Artificial Intelligence is impacting society in ways we never imagined possible 50 years ago.
Machine-learning systems, neural networks, speech recognition, predictive analytics, and natural-language processing all fall under the broad category of AI. But, as evident in everything from video games, smart thermostats, navigation and Siri, to assistive robot technology in the operating room and AI in law, artificial intelligence is continually being reshaped by new developments and moving goalposts.
Every day AI touches the world in obvious and not-so-obvious ways. Adobe predicts that 31 percent of enterprises are expected to use AI over the next 12 months. AI gives computers the capacity to reason and apply logic along with specific qualities that include the ability to self-learn and act on that new knowledge, often at a super-human level. As with anything new, there is as much fear about the future of AI as there is excitement. Even so, at this stage of the game, the pros far outweigh the cons.
AI uses algorithms that discover patterns from data that’s been programmed into it and is used for future decision-making and predictions. From these patterns, AI solutions learn, much like humans learn from replicating a task or inputting data over and over again. For example, say you have a bit sequence like 1,2,1,2,1,2,1,2,1,2. If you (or your AI) can recognize the sequence of alternating 1s and 2s, then you can predict the sequence will continue in this manner.
In utilitarian software systems such as correcting errors in spelling or predicting what a user is going to type, giving users traffic and time estimates, or the best or shortest routes to take, machine intelligence is at work. The same is true for fully autonomous vehicles where advanced systems can control the vehicle and make all navigational decisions. Another critical application, AI in law, reviews documents and flags them as relevant to a particular case. Once a document is flagged as relevant, algorithms can quickly find other documents that are similar.
AI can augment human intelligence, deliver insights and improve productivity. The power behind AI is its ability to make decisions, analyze data, learn and gain new insights to make better decisions.
Think about it like this. If the carburetor in your gas-powered lawn mower starts running low on gas, it will draw in more to continue running. You didn’t make the decision to draw in more gas, the carburetor did. AI is similar. But, these decisions come with a caveat. Big data, and lots of it. Current AI can make decisions based on data that has been programmed into it. From that data, AI can often predict or conjecture a more thorough decision, faster, than its human counterparts.
AI is a machine with the ability to learn from patterns. One notable method of machine learning is what’s known as deep learning. Deep learning is a subset of machine learning which is a subset of AI. Currently, Siri and Amazon Alexa are the most familiar examples of deep learning, although Google and Netflix are not far behind.
AI uses algorithms to build analytical models. From those algorithms, AI technology can learn how to perform tasks through countless rounds of trial and error. Natural Language Processing (NLP) is another form of AI learning that gives machines the ability to read and understand human language. AI systems such as the one built by ROSS Intelligence utilize natural language processing to help analyze legal documents.
The basic types of AI are purely reactive. They cannot (yet) shape memories, make moral choices, or exercise free will. Reactive AI perceives a problem and acts on that perception. For example, take IBM’s “Deep Blue” – a chess-playing computer that defeated Garry Kasparov in the late 1990s. Although Deep Blue can identify each of the chess pieces on the chessboard and how each piece moves, it has no memory of past moves and ignores everything before the present move. Deep Blue can only react to where the chess pieces sit on the board at any given moment and then choose from possible next moves.
The same is true with applications on computers, tablets and phones that predict user actions and make recommendations that suit user choice.
AI is a tool that lets people rethink how we analyze data and integrate information, and then use these insights to improve decision-making. AI visionaries speculate that in less than five years, the ability for computers to converse will advance significantly, which will pave the way for a host of life-changing AI applications. It’s also thought that by around 2030, there will be a sweeping availability of AI technologies in a wide range of industries.
In areas such as research, security, regulation, health care and law, there exist tremendous opportunities. However, as with most transformative technology comes a period of apprehension. Thankfully, apprehension often also breeds excitement. What does the future hold and how will what we now know about AI change in the coming years? Most AI experts think the best is yet to come.
For instance, in the field of law, lawyers can take advantage of AI’s cutting-edge technology to perform network analysis, text processing, data mining, computational argumentation and more, allowing them to focus on the more complex aspects of practicing law. AI also opens the door for career lawyers who may never make it more than a few years in the profession because of the tedious drudge work.
Among the breakthroughs:
With the emergence of big data, an increase in the size of the information community, and the fusion of data and information, the current field of AI has changed profoundly since the term was first coined in 1956. AI has just entered a new stage: AI 2.0, where one of the most apparent features is that AI is enabled with intelligent perceptual capabilities, including visual perception, speech perception, auditory perception, and perceptual information processing and learning.
We already see this in self-driving cars, Amazon’s Alexa and Apple’s Siri. Where once technology only responded to specific questions and delivered programmed responses, now it is much more advanced – almost as if “it” has a personality. Ask Siri for the closest beauty shop to get a haircut, and she may reply that you look good just the way you are.
Smart cars and drones, and products that help you search the web for information, read audio books, get sports scores and schedules for traffic and weather, and control your lights and thermostats, now perceive what we want or need; influencing the way we live and interact. There’s no disputing that the more capable of perception and motion AI becomes, the easier it will be to integrate it into our daily lives.
All said, embracing an AI-friendly mindset in your law firm is a bit more complicated than simply changing your attitude or examining the many benefits. Knowing how and when to invest in AI requires due diligence and a lot of critical analysis.
One of the most considerable advantages of an AI solution in your law firm is that it does not require sleep, lunch breaks, or vacation time in order to function. AI can also continuously perform the most tedious and boring tasks without getting tired or putting in overtime when on a deadline. AI can scour thousands of documents in super-human speed and arrive at a result with fewer errors than its human counterpart. However, in the near foreseeable future, AI will no doubt continue to need the collaboration of humans.
To remain competitive, no discussion on AI in law would be complete without mentioning Ross Intelligence – an advanced legal research tool that harnesses the power of artificial intelligence to make the research process more efficient. Although there is skepticism about what is realistic – what AI can and cannot do – the fact remains that the collaboration between complex algorithms and human wisdom appears inevitable. At ROSS, we think that’s a good thing, especially when meeting your strategic business needs.
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