When IBM’s advanced artificial intelligence program Watson beat Jeopardy champion Ken Jennings in 2011, it was an impressive feat for a computer–but still, it was only processing information that humans already knew in order to answer trivia questions.
As IBM attempts to turn Watson into a new line of business and make it useful in a wide range of industries that are dealing lately with an overwhelming amount of data, it’s now working to push the software, which excels at learning and interpreting human language, forward into the realm of the unknown.
“It’s not giving answers that people know anymore, it’s pointing people in directions that they should investigate,” says IBM Watson group vice president John Gordon. “We’re talking about a computing system that inspires people.”
At an event in New York today, IBM showed off the ways some of its early customers are using the Watson “Discovery Advisor” in research, development, and innovation, especially in the realm of biotech and life sciences. Watson’s aim is to speed up discoveries by teams of researchers by, for example, scanning and interpreting millions of scientific books, articles, and data points–far more than any person’s brain could analyze–and generating new hypothesis or leads that might be fruitful to investigate. Or, as Gordon puts it, Watson gives researchers “smarter hunches.”
Scientists at the Baylor College of Medicine and IBM Research have already used Watson to discover new pathways to cancer therapies, which they reported in a study presented at an academic conference this week. Watson looked closely at 70,000 scientific articles on a protein, called p53, that’s involved in more than half of all cancers. From its analysis, it picked out 6 different proteins that might function as a switch to turn on and off the p53 function–and therefore might be possible good targets for new drugs and cancer therapies. For comparison, says IBM research scientist Scott Spangler, human beings have only discovered about 1 new p53 target a year over the course of a decade.
Drug companies, too, which are struggling today to develop new commercial drugs, are some of the earliest users of Watsons predictive capabilities. Sanofi is using Watson to look through the research literature and its own data to find new uses for its existing drugs on the market. And Johnson & Johnson has developed a system that analyzes clinical studies to compare the efficacy and safety of different treatments.
Soledad Cepeda, Johnson & Johnson’s director of epidemiology, used the example of back pain, for which there are 27 treatments studied in more than 3,000 clinical trials. “[Analyzing this] is slow, it’s tedious, it’s expensive, and it’s prone to errors,” she says. “Now imagine we can teach Watson to do that for us. So instead of six months, Watson can do it in minutes.”
Johnson & Johnson has been working to train Watson to read each study, put it in context, and pick out how many patients dropped out of the study or trial due to side effects or ineffective results. If Watson can give researchers all of this comparative data, rather than them combing through thousands of papers, it would allow researchers to come up with better questions to ask and directions to explore, Soledad says.
But it’s not always easy for Watson to do this–it takes setup and new skills for it to learn. For example, in Johnson & Johnson’s work, in the studies Watson was analyzing, authors often reported the key data in the form of flow diagrams. So Soledad and her team had to first teach Watson to correctly read flow diagrams of varying levels of complexity and design.
Watson’s earliest discovery applications have been in biomedical research, but the company hopes it will prove useful in a wide array of fields where the data available to analyze is growing faster than even the world’s top experts are capable of comprehending, such as law enforcement and finance.
At the event, Roberto Villasenor, chief of police for the city of Tucson, Arizona, detailed an open case of young child who went missing from her home. Over two years of investigating, the police have generated 15,000 pages of lab reports, records, and warrants, 25,00 pages of interviews, 4,000 pages of transcribed wiretaps, and much other data. His department has already worked with IBM on software that integrates different police databases to make it easier for investigators to make connections between disparate data sources. But he hopes systems like Watson will eventually go further–actually aiding investigators in combing through data, making subtle connections, and generating new leads in difficult cases.
The most public demonstration so far of Watson’s “discovery” abilities has been in the form of Watson, the Chef. IBM has put Watson to the task of learning how to cook, and then creating creative new recipes that match surprising foods in tasty but unexpected combinations. It debuted this capability at a food truck at SxSW this year, but has also been working with the Institute of Culinary Education and Bon Appetit magazine to refine and stretch Watson’s cooking skills (It’s still learning though, since no one wants to eat a recipe that calls for “one-inch of paprika,” as Watson once suggested early on.)
Bon Appetit is now beta testing a consumer app that allows readers to input an ingredient and desires and have Watson generate suggested recipes. It held a Watson recipe contest this summer–the winner of the “best use of Watson as a creative discovery tool” was a “Roasted tomato and mozzarella tart” recipe.
Cooking isn’t like curing cancer, of course. But to IBM it’s most about getting the public excited about its advances. “Much the same way that Jeopardy helped people understand systems that can answer questions using natural language, Chef Watson is a way for us to understand how these new systems can be used in our everyday lives,” says IBM senior vice president Mike Rhodin.