You may never have heard of diabetic retinopathy, but this nasty condition is the fastest-growing cause of blindness in the world. It poses a risk to the 415 million people with diabetes—nearly 5 percent of the world’s population. The condition occurs when chronically high blood sugar damages the tiny vessels that provide blood to the retina. People who suffer from diabetic retinopathy can begin to experience distorted vision and ultimately go blind. And here’s the even deeper tragedy: Diabetic retinopathy can be prevented; it just needs to be detected early.
With so many people at risk of this condition, the world simply doesn’t have enough ophthalmologists available to diagnose them, especially in developing countries. But, a couple years ago, a clever team at Google, using computers and code, decided to test the latest deep learning techniques to identify the condition. The results—published in late November—were inspiring. The deep learning algorithm was able to screen for the disease just as accurately as doctors in the field. What that means is we may eventually be able to put the ability to diagnose this disease in the hands of anybody with a smartphone—and save millions of people from going blind.
Arthur C. Clarke once said that “any sufficiently advanced technology is indistinguishable from magic.” Technology is now on the cusp of taking us into a magical age, in which machine learning can prevent blindness, translate any language with expert skill or even save endangered species from extinction. Machine learning is beginning to help us solve problems today that we simply couldn’t solve on our own.
And the most exciting thing of all? These breakthroughs are just the start of this transformation. Just as the internet changed our world 20 years ago and smartphones did 10 years ago, we are now entering a decade in which machine learning will come to define how we interact with technology and the world around us—and how technology helps humanity thrive.
Silicon Valley is occasionally criticized for claiming it will make the world a better place while delivering only incremental benefits. But the truth is, technology can only solve the problems to which is it applied—it’s up to the next wave of innovators to decide whether that means using algorithms to dramatically cut energy waste or for more trivial pursuits. It’s up to all of us who work in the tech sector to orient technology and the benefits of the machine learning age, toward the challenges that most deserve our attention.
It’s vital that we develop technology that’s attentive to everyone’s challenges, not just those of the wealthy, the empowered, or those in our immediate bubble. That’s why it’s important to democratize the tools we build so that you don’t have to work in Silicon Valley to get access to the most powerful technology, from search to satellite mapping to a smart assistant offered in multiple languages. At Google, we’ve made our cutting-edge machine-learning algorithms open source, available for everyone. Whether you’re a student from Hyderabad, India, a scientist from the Research Triangle in North Carolina or a farmer in Japan, you’ll have the opportunity to use the latest computational breakthroughs to help tackle the problems you want to solve.
Amid this hopeful picture, people have legitimate concerns about whether advances in technology like machine learning will worsen inequality. With many economies just barely returning to the levels of prosperity they enjoyed before the Great Recession, the thought of anything that may point to renewed job losses is rightfully troubling.
But there is no reason advances in machine learning have to cost society more jobs than they create. History has actually shown us that technological progress tends to lead to greater prosperity, more jobs, safer workplaces and higher standards of living. That’s what happened globally during the Industrial Revolution as people transitioned away from agriculture to industry—a process that is still occurring in developing countries. And it’s what happened in the U.S. and Europe during the boom years immediately following World War II, when the spread of technologies like refrigeration, automatic telephone switches and airplane travel forever changed our economies and vastly improved the lives of nearly everyone. Although this meant fewer milkmen, phone operators and ocean liner crews, job growth actually accelerated during this time.
Still, there are steps we can take now to ensure our societies are sufficiently prepared to take advantage of technological growth rather than be disrupted by it. That includes supporting digital skills education and career retraining to prepare people for the jobs of the future; as a start, in November Google made a multimillion-pound commitment to provide five hours of free digital skills training for every person in the U.K., set to take place throughout this year. Since 2011, we’ve built six campuses throughout the world solely to give local innovators and advocates a place to congregate, learn from one another and create the jobs of the future. To ensure the gains from technology don’t lead to greater inequality, all governments and businesses should strengthen social safety nets and expand corporate benefits like equal pay and family leave.
We are fortunate to be living in a time when technology has the potential to fundamentally improve the way people work, learn and live—no matter who they are, where they are or what they do. It can make us all smarter, happier and healthier, on a scale we’ve never seen before in history. But it’s up to all of us—tech companies, governments, business, civil society—to work together to create the conditions that allow innovation to flourish. Only then will we see the progress our societies deserve, and demand. Only then will we see magic.
Eric Schmidt is the executive chairman of Alphabet, the parent company of Google.