Steven Niederer, a biomedical engineer at the Alan Turing Institute and Imperial College London, has a cardboard box full of 3D printed hearts. Each is modeled after the actual heart of a person with heart failure, but Niederer is more interested in creating detailed replicas of human hearts using computers.
These “digital twins” are the same size and shape as the real thing. They work the same way. But they only exist virtually. Scientists can perform virtual surgery on these virtual hearts to determine the best course of action for a patient’s condition.
After decades of research, models like these are now entering clinical trials and being used for patient care. The ultimate goal is to create digital versions of our bodies—computerized copies that could help researchers and doctors figure out our risk of developing various diseases and determine which treatments might work best.
But budding technology will have to be developed very carefully. Read the full story to find out why.
— Jessica Hamzelou
This story comes from the upcoming issue of MIT Technology Review, which launches on January 6 – it’s all about the exciting breakthroughs happening in the world right now. If not yet, subscribe get future copies.
This is where the data to create artificial intelligence comes from
AI is all about data. It takes reams and reams of data to train algorithms to do what we want, and what goes into the AI models determines what comes out. But here’s the problem: AI developers and researchers don’t really know much about the data sources they’re using.
The Data Provenance Initiative, a group of more than 50 researchers from academia and industry, wanted to fix that. They wanted to know very simply: Where does the data come from to create artificial intelligence?
Their findings, shared exclusively with MIT Technology Review, show a troubling trend: AI data practices risk overwhelmingly concentrating power in the hands of a few dominant tech companies. Read the full story.
— Melissa Heikkilä