Research by Associate Prof. Jared Curhan in Sloan found that back-to-back negotiations can be challenging, particularly if a person has recently been successful. “Hubristic pride may give you a false sense of confidence, and you may underestimate your next counterpart,” Curhan tells Aisha Al-Muslim at The Wall Street Journal. “That may make you not prepare adequately for the next negotiation.”
A study by MIT scientists has identified the neurons that fire at the beginning and end of activities, which is important for initiating a routine. “This task-bracketing appears to be important for initiating a routine and then notifying the brain once it is complete,” Prof. Ann Graybiel told Xinhua.
In an article for the Financial Times about the best economics books of 2017, Martin Wolf highlights new works by Prof. Andrew Lo and Prof. Peter Temin. Wolf writes that in Temin’s “important and provocative book, [he] argues that the US is becoming a nation of rich and poor, with ever fewer households in the middle.”
A new study by MIT researchers shows how stress can lead people to make risky decisions, reports Kristin Hugo for Newsweek. “The study lends insights into how neurological disorders affect people. It could be the stress of dealing with inabilities to function properly and staving off cravings, compounded with the chemical effects on the brain, that are influencing people’s uninhibited behavior.”
Writing for HuffPost, Prof. Georgia Perakis explains that it is possible to detect customer trends without using data gathered via social media. By using data like store locations, customer demographics, and timing of purchases, “we can still understand the influence of certain individuals and groups,” Perakis explains.
Bloomberg Businessweek reporter Arianne Cohen spotlights Prof. Andrew Lo’s research examining adaptive markets. Cohen explains that, “Lo’s hypothesis says people act in their own self-interest but frequently make mistakes, figure out where they’ve erred, and change their behaviors. The broader system also adapts.”
A new study by MIT researchers shows that children as young as 15 months can learn tenacity from watching their parents, reports Dennis Thompson for U.S. News & World Report. Graduate student Julia Leonard explains that the study shows, "infants are watching your behavior intently and actually learning from what you do."
Scientific American reporter Yasemin Saplakoglu writes that MIT researchers have found that watching an adult struggle and then succeed can inspire infants to try harder at their own task. Saplakoglu explains that the study shows, “babies can also infer values—such as when it is worth it to keep trying—from adults’ behaviors.”
AP reporter Malcom Ritter writes that children as young as 15 months old can be inspired to try harder at a task when they see adults struggle before succeeding. Prof. Laura Schulz explained that the findings show young children, “can learn the value of effort from just a couple of examples.”
After studying more than 100 languages, Prof. Edward Gibson has “discovered a pattern in the way different cultures discern and label colors,” writes Ben Thompson for the Boston Globe.
A new study from Prof. Edward Gibson examines the way different languages describe colors. “If you were to take the spectrum of colors that are perceptibly different to humans and chop it in half, every language would have more words for describing the warm half than the cool half,” writes Rachel Gutman for The Atlantic.
A new study by MIT researchers examines how people who speak different languages describe colors, reports Zach Zorich for Science. The researchers found that, “the ability to describe colors isn’t as rooted in our biology as many scientists thought. And that means that language development may be far more rooted in our culture than in how we literally see the world.”
CSAIL researchers have developed an artificial neural network that generates recipes from pictures of food, reports Laurel Dalrymple for NPR. The researchers input recipes into an AI system, which learned patterns “connections between the ingredients in the recipes and the photos of food,” explains Dalrymple.
In this video for USA Today, Sean Dowling highlights Pic2Recipe, the artificial intelligence system developed by CSAIL researchers that can predict recipes based off images of food. The researchers hope the app could one day be used to help, “people track daily nutrition by seeing what’s in their food.”
Researchers at MIT have developed an algorithm that can identify recipes based on a photo, writes BBC News reporter Zoe Kleinman. The algorithm, which was trained using a database of over one million photos, could be developed to show “how a food is prepared and could also be adapted to provide nutritional information,” writes Kleinman.