[Originally in Spanish] MIT researchers have developed a new technique to educate robots by increasing human input, reports Uriel Bederman for TN Tecno. “We can’t expect non-technical people to collect data and fine-tune a neural network model," explains graduate student Felix Yanwei Wang. "Consumers will expect the robot to work right out of the box, and if it doesn’t, they’ll want an intuitive way to customize it. That’s the challenge we’re addressing in this work."
Prof. David Autor speaks with Financial Times reporter Tom Davis about the impact of dataism – the belief that through gathering increasing amounts of information businesses can make the right decisions and create value - and automation in business management. “You can think of automation as a machine that takes a job’s inputs and does it for the worker,” says Autor. “[And] augmentation as a technology that increases the variety of things that people can do, the quality of things people can do, or their productivity”.
Prof. Eric So speaks with Financial Times reporter Seb Murray about the use of AI in business programs. “I’ve seen a mixture of surprise, enthusiasm, concern and trepidation,” explains So. “It’s quite difficult to design assignments that can be done without AI. I suspect much of our curriculum will be redesigned from the ground up.”
Prof. Behnaz Farahi and her team have created “Gaze to the Stars,” an art installation that features video projections of eyes onto the MIT Dome while sharing stories of aspiration, struggle, longing, and hope, reports Emily Maher for WCVB. “Farahi and her team created a space, a pod, where people looked into a screen of stars as their eyes were scanned,” explains Maher. “Next, an AI voice began encouraging them to share their stories.”
A new proposal by graduate student Shayne Longpre and other AI researchers suggests “a new scheme supported by AI companies that gives outsiders permission to probe their models and a way to disclose flaws publicly,” reports Will Knight for Wired. “The authors suggest three main measures to improve the third-party disclosure process: adopting standardized AI flaw reports to streamline the reporting process; for big AI firms to provide infrastructure to third-party researchers disclosing flaws; and for developing a system that allows flaws to be shared between different providers,” writes Knight.
Writing for Fast Company, graduate student Sheng-Hung Lee and Devin Liddell of Teague highlight four types of AI technologies that could aid senior citizens in their homes. “To better understand how seniors want AIs and robots to help in their homes, we asked them,” they write. “We recruited seniors from the MIT AgeLab’s research cohort—each around 70 years old and in the early stages of retirement—and then engaged in wide-ranging conversations about their aspirations and fears about these technologies.”
Prof. Behnaz Farahi speaks with WBUR reporter Maddie Browning about her “Gaze to the Stars” exhibit, which will bring illuminated projections of eyes to the MIT Dome. “This is an incredible time to really use art and technology, not to just create something which is provocative, but also have a meaningful experience to share stories that matters,” says Farahi.
Research Scientist Eva Ponce, director of online education for the MIT Center for Transportation & Logistics, speaks with Financial Times reporter Rafe Uddin about how companies are shifting toward automation and the impact on employees. “Companies are investing more in upskilling associates… ensuring they’re ready for a new style of work,” says Pone. “More complex tasks will still need to be done by people… These technologies are disruptive. The warehouse of the future is a combination of robotics, sensors and computer vision.”
Prof. Sara Beery speaks with TechCrunch reporter Kyle Wiggers about the use of AI tools in the advancement of science. “Most science isn’t possible to do entirely virtually — there is frequently a significant component of the scientific process that is physical, like collecting new data and conducting experiments in the lab,” explains Beery.
Writing for Forbes, Dr. Diane Hamilton spotlights how a course offered by Profs. Danielle Li and Thomas Malone “challenged common assumptions about AI’s role in the workplace, offering a more interesting and, at times, unexpected perspective.” Hamilton notes: MIT researchers reveal AI’s good and bad impact on jobs and skills, making it clear that AI is not just about automation. It is about augmentation. Companies that use AI to empower employees rather than replace them will be the ones that thrive in the years ahead.”
Bloomberg reporter Robb Mandelbaum spotlights how the Martin Trust Center for MIT Entrepreneurship has developed a new AI JetPack to help students accelerate the entrepreneurial process. “Our mission at the Trust Center is to advance the field of innovation-driven entrepreneurship everywhere,” Paul Cheek, executive director of the Martin Trust Center. “We can’t do it with intuition or by throwing stuff against the wall. We have to practice entrepreneurship in a rigorous, systematic way that increases the odds of success.”
Principal Research Scientist Andrew McAfee co-founded Workhelix, a “tech-enabled service startup that works with enterprises to better understand and monitor AI automation at their companies,” reports Rebecca Szkutak for Tech Crunch. “Workhelix breaks down a company’s employee positions into specific job functions and tasks and scores each task for its suitability for AI adoption,” explains Szkutak. “This helps companies build roadmaps for how and where to adopt AI and gives enterprises a way to monitor if the AI they adopted is working.”
Mohamed Elrefaie speaks with Automotive World reporter Will Girling about his work developing an open-source dataset of 8,000 car designs, including their aerodynamic characteristics, which could be used to develop novel car designs in a more efficient manner. “If an automaker wants to reduce drag and improve performance, it can guide the GenAI model to produce those specific designs,” Elrefaie explains. “The standard development cycle for a design using legacy tools can take anywhere from three to five years, as it requires collaboration between many specialized departments. With AI, you could validate up to 600 designs in just one or two minutes.”
Writing for Forbes, Paula Schneider, CEO of Susan G. Komen, highlights Prof. Regina Barzilay’s research using AI to detect breast cancer. “Using her own mammograms in her research at MIT, Dr. Barzilay demonstrated how AI could have detected her breast cancer much earlier, potentially improving her prognosis,” writes Schneider. “Studies show that incorporating AI into mammogram analysis boosts cancer detection rates by 20%, without increasing false positives. This is a significant leap forward, as early detection is key to a better chance at positive outcomes and survival.”
Eva Ponce, director of online education for the MIT Center for Transportation & Logistics, speaks with Financial Times reporter Rafe Uddin about how companies are integrating automation. “Labor shortages are a persistent theme and this is another driver for this investment,” says Ponce.