It was the constant stories about self-driving cars that made machine learning the breakthrough tech topic of 2015. Five years ago news stories talked about robots that could do repetitive tasks, but they said real complex tasks requiring seasoned judgement—like driving a car—were years away. Then cars started driving themselves. It turns out that computers are getting smart faster than most predicted.
Machine learning, a subset of artificial intelligence, is an effort to program computers to identify patterns in data to inform algorithms that can make data-driven predictions or decisions. As we interact with computers, we’re continuously teaching them what we are like. The more data, the smarter the algorithms become.
Pedro Domingos, author of the The Master Algorithm, said machine learning is the new switchboard for Higher Education. Machine learning is the new weapon attacking cancer, climate change, and terrorism. It’s the new infrastructure for everything.
In the spring of 2014 data privacy (and over-testing) concerns rose to the forefront of the US K-12 dialog. By October more than 100 EdTech vendors had signed a data privacy pledge.
In 2015, our SmartParents series argued that data is key to personalized learning and that parents should have access to student data and should be able to decide with whom to share portions of that data—requiring policymakers to embrace personalization and privacy.