Daily Double: Water and Analytics

Posted on February 17th, 2011 by

Millions of viewers tuned in to Jeopardy! this week to watch Watson, a computing system built by IBM researchers that rivals a human’s ability to understand human language and answer questions, compete against Jeopardy! record holders Ken Jennings and Brad Rutter. In preparation for the match, Watson, named after IBM founder Thomas J. Watson, ingested more than 200 million pages of content. It not only understands English, it knows how real people use it in conversation.

The real-world applications for this deep QA (question and answer) technology are practically limitless. A computer system that can collect, process and understand natural language-based data could prove revolutionary in a variety of fields, including environmental science. Personally, I’m excited by the possibilities this technology holds for the water management industry.

Many government agencies and researchers warn that large parts of the world could suffer significant water shortages in the not-so-distant future if we do not make dramatic changes now. While the global population grows and demands on our water supply increase, the supply remains finite.

There is much to be done in the way of better managing this precious resource. As the adage goes, “you can’t manage what you can’t measure,” and while an abundance of water data exists – for example, the United States Geological Survey collects real-time water data from various sources nationwide – gleaning useful information from that data poses tremendous challenges. But with access to a system like Watson, utility managers could make more informed decisions based on available data, supported by deep analytics – and do so through a natural language interaction.

Another aspect of water management I’m particularly interested in is the notion of “citizen science” – crowdsourcing, if you will. Science is no longer reserved for academics in white lab coats; it’s for anyone who takes an interest in the world around them. Take, for example,CreekWatch, an iPhone application we recently launched, that allows everyday people to help monitor local watersheds. They don’t need degrees in environmental science, and the only necessary equipment is an iPhone (and we’re working on a version for Android). The user provides just a few key pieces of data: how much water is there; how fast or slow is it moving; and how much trash or pollution is in the water. Users can also upload photos to include with the report and the data is shared with local water control boards. Collectively, CreekWatch provides important data that simply would not otherwise be available, helping water managers make smarter decisions both in real time and over the long term.

And we’ve only begun to unlock the value hidden in this kind of data. As the public takes a more active role in data collection, deep QA technology will be crucial in terms of having a reliable, fast and easy way to sift through and find answers in massive amounts of data from disparate sources.

Watson is a system that thinks and learns. With this capability – unprecedented in history – Watson’s analytics technology analyzes massive amounts of data and arrives at the correct answer to a staggering variety of difficult questions. Using sophisticated analytics to understand the meaning and context of human language, Watson can rapidly analyze information and find precise answers in under 3 seconds – that’s the ability to sift through an equivalent of about 1 million books or roughly 200 million pages of data and provide instant answers to questions.

As IBM celebrates its 100 year anniversary, we’re ushering in the eras of big data and citizen science side by side; both present enormous potential and significant challenges. Watson represents the future of analyzing the mountains of data in completely new ways at a faster pace than ever before — a breakthrough in human to computer communication that will allow computers to be even more helpful to humans moving forward.

Make no mistake: Deep QA won’t ever replace water managers or any other decisionmakers; there’s simply no way a machine can match the knowledge and ability to reason of a smart, experienced human being. But the technology can unquestionably extend our capabilities and help us perform better.

After all, it was human ingenuity that made Watson possible. And I hope that soon we’ll be harnessing these amazing new capabilities to improve industry as well as society.

Written by Cameron Brooks, IBM

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