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When I think about AI, my mind reminisces the scene from the televised wonders of the sci fi episodes of Star Trek, where Mr Spok asks a question to the onboard computer of the Starship Enterprise and the computer retorts back with an answer as a solution to a query. I used to be quite fascinated by this scene as a kid. Never could be imagine that dramatic changes in technology would one day be leading us to these formats of AI, which would be applicable to our way of life and our work. Every kid off the block like me used to get fascinated by this and really thought that it was all a lot of cool stuff.
The biggest example that we have similar to this is Apple’s Siri or Amazon’s Alexa, where we ask a question and the device, whether a computer or a mobile handset revert back to us with an answer. This is NLP or Natural Language Processing. This is just a simple example drawing a parlance to what we visualized or ideated about 4 decades back would eventually get into the reality mode. Now this is Artificial Intelligence and it has arrived big time and are making inroads eventually in our lives and our fields of work.
In the Legal Industry, Artificial Intelligence or AI has already started making inroads. Within the next 5 years we will see the cusp of a revolution in the practice of the law – in particular, by the in house lawyers. Needless to say that AI will become ubiquitous – an indispensable assistant to each lawyer. Those who will not adapt to this technology would be left behind or get severely lagging behind in the trade. Adaptation to AI would make the lawyers free to do the most 2 important things: thinking and advising.
Like many of us may be wondering what AI products are there available and of which particular use? In order to get into that we need first to understand what really is AI?
What actually is Artificial Intelligence?
AI is application of computers to teach them how to do reasoning and make decisions. That is called Cognitive Computing. Cognitive tools are trained vs programmed applications to complete tasks traditionally done by people, where the focus is looking for patterns in data and thus finding and providing results. Just like a research assistant who can browse through the stockpile of information and revert back on where and what is found. Why is this important? According to IBM, 2.5 quintillion bytes of data are being generated every day, where a quint is equivalent to 2,500,000,000,000,000,000 bytes. So the ability of a human being to review and comprehend that level of data is impossible.
Diving Deeper
The recent explosion in AI is due to a fundamental rule of technology : Moore’s Law.
In 1965, Gordon Moore, a scientist at Intel, made a prediction based on his observation that the number of transistors per square inch on integrated circuits had doubled every year since their invention. His law predicts that this trend will continue and growth in computer power will double roughly every 2 years while the cost of that computing power will go down. Simply put, more computers for less money. When coupled with the ever – lower cost of storing electronic data, you have the basis for the rapid rise in AI capabilities and availability. In fact, experts predict that spending on AI by companies will grow from $8 billion in 2016 to $47 billion, this year end which is by 2020. Up almost by 600%.
The reason for this huge spending in AI is simple: There is huge productivity gains and cost savings available from freeing humans from routine tasks those computers can handle, allowing people to focus on tasks add value, which essentially needs human intervention. More importantly, legal industry and departments must be ready to adapt to AI as a way of life. All premier MBA institutions like Harvard, MIT, Stanford, France’s INSEAD School of Business have added AI in their curriculum. As CEOs and CFOs become more accustomed to using AI, they will expect the other members of the C –Suite – including the general counsel and legal department – to follow suit. In house lawyers that embrace AI, will become more valuable to the next generation of CEOs and CFOs.
How it works?
At its core, AI is the science of teaching computers how to “learn, reason, perceive, infer, communicate and make decisions like as we humans do. The initial goal is called machine learning, where the machine, a computer begins to make decisions with minimal programming. Instead of manually writing rules for how the computer should interpret a set of data, machine learning algorithms (i.e. a set of instructions for solving particular problems) allow the computer to determine the rules itself. Beyond machine learning lays an even bigger goal, deep learning. Deep learning uses more advanced algorithms to perform more abstract tasks such as recognizing images.
Ultimately, with machine learning or deep learning, computers actually become better at their tasks with experience. Fundamental to this learning are 3 core processes of how cognitive computing works: 1) gather information, 2) analyze and try to understand the information, and 3) make decisions based on this understanding. As all lawyers know from their experience, this process is iterative and we become better the more times we undertake the task- especially if we are corrected and guided in our work by someone more experienced (just like being a young associate at a law firm). For the legal industry, it works exactly the same way with artificial intelligence.
You can give information to a computer about apples, bananas, and fruit in general, but on its own, it will never come up with the realization that apples and bananas are both fruit.”Connecting these concepts is where humans come in. For example, you can teach a computer to determine the relationship between words in a news article and a specific category by creating a set of training data, in this case a list of articles that are all given category tags. When the machine reads an article categorized as “sports” and sees the word football, it increases the likelihood that the word football predicts a story about sports. On the flip side, if the computer sees the word football in an article on politics (e.g., a political football), a vote will go toward the “politics” category. As the computer reads more articles, it can figure out which words are the strongest predictors of certain topics and weigh them accordingly. Over time, humans interact with the computer to correct mistakes and – in the instance of deep learning, the system self-corrects through a process called propagation. Regardless of how, all of these inputs work in combination until the computer learns the task with an acceptable degree of accuracy.
The computer must learn to understand what is relevant to the person searching and make suggestions that are usable in terms of narrowing the search results to a workable amount. Again, since machines have no inherent ability to limit the answers, this falls to the human teacher.
On top of the learning comes the interface, or how do people and the machine interact? For years, the most common way has been to enter information or queries into a computer, press Enter, and wait for the answer. These types of searches have run on Boolean logic, i.e., keyword searches. This means that each search is linear and bears no relationship to past or future searches. With AI, that changes as each search becomes part of the learning process and each search and answer (and correction if necessary) makes the machine that much better for the next task. Now you have the basis for the great leap forward in artificial intelligence, the legal industry, and specifically the potential for legal departments, i.e., the ability of machines to learn tasks that previously were done by lawyers and the ability of lawyers to extract pertinent information by either typing a query directly or by asking the machine to perform a task. While the latter is the most exciting and most sci-fis, the former is likely to be the most used method of AI for the legal industry, and specifically legal departments, for the foreseeable future. Moreover, the development of evermore sophisticated algorithms means the demise of relying on Boolean logic and keyword searches.
AI brings the ability to search for concepts (e.g., contract review and analysis for due diligence), to identify changes in tone of email communications (including looking for code words used to otherwise try to disguise the true nature of the conversation), and even to draft where the computer understands what needs to be drafted and prepares the document.
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