The Wall Street Journal/Getty Images
UW CSE professor Pedro Domingos recently penned a column for The Wall Street Journal envisioning a not-too-distant future in which machine learning will enable us to build and control a digital model of ourselves, transforming how we approach everything from shopping, to job-hunting, to finding a mate.
From the column:
“Entrusting your money to a bank once seemed strange and risky. Similarly, entrusting all of your data to a company and letting its algorithms build a detailed model of you from it might seem to be an odd or even dangerous idea, but we’ll all soon take it for granted.
“A decade from now, your personal model will be more indispensable than your smartphone, and the company that provides it may well be the world’s first trillion-dollar business. So it is time to start getting acquainted with our digital alter egos—and what they’ll mean for our lives.”
Domingos points out that today’s digital models, such as those Google builds from our web searches or that Amazon bases on what we buy, fall short for two reasons: they are driven by the companies’ own profit motive, and they are built using incomplete data. He suggests a new approach, one in which we intentionally construct a complete digital model of ourselves and deploy it online for our own benefit.
“Today’s models don’t yet interact with us: You can’t tell them they’re wrong or ask them questions. Machine-learning algorithms are black boxes that only computer scientists can open up. But that will change as more of us realize how important machine learning is and demand a say in how it occurs,” Domingos writes.
Read the full column here. Check out our past coverage of Domingos and his new book, The Master Algorithm, here and here.