For years, scientists have been heralding the artificial intelligence revolution. We’ve been able to program robots and vacuums, play chess, and even win at Jeopardy. But, before now, technology has not been able to produce artificial intelligence that can do one of the most fundamental human skills: communicate. The emergence of natural language generation is changing all of that.
Natural language generation is artificial intelligence that mimics the way humans communicate. In real-time, the technology reviews vast sets of unstructured data from multiple sources, analyzes it, draws conclusions, and ultimately generates a natural language report summarizing the key findings. The reports are told in a compelling narrative that could have been written by a human.
NLG platforms can be tailored to analyze data like industry experts (whether that is doctors or weathermen) in order to generate insightful reports. The technology can even identify what information is important and then tailor the language based on audience. For example, imagine if you are visiting a loved one in the hospital. All of his or her medical information is in a medical chart at the foot of the bed, but you don’t understand the technical terms or abbreviations. NLG platforms could review the medical chart, and generate a report for you (a non-medical professional) in layman’s terms to explain your loved one’s health: from diagnosis to treatment.
More and more data is being generated every day; and the lack of experts with the ability to analyze this data is already becoming apparent. Gartner (News - Alert) forecasts that by 2020, about 1.7 megabytes of new information will be created every second for each person on Earth. But less than 0.5 percent of data is ever analyzed; much of this due to the lack of experts. According to McKinsey, the United States alone faces a shortage of 140,000 to 190,000 people with analytical expertise and 1.5 million managers and analysts with the skills to understand and make decisions based on the analysis of big data.
Training NLG platforms to think and act like experts helps alleviate this burden. Once the process of capturing the experts’ analytical skills and expertise in NLG platform algorithms is completed, they can be liberated from having to spend their days analyzing data. The best and brightest will be free to do what they are trained to do – engineers to build, doctors to heal, scientists to discover.
In an age where corporations are constantly competing in new spaces, and there’s an inability for many industries to continue their growth trajectories on the back of human capital alone, AI and NLG platforms provide much-needed solutions. Fortunately, companies are investing in these technologies. Since 2011 venture capital investments in companies developing and commercializing AI-related products and technology have exceeded $2 billion and tech companies have invested billions more acquiring AI startups.
Already, NLG platforms are being incorporated across industries. Take the financial sector as an example. Financial advisors spend significant time interpreting data to provide their investors; NLG technology is now being deployed to digest mass amounts of financial data and generate tailored reports that explain the performance of individual stock portfolios, saving hours and hours of analytical work. These financial advisors are liberated from having to spend their days reporting past performance and free to spend their time researching investment strategies and providing clients insights and advice.
NLG platforms are also helping utility companies, as companies are making large-scale investments in control technology and systems integration. NLG is acting as a virtual monitoring team in a control center, diagnosing issues, and generating content on everything from work orders to media alerts on outages. Some companies are even providing personalized usage reports for smart meter customers. In collaborating with the technology, employees are able to be more efficient with their time, and spend less of each day on mind-numbing monitoring or administrative tasks.
Matthew Gould is CSO and co-founder of Arria NLG (www.arria.com).
Edited by Alicia Young