People struggling with their mental health are more likely to browse negative content online, and in turn, that negative content makes their symptoms worse, according to a series of studies by researchers at MIT. The group behind the research has developed a web plug-in tool to help those looking to protect their mental health make…

For all the talk about artificial intelligence upending the world, its economic effects remain uncertain. There is massive investment in AI but little clarity about what it will produce. Examining AI has become a significant part of Nobel-winning economist Daron Acemoglu’s work. An Institute Professor at MIT, Acemoglu has long studied the impact of technology…

One might argue that one of the primary duties of a physician is to constantly evaluate and re-evaluate the odds: What are the chances of a medical procedure’s success? Is the patient at risk of developing severe symptoms? When should the patient return for more testing? Amidst these critical deliberations, the rise of artificial intelligence…

If someone advises you to “know your limits,” they’re likely suggesting you do things like exercise in moderation. To a robot, though, the motto represents learning constraints, or limitations of a specific task within the machine’s environment, to do chores safely and correctly. For instance, imagine asking a robot to clean your kitchen when it…

Five MIT faculty members and two additional alumni were recently named to the 2024 cohort of AI2050 Fellows. The honor is announced annually by Schmidt Futures, Eric and Wendy Schmidt’s philanthropic initiative that aims to accelerate scientific innovation.  Conceived and co-chaired by Eric Schmidt and James Manyika, AI2050 is a philanthropic initiative aimed at helping…

Large language models (LLMs) that drive generative artificial intelligence apps, such as ChatGPT, have been proliferating at lightning speed and have improved to the point that it is often impossible to distinguish between something written through generative AI and human-composed text. However, these models can also sometimes generate false statements or display a political bias….

Chatbots can wear a lot of proverbial hats: dictionary, therapist, poet, all-knowing friend. The artificial intelligence models that power these systems appear exceptionally skilled and efficient at providing answers, clarifying concepts, and distilling information. But to establish trustworthiness of content generated by such models, how can we really know if a particular statement is factual,…

Daniela Rus, director of MIT’s Computer Science and Artificial Intelligence Laboratory and MIT professor of electrical engineering and computer science, was recently named a co-recipient of the 2024 John Scott Award by the board of directors of City Trusts. This prestigious honor, steeped in historical significance, celebrates scientific innovation at the very location where American…

Machine-learning models can make mistakes and be difficult to use, so scientists have developed explanation methods to help users understand when and how they should trust a model’s predictions. These explanations are often complex, however, perhaps containing information about hundreds of model features. And they are sometimes presented as multifaceted visualizations that can be difficult…

Machine-learning models can fail when they try to make predictions for individuals who were underrepresented in the datasets they were trained on. For instance, a model that predicts the best treatment option for someone with a chronic disease may be trained using a dataset that contains mostly male patients. That model might make incorrect predictions…