Researchers from MIT and the MIT-IBM Watson AI Lab have developed a machine-learning accelerator that is resistant to the two most common types of cyber attacks. This development is a major leap forward in data and information security within devices using machine-learning applications. The chip can protect sensitive user information such as health records and…
The planetary boundary layer (PBL), the lowest layer of the troposphere, significantly influences weather near the Earth's surface and holds the potential to enhance storm forecasting and improve climate projections. A research team from Lincoln Laboratory's Applied Space Systems Group has been studying the PBL with a focus on deploying machine learning for creating 3-D…
Researchers at MIT and the MIT-IBM Watson AI Lab have developed an AI system designed to educate users on when to trust an AI's decision-making process - for instance, a radiologist determining if a patient's X-ray shows signs of pneumonia. The training system identifies scenarios where the human should not trust the AI model, automatically…
Researchers from MIT and the MIT-IBM Watson AI Lab have developed a system to teach users of artificial intelligence (AI) technology when they should or shouldn't trust its outcomes. This could be particularly beneficial in the medical field, where errors could have serious repercussions.
The team created an automated system to teach a radiologist how…
Researchers at MIT and the MIT-IBM Watson AI Lab have developed a method of teaching users when to collaborate with an artificial intelligence (AI) assistant. The model creates a customised onboarding process, educating users on when to trust or ignore an AI model’s advice. The training process can detect situations where the AI model is…
Researchers at the Massachusetts Institute of Technology and the MIT-IBM Watson AI Lab have developed an onboarding system that trains humans when and how to collaborate with Artificial Intelligence (AI). The fully automated system learns to customize the onboarding process according to the tasks performed, making it usable across a variety of scenarios where AI…
Researchers at MIT and the MIT-IBM Watson AI Lab have developed a system that teaches users when to trust AI and when to ignore it, and it has already led to an approximately 5% increase in accuracy during image prediction tasks. The researchers designed a customised onboarding process, which is when the user is familiarized…
Researchers from MIT and the MIT-IBM Watson AI Lab have developed a system that instructs users when to trust an AI system’s decision-making. In medicine, there might be instances like a radiologist using an AI model for reading X-rays where human intervention can make a difference. However, clinicians are uncertain whether to lean on the…
Researchers from MIT and the MIT-IBM Watson AI Lab have developed an onboarding process which teaches users how to effectively collaborate with artificial intelligence (AI) assistants. The system was designed to provide guidance to users and to improve collaboration between humans and AI. The automated system learns how to create the onboarding process by gathering…