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GPT-5 Doesn't Dislike You--It Might Just Need a Benchmark for Emotional Intelligence
Since the all-new ChatGPT launched on Thursday, some users have mourned the disappearance of a peppy and encouraging personality in favor of a colder, more businesslike one (a move seemingly designed to reduce unhealthy user behavior.) The backlash shows the challenge of building artificial intelligence systems that exhibit anything like real emotional intelligence. Researchers at MIT have proposed a new kind of AI benchmark to measure how AI systems can manipulate and influence their users--in both positive and negative ways--in a move that could perhaps help AI builders avoid similar backlashes in the future while also keeping vulnerable users safe. Most benchmarks try to gauge intelligence by testing a model's ability to answer exam questions, solve logical puzzles, or come up with novel answers to knotty math problems. As the psychological impact of AI use becomes more apparent, we may see MIT propose more benchmarks aimed at measuring more subtle aspects of intelligence as well as machine-to-human interactions.
Heavy ChatGPT users tend to be more lonely, suggests research
Heavy users of ChatGPT tend to be lonelier, more emotionally dependent on the AI tool and have fewer offline social relationships, new research suggests. Only a small number of users engage emotionally with ChatGPT, but those who do are among the heaviest users, according to a pair of studies from OpenAI and the MIT Media Lab. The researchers wrote that the users who engaged in the most emotionally expressive personal conversations with the chatbots tended to experience higher loneliness – though it isn't clear if this is caused by the chatbot or because lonely people are seeking emotional bonds. While the researchers have stressed that the studies are preliminary, they ask pressing questions about how AI chatbot tools, which according to OpenAI is used by more than 400 million people a week, are influencing people's offline lives. The researchers, who plan to submit both studies to peer-reviewed journals, found that participants who "bonded" with ChatGPT – typically in the top 10% for time spent with the tool – were more likely than others to be lonely, and to rely on it more.
Joint studies from OpenAI and MIT found links between loneliness and ChatGPT use
New studies from OpenAI and MIT Media Lab found that, generally, the more time users spend talking to ChatGPT, the lonelier they feel. The connection was made as part of two, yet-to-be-peer-reviewed studies, one done at OpenAI analyzing "over 40 million ChatGPT interactions" and targeted user surveys, and another at MIT Media Lab following participants' ChatGPT use for four weeks. MIT's study identified several ways talking to ChatGPT -- whether through text or voice -- can affect a person's emotional experience, beyond the general finding that higher use led to "heightened loneliness and reduced socialization." For example, participants who already trusted the chatbot and tended to get emotionally attached in human relationships felt lonelier and more emotionally dependent on ChatGPT during the study. Those effects were less severe with ChatGPT's voice mode, though, particularly if ChatGPT spoke in a neutral tone.
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OpenAI has released its first research into how using ChatGPT affects people's emotional wellbeing
The researchers found some intriguing differences between how men and women respond to using ChatGPT. After using the chatbot for four weeks, female study participants were slightly less likely to socialize with people than their male counterparts who did the same. Meanwhile, participants who interacted with ChatGPT's voice mode in a gender that was not their own for their interactions reported significantly higher levels of loneliness and more emotional dependency on the chatbot at the end of the experiment. OpenAI plans to submit both studies to peer-reviewed journals. Chatbots powered by large language models are still a nascent technology, and it's difficult to study how they affect us emotionally.
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A conversation with OpenAI's first artist in residence
Officially, the appointment started in January and lasts three months. But Reben's relationship with the San Francisco–based AI firm seems casual: "It's a little fuzzy, because I'm the first, and we're figuring stuff out. I'm probably going to keep working with them." In fact, Reben has been working with OpenAI for years already. Five years ago, he was invited to try out an early version of GPT-3 before it was released to the public. "I got to play around with that quite a bit and made a few artworks," he says.
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Making life friendlier with personal robots
Sharifa Alghowinem, a research scientist in the Media Lab's Personal Robots Group, poses with Jibo, a friendly robot companion developed by Professor Cynthia Breazeal. "As a child, I wished for a robot that would explain others' emotions to me" says Sharifa Alghowinem, a research scientist in the Media Lab's Personal Robots Group (PRG). Growing up in Saudi Arabia, Alghowinem says she dreamed of coming to MIT one day to develop Arabic-based technologies, and of creating a robot that could help herself and others navigate a complex world. In her early life, Alghowinem faced difficulties with understanding social cues and never scored well on standardized tests, but her dreams carried her through. She earned an undergraduate degree in computing before leaving home to pursue graduate education in Australia.
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How AI could help local newsrooms remain afloat in a sea of misinformation
It didn't take long for the downsides of a generative AI-empowered newsroom to make themselves obvious, between CNet's secret chatbot reviews editor last November and Buzzfeed's subsequent mass layoffs of human staff in favor of AI-generated "content" creators. The specter of being replaced by a "good enough AI" looms large in many a journalist's mind these days with as many as a third of the nation's newsrooms expected to shutter by the middle of the decade. But AI doesn't have to necessarily be an existential threat to the field. As six research teams showed at NYU Media Lab's AI & Local News Initiative demo day in late June, the technology may also be the key to foundationally transforming the way local news is gathered and produced. Now in its second year, the initiative is tasked with helping local news organizations to "harness the power of artificial intelligence to drive success." It's backed as part of a larger $3 million grant from the Knight Foundation which is funding four such programs in total in partnership with the Associated Press, Brown Institute's Local News Lab, NYC Media Lab and the Partnership on AI.
Smart textiles sense how their users are moving
Using a novel fabrication process, MIT researchers have produced smart textiles that snugly conform to the body so they can sense the wearer's posture and motions. By incorporating a special type of plastic yarn and using heat to slightly melt it -- a process called thermoforming -- the researchers were able to greatly improve the precision of pressure sensors woven into multilayered knit textiles, which they call 3DKnITS. They used this process to create a "smart" shoe and mat, and then built a hardware and software system to measure and interpret data from the pressure sensors in real time. The machine-learning system predicted motions and yoga poses performed by an individual standing on the smart textile mat with about 99 percent accuracy. Their fabrication process, which takes advantage of digital knitting technology, enables rapid prototyping and can be easily scaled up for large-scale manufacturing, says Irmandy Wicaksono, a research assistant in the MIT Media Lab and lead author of a paper presenting 3DKnITS.
Robot overcomes uncertainty to retrieve buried objects
MIT researchers previously demonstrated a robotic arm that combines visual information and radio frequency (RF) signals to find hidden objects that were tagged with RFID tags (which reflect signals sent by an antenna). Building off that work, they have now developed a new system that can efficiently retrieve any object buried in a pile. As long as some items in the pile have RFID tags, the target item does not need to be tagged for the system to recover it. The algorithms behind the system, known as FuseBot, reason about the probable location and orientation of objects under the pile. Then FuseBot finds the most efficient way to remove obstructing objects and extract the target item.
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President Guðni Thorlacius Jóhannesson of Iceland visits MIT
Guðni Thorlacius Jóhannesson, the president of Iceland, visited MIT on Friday, engaging in talks with several campus leaders and professors, and touring the Media Lab. Jóhannesson visited the Institute along with a substantial delegation of officials and scholars from Iceland. They met with MIT scholars, who delivered a variety of presentations on research, design, and entrepreneurship; the Iceland delegation also had a particular interest in the inclusion of the Icelandic language in artificial intelligence-driven tools that automatically recognize, translate, and deploy speech and texts. "We are determined to make sure that Icelandic has a place in the digital age," Jóhannesson said. "AI plays a key role there."
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