collective unconscious of the smarter planet

A thoughtful piece by IBM’s David Ferrucci on the future of cognitive computing.

A year has passed since the Watson computer developed by my team at IBM Research defeated two all-time champions on the TV quiz show Jeopardy! A lot has happened since then. IBM launched a new business, IBM Watson Solutions, which is tasked with commercializing the technology. The Solutions team is developing versions of Watson for a number of industries, starting with healthcare and financial services. (Suggestions? Tweet to #WhatShouldWatsonDoNext?) Meanwhile, there’s plenty to do in IBM Research. We spent four years developing Watson for Jeopardy!, but that’s just the beginning of what Watson can become.

Watson is a first step in a new era of computing. There were two previous eras in the evolution of data processing machines: the tabulating era, which began in the late 1800s; and the computing era, which started in the 1940s. We’re now entering a period when machines will become increasingly capable of learning – graduating from moving bits around to understanding what they mean and how they apply to our lives.  These machines will be ubiquitous. They’ll be extremely powerful. And they’ll utterly transform the relationships between humans with computers. No longer will computers be simply data processing devices. Think of them as intelligent machines.

This new era of computing is being enabled in part by epochal shifts in technology that we believe will enable people to make the planet smarter in every dimension. Because the world is increasingly instrumented, we can gather immense amounts of information about everything from climate change, to the way transportation systems interact with one another, to the changes in society caused by government actions. Because computing devices are interconnected, all of that data plus many of the digital communications between people can be combined in ways that turn it into useful information. Using analytics tools, we can explore our troves of information and understand better how the world works, predict what will happen next and make better decisions.

With the Jeopardy! experiment, we showed that we could teach Watson how to gather information, how to interpret it in context and how to share insights with humans. Watson 2.0 and 3.0 will continue to expand this ability to learn. A future Watson will learn by analyzing the huge reservoirs of knowledge captured in human language, drawing inferences and engaging with humans to expand and validate its knowledge. Watson will help us grapple with information overload by enabling people to absorb, integrate, evaluate and apply otherwise unimaginably large volumes of data.  Think of it this way: A new era of computing will facilitate an intelligent dialogue between an individual and ALL other humans. These machines will make it possible for humans to collaborate in much more powerful ways than they can today.

Here’s a scenario that helps me picture the role that intelligent machines could play in society a decade or so from now: Today, governmental leaders in democratic societies make their decisions based on the best information they can gather, their own beliefs and political calculations. The problem is, the systems they deal with–everything from healthcare to national defense–are not only extremely complicated, but they evolve over time. These systems are beyond the ability of one person or even teams of people to understand, manage and predict. So we’re on the defensive. We are in reactive mode — waiting for things to break and then responding to local disruptions and often missing the big picture.

As a result, leaders and decision makers lack the information and analysis necessary to know what is truly the best course of action or the best policy for their city or nation. They end up making decisions that are primarily weighted towards personal beliefs and political considerations.

But what if they knew much more? What if computers could gather all manner of data about the complex systems of society, digest it, and make rational and well-documented predictions about the consequences of particular actions? Also, imagine that this data is open and available to all citizens where they can explore the implications of different policies as if exploring a simulated world.

In this scenario, leaders will have a crisp and more transparent understanding of what the best decision or policies might be. Every citizen can easily explore the simulated outcomes of well rationalized scenarios rather than rely on sound bites or politically motivated guesses. Leaders will be under tremendous pressure to do what makes the most sense.. In this way, intelligent computer systems can help us control our collective destiny.

There’s a lot of work to be done by scientists to get from where we are today to a future where intelligent machines can help transform the way societies, governments and businesses operate. At IBM, we’re improving the Watson technology in four key dimensions. We’ll extend the information that Watson understands from specific questions to problem-solving scenarios. We’ll shift from simple question-and-answer interactions with humans to rich conversations. We’ll enhance Watson’s ability to explain its results. And, finally, we’ll change how Watson learns. Instead of depending on human programs to feed it information in batches, Watson will be able gather information continuously and learn deeply about specific domains of knowledge.

It was a thrill to lead the team that created a software program that beat very smart humans at Jeopardy! But it’s even more thrilling to lead the team into a new era of computing.