Keeping blood sugar under control can improve outcomes in patients, but that's not always easy to do. Now, doctors are using artificial intelligence to help! Researchers are now using the technology to help people with Type 2 diabetes get their disease under control. "Diabetes is the leading cause of blindness," explained Mary Vouyiouklis Kellis, an endocrinologist at the Cleveland Clinic. "It can also affect kidney function. It can affect nerves, it can increase the risk for lower limb amputation."

Scientists, students, and community members came together last month to discuss the promise and pitfalls of artificial intelligence at MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) for the fourth TEDxMIT event held at MIT. Attendees were entertained and challenged as they explored "the good and bad of computing," explained CSAIL Director Professor Daniela Rus, who organized the event with John Werner, an MIT fellow and managing director of Link Ventures; MIT sophomore Lucy Zhao; and grad student Jessica Karaguesian. "As you listen to the talks today," Rus told the audience, "consider how our world is made better by AI, and also our intrinsic responsibilities for ensuring that the technology is deployed for the greater good." Rus mentioned some new capabilities that could be enabled by AI: an automated personal assistant that could monitor your sleep phases and wake you at the optimal time, as well as on-body sensors that monitor everything from your posture to your digestive system. "Intelligent assistance can help empower and augment our lives. But these intriguing possibilities should only be pursued if we can simultaneously resolve the challenges that these technologies bring," said Rus.

AI has already been used to improve disease treatment and detection, discover promising new drugs, identify links between genes and diseases, and more. By analyzing large datasets and finding patterns, virtually any new algorithm has the potential to help patients--AI researchers just need access to the right data to train and test those algorithms. Hospitals, understandably, are hesitant to share sensitive patient information with research teams. When they do share data, it's difficult to verify that researchers are only using the data they need and deleting it after they're done. Secure AI Labs (SAIL) is addressing those problems with a technology that lets AI algorithms run on encrypted datasets that never leave the data owner's system.

AI has already been used to improve disease treatment and detection, discover promising new drugs, identify links between genes and diseases, and more. By analyzing large datasets and finding patterns, virtually any new algorithm has the potential to help patients -- AI researchers just need access to the right data to train and test those algorithms. Hospitals, understandably, are hesitant to share sensitive patient information with research teams. When they do share data, it's difficult to verify that researchers are only using the data they need and deleting it after they're done. Secure AI Labs (SAIL) is addressing those problems with a technology that lets AI algorithms run on encrypted datasets that never leave the data owner's system.

The sequencing of the human genome laid the foundation for the study of genetic variation and its links to a wide range of diseases. But the genome itself is only part of the story, as genes can be switched on and off by a range of chemical modifications, known as "epigenetic marks." Now, a decade after the human genome was sequenced, the National Institutes of Health's Roadmap Epigenomics Consortium has created a similar map of the human epigenome. Manolis Kellis, a professor of computer science and a member of MIT's Computer Science and Artificial Intelligence Laboratory and of the Broad Institute, led the effort to integrate and analyze the datasets produced by the project, which constitute the most comprehensive view of the human epigenome to date. In a paper published today in the journal Nature, Kellis and his colleagues report 111 reference human epigenomes and study their regulatory circuitry, in a bid to understand their role in human traits and diseases.