The Data Science Revolution

05/06/2015 06:04 pm ET | Updated May 06, 2016

The Huffington Post launched in 2005, but had it done so 10 years prior, it would have met a very different audience. By 2005, the average reader was digitally savvy -- spending lots of time online, communicating mainly through email and mobile phones, and engaging daily with social media. Yet this was before the likes of Siri, Google Now, and Waze came along. Today, we are more connected than ever, and rely on all kinds of smart machines on a daily basis. Computers may have started as linear tools used only by engineers for discrete tasks, but they have grown into versatile devices that support each of us in a distinct and exciting way.

And what's ahead is still more exciting. In the next 10 years, we believe that computers will move beyond their current role as our assistants, and become our advisors. With their help, we'll grapple with and solve some of the toughest issues facing the world today.

Once upon a time, computers were created with a singular purpose in mind: To churn through large data sets and find answers for specific questions, identifying the proverbial needle in a haystack of information. They still do this today -- only at drastically faster speeds and levels of complexity. The twin powers of data science and machine learning have allowed us to hand off a growing number of time-intensive and tedious tasks, freeing us up for more valuable pursuits.

Consider the Fitbit. We could certainly track our physical activity by hand, but we wouldn't do it as consistently and precisely as the wearable digital device programmed to do it for us. And consider self-driving cars. Moving the task of driving to a computer will liberate countless hours that we could spend on work, learning, or talking with friends and loved ones. It also brings the added benefit of safety, as computerized drivers don't get distracted by conversation, fatigue, or alcohol.

The benefits of digital tools are not limited to the few and privileged. Fishermen off the coast of Africa now use mobile phones to find the market with the best price to sell their catch. Students who once shared one textbook per classroom can now access a world's worth of information through the Internet.

Yet we believe that computers will do more. Their capacity for data analysis is ever increasing, and more data is now stored digitally. They will have broad societal impact, and help us to tackle pressing issues like health care and climate change.

"In the next 10 years, we believe that computers will move beyond their current role as our assistants, and become our advisors."

Over the next few decades, an estimated 60 million people per year will move into cities. There will be questions around traffic control, fuel, carbon footprint and city planning. Enter data science. In the next decade, the amount of information we will aggregate will grow exponentially -- car ownership, fuel consumption, average wait time at each traffic light. We will not be able to analyze all of this data ourselves, nor will we always know the right questions to ask. But with machine learning, computers will be able to look at the data en-masse, recognizing patterns and bottlenecks we wouldn't look for based on intuition. Countless relationships and dependencies will be uncovered, and city planning will be more scientific, solving some potential problems before they even arise.

Today, we are on the verge of having cars drive us automatically to an address we specify. In the next decade, computers will advise us with answers to questions about transportation that we may not know to ask.

Data science will also transform medicine. Already, IBM's Watson machine is crunching data from individual patient records to identify best courses of treatment. In the future, the impact of machine learning will expand to combat entire categories of disease. We imagine all biologic matter becoming sequenced eventually, with all resulting data residing in a database for computerized analysis. The insights that could arise from computer-powered pattern recognition in this kind of data are staggering. Our understanding of treatment and prevention may be transformed entirely. Today, we tend to look at data once a person is already ill, and medical studies focus on a specific sample set of patients once treatment is provided. Imagine expanding the scope of our analysis to include anonymous insights across an entire population, integrating data points that go beyond illness and include factors like environmental exposure, childhood nutrition and fitness habits.

We couldn't possibly guess, but what if anonymous data collected from fitness trackers led to insights around illness prevention? What if computer-powered pattern recognition solved the relationship between genetics and cancer? Imagine if, just like we donate money to cancer research, we could each choose to donate our anonymous Fitbit data to be mined for life-saving impact.

We believe that the goal of computers is to empower people by complementing their abilities. The next decade will bring just that. We will learn to build machines that go beyond executing tasks, and that will provide us with the kinds of insights that empower historic decision-making. It's an exciting time to be alive.

This post is part of a series commemorating The Huffington Post's 10-year anniversary through expert opinions looking forward to the next decade in their respective fields. To see all of the posts in the series, read here.


Eric Schmidt is the Executive Chairman of Google. Jared Cohen is the Director of Google Ideas & Advisor to the Executive Chairman. Together they are co-authors of the New York Times bestseller The New Digital Age: Transforming Nations, Businesses, and Our Lives.