft" company's claims and then look at how many of these comparable cases are progressing? Lawyers can say to clients, ' I think you have a bit of a win--and that's the percentage that the computer infers on 10,000 similar cases. ' said Katz.

No machine can do this today, but it will. In the previous chapter, I looked at a technology that was eating into journalism--computers were becoming more adept at using language, and they had been able to write stories entirely by themselves. And the journalist's work is a piece of cake; If you want to engage in a job that relies heavily on language, then the rich and strong legal profession is a good place to be.

In the past few years, the legal profession has witnessed the rapid development of technological innovation, thanks to the increasing ability of computers to translate and understand written documents. Many law firms now use "electronic forensics" tools to search for facts and figures of interest from a large amount of evidence. The firm also has a software program that can draft legal documents, which takes only a fraction of the human race. Some of the services that are about to be born will do more-for example, to negotiate contract terms, or to judge whether you should sue.

This automated technology will bring legal services to the masses. Many people who should have hired a defense attorney to deal with business matters or personal disputes could not afford the cost. You can rely on computer software when you want to fight your mortgage lender, draft a contract to start a small company, or want to take a lawsuit to win the child's upbringing.

Although legal automation is a benefit for those who cannot afford to pay a lawyer, that is bad news for lawyers. The legal profession is now in a slump, and law school is no longer the path to riches. Because the existence of software allows fewer lawyers to do more work, the price and demand for lawyers inevitably declines.

"In the Illinois where I live, you can see large tracts of unused land--because you no longer need to hire people to farm corn and soybeans as before." Larry Ribstein, a professor at the University of Illinois Law School, said he had written several papers on the Larry Libostaine revolution in the legal profession. "I see this soybean field now and I think of lawyers. ”

In my article on robots and doctors, I advocate that the profession of primary care physicians may survive a robotic invasion because their careers depend on essential human skills, such as the ability to lead face-to-face conversations. At first glance, the legal profession looks similar: The law is made by human politicians and administered by human authorities. When there is an argument, it is decided by the human judge and the jury. All aspects of the legal world-from the professional language involved in contracts and litigation to complex analytical inferences, and the reliance of court clerks and judges on the learned jurisprudence-come from the frontal lobes of the monsters we call lawyers.

If you look at the jobs that most lawyers do every day, you will find that many of them can be done by machines. The processing of language, complex logic, and the prediction of multivariate scenarios--computers are much more adept at these things.

Think of the most inflexible part of the legal process: drafting a commercial contract. In the career of a lawyer, he may have to draft thousands of contracts, many of which contain a lot of repetitive content. Now, several legal technology companies have written programs that can automatically generate these documents. The software works much like TurboTax tax software, asks you a series of questions, and then uses branching logic to delve into specific areas. Matt Kesner (Matt Kesner), a leading information officer at the Fenwick & West, a pioneering law firm in Silicon Valley, told me that the document generation program helps customers save time and money. Last year, the law firm developed a system that automatically generates the documents needed to merge cases. "It reduces the amount of work we spend on an average of 20-40 hours in a few hours," Kesner said, "even in cases that require a lot of documentation, we can reduce the time it takes to draft files from a few days to a few weeks." ”

The meaning of electronic forensics software is also revolutionary. These systems can tap into a huge amount of material, such as all emails in a civil lawsuit, to find even a tiny bit of evidence. The simplest software is to search for specific keywords, but more complex systems can detect where lawyers might be interested. Once a novice lawyer has been doing this work all day for the first time as a deputy; now computers do it faster and at lower cost, but as well as humans do.

Now, human lawyers have the same advantage: the legal profession has always been skeptical about automation, and it does not apply in some ways at all. In order to establish his legal forecasting system, Daniel Katz needed a lot of legal documents. But such databases are not readily available. The court will issue a written verdict, but other materials-such as filing and motions-are kept in a database such as the Federal Court's electronic records Public access System (PACER), which would have to be paid for. Until the information is more readily available, human lawyers can get a slice of the pie.

But just as rules and regulations do not protect human pharmacists forever, lawyers should not feel safe under the pressure of today's flawed databases and software. Katz and other researchers are working on ways to extract and interpret historical data--a project called recap, with the goal of creating a pacer free mirror. In some specific areas of the law, data analysis has been widely used. A group of lawyers and technicians at Stanford University established the IPR Litigation Information Exchange Center (Intellectual Property Litigation Clearinghouse) in 2008, a project that tracked more than 100,000 patent and trademark lawsuits. Stanford opened it up last year, setting up an independent "legal machine" (Lex Machina), the most comprehensive collection of patent cases so far, and has helped overturn some of the basic tenets of the patent law field. For years, patent law lawyers have believed that courts in northern California State are more likely to be accused, while the eastern part of the Texas prefers plaintiffs, a notion that has made them accustomed to choosing a court of their own advantage. "But when we look at the records of the Northern California courts, we find that the plaintiffs won more--completely contrary to what we know," said litigious, chief executive of the Law machine, joshuawalker.

Stories like this-data analysis shows examples of human intuition errors-show the power of computer analysis. The "Legal Machine" project is still immature and no one has used a database to predict the outcome of a particular patent case. But you can still see how much convenience the system will make in you and the tiny, soft lawsuits. At the very least, you can use it to select your lawyer and decide whether or not to reconcile.

Walker thinks things like "legal machines" are designed to complement human wisdom, not replace humans. The database, he says, will make lawyers more adept at their jobs as more people become more staffed. This may be true, but it is also beyond doubt that these systems can systematically help clients decide whether to prosecute, and which legal institution to ask, and where to submit the case, which would reduce the use of counsel. All the legal researchers I've talked to have not objected to this, but some say that in the long run, automation can make it more fun to be a lawyer. Most computers can do things that lawyers hate to do. As Daniel Katz, lawyers can outsource the worst part of the job to machines so they can spend more time dealing with customer relationships and making sure that computers do what they do.

"You have to get this virtual line moving-you're the commanding master wielding the baton, directing the whole process," Katz said. Automation not only allows lawyers to get rid of drudgery, but also allows them to serve more clients. Also, you've only been able to serve a few customers at a high price, and now you can serve thousands of people through machines to help people who can't get legal services now.

If automation can take less money, bring legal services to more people, and reduce the human-law team, I think most readers will think it's a win. In the long run, this is likely to happen. The problem is that this step can be tough--a number of firms will fail, and a large group of rookie lawyers will be unable to find jobs, and the economic outlook for a huge industry is in decline.

But for all the professions I have written now, the prospects for the legal profession look relatively bright. It is true that lawyers will suffer, but the rest of us will benefit from them. "The law does not provide a job for lawyers," Katz said, "It's not a social function." It exists to solve problems for people-and if we can serve more people with fewer lawyers, I don't think this is an unreasonable way. ”

The next thing I want to explain is that I find similar trends in the scientific community. Perhaps the computer will soon uncover some of the basic mysteries of nature. Perhaps they are gradually replacing humans, should we be careful?