Prof. Sinan Aral speaks with Yahoo! Finance Live host Julie Hyman about President Biden’s executive order on artificial intelligence regulation. “This is big, it's bold, it's broad,” says Aral. “It has a number of provisions. It has provisions for safety, for privacy, for equity, for workers, for competition and innovation, and leadership abroad. And it really targets those foundation models, the big AI companies in terms of their safety and security standards.”
Joy Buolamwini PhD '22 writes for The Boston Globe about her experience uncovering bias in artificial intelligence through her academic and professional career. “I critique AI from a place of having been enamored with its promise, as an engineer more eager to work with machines than with people at times, as an aspiring academic turned into an accidental advocate, and also as an artist awakened to the power of the personal when addressing the seemingly technical,” writes Buolamwini. “The option to say no, the option to halt a project, the option to admit to the creation of dangerous and harmful though well-intentioned tools must always be on the table.”
Researchers from MIT and elsewhere have developed a transparency index used to assess 10 key AI foundation models, reports Ryan Heath for Axios. Heath writes that the researchers emphasized that “unless AI companies are more forthcoming about the inner workings, training data and impacts of their most advanced tools, users will never be able to fully understand the risks associated with AI, and experts will never be able to mitigate them.”
Tom Davenport, a visiting scholar at the MIT Initiative on the Digital Economy, writes for Forbes about how organizations are approaching generative AI. “If organizations are to succeed with generative AI, they need to increase the focus on data preparation for it, which is a primary prerequisite for success,” writes Davenport.
Graduate student Kaylee Cunningham speaks with CBS Boston about her work using social media to help educate and inform the public about nuclear energy. Cunningham, who is known as Ms. Nuclear Energy on TikTok, recalls how as a child she was involved in musical theater, a talent she has now combined with her research interests as an engineer. She adds that she also hopes her platform inspires more women to pursue STEM careers. “You don't have to look like the stereotypical engineer,” Cunningham emphasizes.
Graduate student Sarah Gurev and her colleagues have developed a new AI system named EVEscape that can, “predict alterations likely to occur to viruses as they evolve,” reports Erin Prater for Fortune. Gurev says that with the amount of data the system has amassed, it “can make surprisingly accurate predications.”
MIT CSAIL researchers have developed a new air safety system, called Air-Guardian, that is designed to serve as a “proactive co-pilot, enhancing safety during critical moments of flight,” reports Jace Dela Cruz for Tech Times.
Arvid Lunnemark '22, Michael Truell '22, Sualeh Asif '22, and Aman Sanger '22 co-founded Anysphere, a startup building an “‘AI-native’” software development environment, called Cursor,” reports Kyle Wiggers for TechCrunch. “In the next several years, our mission is to make programming an order of magnitude faster, more fun and creative,” says Truell. “Our platform enables all developers to build software faster.”
Curtis Northcutt SM '17, PhD '21, Jonas Mueller PhD '18, and Anish Athalye SB '17, SM '17, PhD '23 have co-founded Cleanlab, a startup aimed at fixing data problems in AI models, reports Alex Konrad for Forbes. “The reality is that every single solution that’s data-driven — and the world has never been more data-driven — is going to be affected by the quality of the data,” says Northcutt.
Axios reporter Alison Snyder writes about how a new study by MIT researchers finds that preconceived notions about AI chatbots can impact people’s experiences with them. Prof. Pattie Maes explains, the technology's developers “always think that the problem is optimizing AI to be better, faster, less hallucinations, fewer biases, better aligned, but we have to see this whole problem as a human-plus-AI problem. The ultimate outcomes don't just depend on the AI and the quality of the AI. It depends on how the human responds to the AI.”
MIT researchers have found that user bias can drive interactions with AI chatbots, reports Nick Hilden for Scientific American. “When people think that the AI is caring, they become more positive toward it,” graduate student Pat Pataranutaporn explains. “This creates a positive reinforcement feedback loop where, at the end, the AI becomes much more positive, compared to the control condition. And when people believe that the AI was manipulative, they become more negative toward the AI—and it makes the AI become more negative toward the person as well.”
Prof. Thomas Kochan and Prof. Thomas Malone speak with Boston Globe reporter Hiawatha Bray about the recent deal between the Writers Guild of America and the Alliance of Motion Picture and Television Producers, which will “protect movie screenwriters from losing their jobs to computers that could use artificial intelligence to generate screenplays.” Kochan notes that when it comes to AI, “where workers don’t have a voice through a union, most companies are not engaging their workers on these issues, and the workers have no rights, no redress.”
Researchers at MIT and elsewhere have identified key cell types that may protect the brain against Alzheimer’s symptoms, reports Sara Reardon for Nature. “Most Alzheimer’s research has focused on excitatory neurons, which relay electrical signals to activate other neurons,” explains Reardon. “But the authors found that the cells with reelin or somatostatin were inhibitory neurons, which halt neuronal communication. These inhibitory cells might therefore have a previously unknown role in the types of cognitive function that are lost during Alzheimer’s.”
Researchers from MIT and elsewhere have identified some of the benefits and disadvantages of generative AI when used for specific tasks, reports Paige McGlauflin and Joseph Abrams for Fortune. “The findings show a 40% performance boost for consultants using the chatbot for the creative product project, compared to the control group that did not use ChatGPT, but a 23% decline in performance when used for business problem-solving,” explain McGlauflin and Abrams.
A study by researchers from MIT and Harvard examined the potential impact of the use of AI technologies on the field of radiology, reports Laura Landro for The Wall Street Journal. “Both AI models and radiologists have their own unique strengths and areas for improvement,” says Prof. Nikhil Agarwal.