Computers have grown smarter and increasingly are doing tasks that require a higher level of awareness, reasoning, and learning. You can see it today in:
- Self-Driving Cars — Cars that drive themselves or assist drivers in avoiding accidents.
- Investment Advice — Vanguard Group, an investment firm, employs artificial intelligence to offer their customers detailed, tailored investment advice.
- Customer Service — Virgin Trains, a railroad in Great Britain, uses artificial intelligence to provide basic customer service responses. The technology uses natural language processing to gauge meaning and mood of customer emails, and then responds to the customer. Virgin Trains estimates this reduces their labor efforts by 85 percent.
- Campaign for President of the United States — Donald Trump's campaign credits their fundraising success and targeted ad campaign success to machine learning. By using cognitive processes to parse their data, the Trump campaign claimed they sent out more than 100,000 successful and targeted advertisements to voters each day. The Trump campaign eventually used their data operations to make targeted decisions about where to travel, how to do fundraising, and even choose rally locations as well as the topics of speeches. This allowed the campaign to choose where to spend money more effectively.
- More Effective Government — At least five agencies of the U.S. government are experimenting with something called process robotics — a type of smart automation that could handle rote tasks and free up federal workers to handle more mission-based work. These "process bots" can work 24 hours a day doing highly repeatable rules-based tasks such as processing, structuring, and extracting information from incoming emails and attachments; making decisions about how to process the information; and more.
For decades, we have been living in an age of machine automation where a basic form of artificial intelligence does simple, manual tasks like manufacturing, and more recently, low-value tasks such as data manipulation. Building computers capable of learning and reasoning is not a new area of technology. It has been the subject of much research and development, and many articles, movies and books. What is new is how fast this technology has advanced and how quickly it is starting to change our lives and our jobs. Such artificial intelligence has many names and facets: robots or bots, cognitive bots, cognitive computing, robotic process automation, machine learning, and more.
The technologies for how computers learn, remember and reason are combining with advanced analytics of big data to drive an unparalleled transformation in how we work and do business. Typically, basic artificial intelligence has been driven by rules and logic to perform simple tasks, but this is now being combined with more than just rules. Using machine learning and natural language processing, artificial intelligence can do much more complex tasks.
Computers can now intelligently analyze and organize information from not only just text, but also from images, audio and video. Technologies have even advanced to the point where they can provide guidance and advice — this is where this technology gets even more interesting and possibly frightening in its pace. This technology is not just sitting on the shelf. It seems to be everywhere and growing fast.
Learn Understand and Reason
There are a myriad of processes and technologies that make up what is artificial intelligence. However, not everyone agrees about what "intelligence" really is. How it is defined and achieved is a complex argument beyond the scope of this article. Suffice to say, computers must learn, understand, and reason. Below is a brief description of some of the current technologies and ideas involved with making computers work intelligently:
- Learning — In the past, computers had to be programmed exactly what to do. This was rote learning. Machine learning is a means by which computers can adaptively learn without being told exactly what to do. Computers are given algorithms that allow them to analyze lots of data and recognize patterns, then learn and make independent decisions based on that experience.
- Understanding — Understanding and language are the key to learning. Natural language processing (NLP) is combination of technology and linguistics that allow computers to understand and interact with humans and their languages. The goal of NLP is not only to communicate with humans in person, but to aid in the analysis and understanding of large bodies of written and spoken materials.
- Reasoning — Computers will need the ability to apply reason and analysis to what they learn. Automated reasoning combines technology and mathematical logic to help computers apply reason using such techniques as proofs, inductive, and deductive reasoning. Another method that helps computers solve problems is Knowledge Representation and Reasoning (KR). Instead of building understanding from the basics and building up, KR builds understanding from the top down by giving the computer only what it needs to know to act with intelligence.
Intelligent Computing is Already in Law Firms
Sensing the potential risks that new intelligent technologies pose to their practice, some law firms are proactively taking the initiative to get ahead of the curve. According to a March 19, 2017 article in the New York Times, large firms are making investments in understanding intelligent computing to adapt their practice and to exploit the advantages of these technologies. Firms are not only keeping an eye on emerging technology, but are also making investments in legal technology startups. Some basic examples of intelligent technologies that have already found their way into the legal industry:
- Document Search and Analysis — Sorting and analyzing unsorted and unstructured documents is easily be done by intelligent computer technology. What might take reviewers months to review could take intelligent technology minutes. That is a hard advantage to ignore. According to a 2016 study done at the University of North Carolina School of Law, basic document review is already being automated at some large law firms where only 4 percent of attorney time is now spent on document review.
- Legal Research — the cornerstone of law practice is legal research. Intelligent machines can now do basic legal research quickly, allowing lawyers to try more complex and detailed search variations to greatly enhance their research.
- Writing Contracts — intelligent computers are now writing legal contracts. According to a New York Times article, machines are being taught the basics of contract law and are successfully being used to create contract language.
However, the question is: can an intelligent computer can do the work of an attorney? The answer is not a clear yes or no. As intelligent computing makes advancements into the law firm, the fear is attorney jobs will be eliminated. However, it is more likely that technology will replace or enhance specific tasks, not whole jobs. Many believe intelligent computing will allow attorneys to focus on more complex and higher-value work and achieve greater results. Law firms will adapt to this changing work environment, and these new technologies will likely enhance and change how lawyers work rather than replace them. It will not make attorneys extinct, but merely provide more technology to help solve problems.
It is more likely that intelligent computers and humans will adapt to work together. As an example, in 1997 Chess Grand Master Gary Kasparov was beaten by IBM's Deep Blue computer. It was touted as the death knell for chess grand masters. However, today chess teams comprised of both intelligent computers and humans are working together to play competitive chess. As in that situation, we are more likely to grow, adapt and work with these new technologies. There is even research going that is working to create a digital mesh so human brains can work directly with intelligent computers.
We are at the beginning of a new machine age. Intelligent computing is being successfully applied to many areas of manufacturing, banking, medical, investing, and legal work, and it will only grow. This technology is evolving at an exponential pace and the direction is obvious and clear — it is not a question of whether computers will be intelligent, but how fast we can adapt.
Hugh Son. "JPMorgan Software Does in Seconds What Took Lawyers 360,000 Hours." Bloomberg Markets, February 27, 2017, https://www.bloomberg.com/news/articles/2017-02-28/jpmorgan-marshals-an-army-of-developers-to-automate-high-finance
Dana Remus and Frank S. Levy. "Can Robots Be Lawyers? Computers, Lawyers, and the Practice of Law." November 22, 2016, https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2701092
Steve Lohr. "A.I. Is Doing Legal Work. But It Won't Replace Lawyers, Yet." New York Times, March 19, 2017, https://www.nytimes.com/2017/03/19/technology/lawyers-artificial-intelligence.html
The Digital Industrial Revolution, TED Radio Hour, April 21, 2017, www.npr.org/programs/ted-radiohour/522858434/the-digital-industrial-revolution
Samantha Ehlinger. "The Little Bots That Could." FedScoop, November 21, 2016, https://www.fedscoop.com/the-little-bots-that-could/
Gideon Lewis-Kraus. "The Great A.I. Awakening." New York Times, December 14, 2016, https://www.nytimes.com/2016/12/14/magazine/the-great-ai-awakening.html?_r=0
Cade Metz. "It Begins: Bots are Learning to Chat in Their Own Language." Wired Magazine, March 16, 2017, https://www.wired.com/2017/03/openai-builds-bots-learn-speak-language/
Jim Kerstetter. "Tech Roundup: Will Robots Replace Lawyers?" New York Times, March 20, 2017, https://www.nytimes.com/2017/03/20/technology/robots-lawyers-automation-workers.html
Daisuke Wakabayashi. "Meet the People Who Train the Robots (to Do Their Own Jobs)." New York Times, April 28, 2017, https://www.nytimes.com/2017/04/28/technology/meet-the-people-who-train-the-robots-to-do-their-own-jobs.html
Harry Surden. "Machine Learning and Law." Washington Law Review, March 2014, https://digital.law.washington.edu/dspace-law/handle/1773.1/1321
Betsy Klein. "Kushner explains how he led Trump to victory." CNN, November 22, 2016, http://www.cnn.com/2016/11/22/politics/jared-kushner-donald-trump-campaign/
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