Eric Schmidt and Jared Cohen. Data Science Revolution

The Huffington Post was launched in 2005, but if it had been launched ten years earlier, it would have met a completely different audience. By 2005, the average reader understood the digital world, spending a lot of time online, communicating mainly via email, mobile phones and social services. That was before Siri, Google Now and Waze. Today, we are more than ever dependent on intelligent machines. Computers, which appeared as linear tools for performing discrete engineering tasks, have evolved into universal devices that help everyone in solving everyday tasks.

Ahead of us are even more exciting times.

We believe that in the next 10 years, computers will go beyond their current capabilities. From their current role as our assistants, they will move to the category of consultants. With the help of machines we will deal with the most difficult issues facing the world today.
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Long ago, computers were created with a special purpose. Handling of data files, solving specific highly specialized search, and not only tasks. They are doing this so far, only at higher speeds and difficulty levels. The power of data science and machine learning allowed us to delegate a large number of resource-intensive tasks, freeing us for more valuable lessons.

Consider Fitbit. We could, of course, track our physical activity manually, but we will not be able to do it as accurately and consistently as a specially designed and programmed wearable device. If you think about driving, it’s scary to think about how much time you could have freeing up for work, study, or socializing, using auto with autopilot. In addition, traffic safety would certainly increase, as the computer driver does not get tired, does not drink, and does not get distracted by conversations.

The advantages of digital tools are not limited to small and unique applications. Fishermen off the coast of Africa are currently using mobile phones to find where to sell their catch at a higher price. Students who once shared one textbook for the entire class can now access any information via the Internet.

However, we believe that computers will play an even bigger role. Their ability to analyze data is constantly growing, and every day more and more data is being digitized. They will have a wide public impact, and will help us solve urgent problems such as health and climate change.

According to some estimates, over the next few decades, traffic in cities will grow to 60 million people per year. This will entail issues such as traffic management, fuel shortages, increased carbon dioxide emissions and urban planning.

In the next decade, the number of summary information indicators will grow exponentially - car owners, fuel consumption, average waiting time at each traffic light, etc. We will not be able to analyze all this data by ourselves. But with machine learning, computers will be able to do this. Countless relationships and dependencies will be discovered, and urban planning will become more scientific, solving some potential problems before they even arise.

Data science transforms medicine. The IBM supercomputer (Watson) can already determine the best treatment courses for patients based on records in the case histories. In the future, machine learning will affect a wider range of diseases. We present all biologically significant data in databases for advanced computer analysis. The insight of computerized recognition techniques is already staggering. Our understanding of treatment and prevention can be transformed completely. Today we are reviewing data from already ill people and medical research is focused on a specific sample of patients being treated. Imagine expanding the scope of our analysis to a hidden understanding of the whole population and general data that goes beyond the scope of the disease and includes such factors as environmental exposure, baby food and fitness.

What if anonymous data collected from fitness trackers leads to an understanding of disease prevention? What if computerized recognition methods can find the genetic dependencies of cancer? Imagine that, just like money for cancer research, we could donate our anonymous FitBit data collected to save lives.

We believe that the goal of computers is to empower people by supplementing their abilities. In the next decade, we will learn to build machines that go beyond the simple execution of tasks. And this is an exciting time to live.

PS

This post is part of a series dedicated to the 10th anniversary of The Huffington Post .

Eric Schmidt is the executive chairman of Google. Jared Cohen is the founder and director of the Google Ideas Science Center and advisor to the executive chairman. Together they wrote a book - “A New Digital World: How Technologies Change People’s Lives, Business Models and the Concept of States”.

In the article, I deliberately used not translated data science and machine learning terms, since, in my opinion, a simple translation as data science and machine learning do not fully reflect their essence.