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Implementing artificial intelligence to assist individuals in resolving their issues.

Algorithms, Alumni/ae, Artificial Intelligence, Data, Innovation and Entrepreneurship (I&E), Machine learning, Media Lab, School of Architecture and Planning, Startups, UncategorizedMay 26, 202428Views0Likes0Comments
In 2010, Karthik Dinakar and Birago Jones, two students from the Media Lab at the Massachusetts Institute of Technology, collaborated on a project aimed at supporting content moderation teams for social media companies such as Twitter and YouTube. Their ambition was to develop a tool capable of identifying concerning posts online. Despite some initial struggles,…

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Implementing artificial intelligence for individuals seeking problem-solving solutions.

Algorithms, Alumni/ae, Artificial Intelligence, Data, Innovation and Entrepreneurship (I&E), Machine learning, Media Lab, School of Architecture and Planning, Startups, UncategorizedMay 26, 202433Views0Likes0Comments
In 2010, Media Lab students Karthik Dinakar SM ’12, Ph.D.’17, and Birago Jones SM ’12 developed a tool intended to assist content moderation teams for platforms such as Twitter and YouTube. The tool aimed to flag harmful content, with a key focus on posts that could be linked to cyberbullying. The project was warmly received,…

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Empowering individuals with challenges by providing them access to Artificial Intelligence.

Algorithms, Alumni/ae, Artificial Intelligence, Data, Innovation and Entrepreneurship (I&E), Machine learning, Media Lab, School of Architecture and Planning, Startups, UncategorizedMay 25, 202430Views0Likes0Comments
In 2010, Karthik Dinakar and Birago Jones, students at the Media Lab, teamed up to create a tool designed to aid content moderation teams at companies including Twitter and YouTube. The project generated widespread interest and soon they were invited to the White House to demonstrate their technology designed to identify concerning posts on these…

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Empowering individuals facing challenges by equipping them with artificial intelligence.

Algorithms, Alumni/ae, Artificial Intelligence, Data, Innovation and Entrepreneurship (I&E), Machine learning, Media Lab, School of Architecture and Planning, Startups, UncategorizedMay 24, 202431Views0Likes0Comments
In 2010, MIT Media Lab students Karthik Dinakar SM ’12, PhD ’17 and Birago Jones SM ’12 embarked on creating a tool to assist content moderation teams at companies like Twitter (now X) and YouTube. Their demo, which was presented at a cyberbullying summit at the White House, identified troublesome posts through machine learning. However,…

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The Engineering Department extends a warm welcome to its latest professors.

Aeronautical and astronautical engineering, Artificial Intelligence, Biological engineering, Broad Institute, Chemical engineering, Civil and environmental engineering, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Computer vision, Cryptography, Data, DMSE, Economics, Electrical Engineering & Computer Science (eecs), Electronics, Environment, Faculty, Human-computer interaction, human-robot interaction, IDSS, Immunology, Laboratory for Information and Decision Systems (LIDS), Machine learning, Media Lab, Medicine, MIT Schwarzman College of Computing, Music, Music and theater arts, Research Laboratory of Electronics, Robotics, School of Engineering, School of Humanities Arts and Social Sciences, School of Science, UncategorizedMay 24, 202443Views0Likes0Comments

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Design Fellows for MAD 2024 have been revealed.

Architecture, Artificial Intelligence, Awards, Electrical Engineering & Computer Science (eecs), Graduate, honors and fellowships, Innovation and Entrepreneurship (I&E), Machine learning, Mechanical engineering, Media, Media Lab, MIT Museum, MIT Schwarzman College of Computing, MIT Sloan School of Management, postdoctoral, Robotics, School of Architecture and Planning, School of Engineering, Students, UncategorizedMay 22, 202440Views0Likes0Comments
The MIT Morningside Academy for Design (MAD) unveiled the 2024 Design Fellows at an event held at the MIT Museum on May 1, 2024. The Academy has continually supported MIT graduate students since its inception in 2022 by providing them with a fellowship enabling the pursuit of design research and projects, along with community-building. Interns…

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Physicians encounter greater challenges in identifying diseases when examining images of darker skin tones.

Artificial Intelligence, Computer science and technology, Ethics, Health care, Media Lab, Medicine, Research, School of Architecture and Planning, Social justice, Technology and society, UncategorizedMay 15, 202427Views0Likes0Comments
A new study by researchers from Massachusetts Institute of Technology (MIT) has found that doctors are less accurate in diagnosing skin diseases based on images when the patient has darker skin. The study included over 1,000 dermatologists and general practitioners; dermatologists accurately diagnosed 38 percent of images overall, but only 34 percent of darker skin…

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Physicians often find it more challenging to identify diseases when examining images of darker skin tones.

Artificial Intelligence, Computer science and technology, Ethics, Health care, Media Lab, Medicine, Research, School of Architecture and Planning, Social justice, Technology and society, UncategorizedMay 15, 202439Views0Likes0Comments
Doctors are less accurate when diagnosing skin diseases in people with darker skin, according to a study by MIT researchers. The researchers found that dermatologists accurately characterized 38% of images of skin diseases, but only 34% of those images were of darker skin. The results were similar for general practitioners. The research team suggested that…

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Diagnosing illnesses can be more challenging for physicians when examining images of darker skin tones.

Artificial Intelligence, Computer science and technology, Ethics, Health care, Media Lab, Medicine, Research, School of Architecture and Planning, Social justice, Technology and society, UncategorizedMay 14, 202438Views0Likes0Comments
Doctors struggle to diagnose skin disease accurately in patients with darker skin tones, according to new research from MIT. The study found that dermatologists correctly diagnosed images of skin disease in just 34% of cases involving darker skin, compared with 38% involving lighter skin. The researchers also examined the effect of AI assistance on diagnostic…

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Physicians face greater challenges in identifying diseases when examining images of darker skin tones.

Artificial Intelligence, Computer science and technology, Ethics, Health care, Media Lab, Medicine, Research, School of Architecture and Planning, Social justice, Technology and society, UncategorizedMay 14, 202437Views0Likes0Comments
A new study from MIT researchers suggests that doctors are less accurate in diagnosing skin diseases on patients with darker skin through images alone. The study analyzed the accuracy of over 1,000 dermatologists and general practitioners and found that dermatologists correctly diagnosed about 38% of the images they saw, but only 34% for those of…

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