News You Can Use: A Robot Paralegal?

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The future is now! Dentons, LLP, the multinational firm boasting the largest number of lawyers in the world, apparently needs more of them — of the electro-mechanical sort. Dentons is financially backing a group of students from the University of Toronto who, as a class project, created an artificial intelligence to perform legal research. Code-named Ross, the AI uses IBM’s Jeopardy-nailing Watson to scour massive amounts of case law and legal docs in seconds to produce answers to legal questions. A Siri for lawyers, as the student-startup founders describe it.

Dentons is not new to embracing legal technology. It has its own legal tech lab, called Nextlaw Labs in California, where it apparently cooks up new legal technology projects. The student start-up, known as Ross Intelligence, Inc., will get access to the labs for their work, along with the financial investment from Dentons. Dentons, through Nextlaw, is also in the process of rolling out a cloud-based platform for lawyers, employing the IBM cloud and BlueMix Cloud Foundry technology. The idea is to create the foundation for developers to leverage and enter the legal tech market in order to create even better products for legal consumers to manage their work.

Right now, while the developers are refining and improving, Ross the Robot is focusing his intellectual powers on a database mostly comprised of U.S. bankruptcy law and “he” is being piloted not just at Dentons, but also at a few other elite firms in the US. His developers say that Ross is “learning” through action and responsive feedback – an exciting and frightening concept, to be sure. Pretty soon, I imagine, Ross will have the learned experience of a fifth year associate.

AI in the legal field is not unique to Ross – Microsoft’s Ventures Accelerator program is involved in another project that leverages AI to work through parts of complex contracts. RAVN Govern, powered by RAVN Systems’ Applied Cognitive Engine also uses AI to assesses  risk levels in contracts, and advise regarding the risk exposures before the contract is signed.

But no doubt, Dentons definitely has it all figured out. From the Denton’s release: “Technology is now and will continue to be a real differentiator in the legal profession,” explained Dan Jansen, CEO, NextLaw Labs. “The potential in companies like ROSS shows how the approach to solving client challenges is going to change. NextLaw Labs wants to be a part of transforming what is possible into a tangible offering in today’s legal market.” I, for one, welcome our new robotic paralegal overlords. Can I grab you a cup of coffee, Ross?

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Knowledge Graph: Google's New Search +Your Mind

They say that knowledge is power, and rightly so, particularly in the Digital Information Age (my term, FWIW). Access to information is important, but being able to leverage via machines the extra step that links the pure data to contextual relevancy is the current Holy Grail of Search. Pioneers in the digital knowledge game like Wolfram Alpha and Siri have been making extraordinary inroads in pairing correct answers to natural language questions. Semantic search – the ability to parse contextual meaning from a search inquiry by making connections across data sets – is the key to the next step in the evolution of search.

So, where is Google, the de facto King of Keyword Search, in all of this? Well, as of yesterday, right in the thick of it apparently. Google has introduced a major new refinement of its venerable Search Product called Knowledge Graph. Knowledge Graph appears to be a matrix of contextual connection behind the pure search terms that assist Google in showing results that make sense, as well as direct answers to queries right on the search results page. Instant results will highlight the answer Google believes you intended to find, as well as other possible answers to your question that make sense based on context – the connections between data points. The example from Google’s blog post debuting Knowledge Graph is the phrase “Taj Mahal”, which could be a monument, a Grammy award winning singer, a casino or the Indian restaurant down the street. Before, Google’s search would simply turn to its vast store of crawled data to find sites where the words “Taj” and “Mahal” appeared near each other, putting the sites that had the most clicks for those keywords at the top of the list. With Knowledge Graph, Google takes the next logical step by “guessing” the meaning you intend when you type “Taj Mahal” and presumptively returning relevant results. Pretty freaking cool.

To make this happen, Google is leveraging content stored in trusted sites, such as Wikipedia, Freebase, the CIA World Fact Book and other locales. Not unlike Wolfram Alpha, which turns to its own internal knowledge base comprised of data from official public or private websites, and systematic primary sources.

There are three main features of the new Knowledge Graph.  First, searchers will see different collections of results accessible via one click – click over instantly and tell Google which segment you are interested in researching. New summary info provides information on people, places and things right on the search page, obviating the need to click through to Wikipedia – good for quick bits of information, leaving you free to click through to get more detail if you need. Finally, Knowledge Graph takes it all one step further by providing the second tier information that users tend to look for after making their initial search. Google apparently is able to map those secondary searches and make the information easier to tap into, collapsing first and second searches down and improving search efficiencies. Google also shows other searches that people commonly made when searching for the same information. Google has accomplished the corralling of data in such a way that it can parse likely intent and direct searchers along the search path in a reliable fashion.

Is this all good? Well, not quite and definitely not for power searchers. Yet. Google’s new toy will work best with people, places and things and mostly likely with well-known people, places and things. More arcane and obscure information likely hasn’t been properly mapped yet, particularly since it appears Google’s tool depends on what lots of other searchers tend to do. Which raises an additional question regarding what lots of other searchers tend to do – if you are not your average searcher looking for not your average information, you might find the Knowledge Graph more hindrance than help at this point. However, I wholeheartedly applaud Google’s efforts (as well as Bing’s similar effort released earlier). There is definitely a place for instant, contextually-relevant results in everyone’s search plan. My sense is that it will REALLY get interesting when contextual, semantic search can delve the deeper recesses of data and make finer connections. Like the connections our billions of neurons make when we cogitate on a problem or try to recall key information. I can hear Majel Barrett’s voice now. Is the age of Artificial Intelligence upon us? Maybe. Just maybe.

 

Trapit Goes All AI To Bring You Your News

Any friend of Siri is a friend of mine. And Trapit is practically a relative! Startup Trapit is launching a beta version of its new “Pandora for News” service aimed at leveraging the same Siri Personal Assistant AI engine to bring relevant stories to you. The Siri engine is based on the largest AI project in U.S. history, CALO, which was funded by DARPA, a defense agency.

Using keywords or URLs, you can create a content “Trap” that will pull relevant news stories from 50,000 sources that are apparently free of spammers, link baiters, and content farmers. And, like any good recommendation system, the more you use (i.e. scan, click through, read full articles and share) the more the engine learns and the better the recommendations get. The engine also gets human by scanning news links in social networks which, presumably, have been selected and added by humans. If you don’t feel like creating your own Traps, you can scan other trending Traps.

Of course, the fine people at Trapit are no dummies and have definitely leveraged the visually appealing, blurb-box stylings of popular iPad apps that also seek to bring you the news. Think Flipboard and Pulse here. But with the added cool of recommendations and AI smarts. Of course, as I am a firm believer in relevance based browsing, I am definitely excited to give Trapit a thorough once over. Check it out and see if it solves a content firehose problem for you.