Artificial intelligence

Prof. Daron Acemoglu speaks with VOX Talks host Tim Phillips about his new book written with Prof. Simon Johnson, “Power and Progress.” The book explores “how we can redirect the path of innovation,” Phillips explains.

MIT researchers have developed a new method to make chatbots more factual, reports Gerrit De Vynck for The Washington Post. “The researchers proposed using different chatbots to produce multiple answers to the same question and then letting them debate each other until one answer won out,” explains Vynck. “The researchers found using this ‘society of minds’ method made them more factual.”  

MIT researchers have developed a new machine-learning technique that can identify which pixels in an image represent the same material, which could help with robotic scene understanding, reports Kyle Wiggers for TechCrunch. “Since an object can be multiple materials as well as colors and other visual aspects, this is a pretty subtle distinction but also an intuitive one,” writes Wiggers.

Researchers from MIT and McMaster University have used artificial intelligence to identify a new antibiotic that can fight against a drug-resistant bacteria commonly found in hospitals and medical offices, reports Ken Alltucker for USA Today. The researchers believe the AI “process used to winnow thousands of potential drugs to identify one that may work is an approach that can work in drug discovery,” writes Alltucker.

Researchers from MIT and elsewhere have used artificial intelligence to develop a new antibiotic to address Acinetobacter baumannii, a bacteria known for infecting wounds, lungs and kidneys, reports Harland-Dunaway for The World.

Using a machine-learning algorithm, researchers from MIT and McMaster University have discovered a new type of antibiotic that works against a type of drug-resistant bacteria, reports Brenda Goodman for CNN. Goodman notes that the compound “worked in a way that stymied only the problem pathogen. It didn’t seem to kill the many other species of beneficial bacteria that live in the gut or on the skin, making it a rare narrowly targeted agent.”

Researchers from MIT and McMaster University used a machine-learning algorithm to identify a new antibiotic that can treat a bacteria that causes deadly infections, reports Maya Yang for The Guardian. The researchers used an “AI algorithm to screen thousands of antibacterial molecules in an attempt to predict new structural classes. As a result of the AI screening, researchers were able to identify a new antibacterial compound which they named abaucin,” writes Yang.

The Economist spotlights several MIT studies that use artificial neural networks (ANN) to examine the human brain, including work by former postdoctoral researcher Daniel Yamins and his colleagues training ANNs to pick out objects from photographs, reports The Economist.

Prof. Marzyeh Ghassemi speaks with NPR host Kate Wells about a decision by the National Eating Disorders Associations to replace their helpline with a chatbot. “I think it's very alienating to have an interactive system present you with irrelevant or what can feel like tangential information,” says Ghassemi.

Bloomberg reporter Adrian Wooldridge spotlights a new book titled “Power and Progress: Our Thousand-Year Struggle Over Technology and Prosperity” by Prof. Simon Johnson and Prof. Daron Acemoglu. “The authors’ main worry about AI is not that it will do something unexpected like blowing up the world,” writes Wooldridge. “It is that it will supercharge the current regime of surveillance, labor substitution and emotional manipulation.”

Institute Prof. Daron Acemoglu discusses AI and the labor market, the history of technological progress and Turkey with Financial Times columnist Rana Foroohar. “I think the skills of a carpenter or a gardener or an electrician or a writer, those are just the greatest achievements of humanity, and I think we should try to elevate those skills and elevate those contributions,” says Acemoglu. “Technology could do that, but that means to use technology not to replace these people, not to automate those tasks, but to increase their productivity.” 

Prof. Daron Acemoglu speaks with Wired reporters Gideon Lichfield and Lauren Goode about his new book with Prof. Simon Johnson, “Power and Progress.” Acemoglu explains that: “The way I would put it is, don't think of your labor as a cost to be cut. Think of your labor as a human resource to be used better, and AI would be an amazing tool for it. Use AI to allow workers to make better decisions.”

Prof. Stuart Madnick speaks with Wall Street Journal reporter Seán Captain about how AI could make scamming easier and more dangerous. AI “raises the level of skepticism that we must have substantially,” notes Madnick. “Procedures will have to be put in place to validate the authenticity of who you are dealing with.”

A study conducted by graduate student Aspen Hopkins and colleagues trained a version of a GPT neural network on the board game Othello “by feeding in long sequences of move in text form”, reports George Musser for Scientific American. “Their model became a nearly perfect player,” writes Musser.

Prof. Cynthia Breazeal, the MIT dean of digital learning, speaks with Education Week reporter Alyson Klein about the importance of ensuring K-12 students are AI literate. “The AI genie is out of the bottle,” says Breazeal. “It’s not just in the realm of computer science and coding. It is affecting all aspects of society. It’s the machine under everything. It’s critical for all students to have AI literacy if they are going to be using computers, or really, almost any type of technology.”