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Start developing a more efficient AI assistant by first understanding and replicating the unpredictable actions of humans.

Algorithms, Artificial Intelligence, Computer modeling, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Electrical Engineering & Computer Science (eecs), Human-computer interaction, Machine learning, MIT Schwarzman College of Computing, National Science Foundation (NSF), Research, School of Engineering, UncategorizedApril 19, 202431Views0Likes0Comments
Artificial Intelligence (AI) researchers at MIT and the University of Washington have created a model that can predict a human's decision-making behaviour by learning from their past actions. The model incorporates the understanding that humans can behave sub-optimally due to computational constraints — essentially the idea that humans can't spend indefinitely long periods considering the…

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An improved, more efficient method to inhibit AI chatbots from delivering harmful responses.

Algorithms, Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Defense Advanced Research Projects Agency (DARPA), Electrical Engineering & Computer Science (eecs), Human-computer interaction, Machine learning, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, Research, School of Engineering, UncategorizedApril 10, 202434Views0Likes0Comments

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The automated platform instructs users on the appropriate instances to engage with an AI assistant.

Algorithms, Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Data, Electrical Engineering & Computer Science (eecs), Health care, Human-computer interaction, IDSS, Institute for Medical Engineering and Science (IMES), Machine learning, MIT Schwarzman College of Computing, Research, School of Engineering, UncategorizedApril 8, 202437Views0Likes0Comments
Researchers at MIT and the MIT-IBM Watson AI Lab have developed an AI system designed to educate users on when to trust an AI's decision-making process - for instance, a radiologist determining if a patient's X-ray shows signs of pneumonia. The training system identifies scenarios where the human should not trust the AI model, automatically…

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The system instructs users on determining the appropriate times to work in conjunction with an AI assistant.

Algorithms, Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Data, Electrical Engineering & Computer Science (eecs), Health care, Human-computer interaction, IDSS, Institute for Medical Engineering and Science (IMES), Machine learning, MIT Schwarzman College of Computing, Research, School of Engineering, UncategorizedApril 8, 202438Views0Likes0Comments
Researchers from MIT and the MIT-IBM Watson AI Lab have developed a system to teach users of artificial intelligence (AI) technology when they should or shouldn't trust its outcomes. This could be particularly beneficial in the medical field, where errors could have serious repercussions. The team created an automated system to teach a radiologist how…

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The automated platform instructs users on the appropriate instances to engage with an AI assistant.

Algorithms, Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Data, Electrical Engineering & Computer Science (eecs), Health care, Human-computer interaction, IDSS, Institute for Medical Engineering and Science (IMES), Machine learning, MIT Schwarzman College of Computing, Research, School of Engineering, UncategorizedApril 7, 202434Views0Likes0Comments
Researchers at MIT and the MIT-IBM Watson AI Lab have developed a method of teaching users when to collaborate with an artificial intelligence (AI) assistant. The model creates a customised onboarding process, educating users on when to trust or ignore an AI model’s advice. The training process can detect situations where the AI model is…

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The automated system guides users on when to partner with an artificial intelligence assistant.

Algorithms, Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Data, Electrical Engineering & Computer Science (eecs), Health care, Human-computer interaction, IDSS, Institute for Medical Engineering and Science (IMES), Machine learning, MIT Schwarzman College of Computing, Research, School of Engineering, UncategorizedApril 7, 202435Views0Likes0Comments
Researchers at the Massachusetts Institute of Technology and the MIT-IBM Watson AI Lab have developed an onboarding system that trains humans when and how to collaborate with Artificial Intelligence (AI). The fully automated system learns to customize the onboarding process according to the tasks performed, making it usable across a variety of scenarios where AI…

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The automated platform instructs users about the appropriate time to partner with an AI assistant.

Algorithms, Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Data, Electrical Engineering & Computer Science (eecs), Health care, Human-computer interaction, IDSS, Institute for Medical Engineering and Science (IMES), Machine learning, MIT Schwarzman College of Computing, Research, School of Engineering, UncategorizedApril 6, 202437Views0Likes0Comments
Researchers at MIT and the MIT-IBM Watson AI Lab have developed a system that teaches users when to trust AI and when to ignore it, and it has already led to an approximately 5% increase in accuracy during image prediction tasks. The researchers designed a customised onboarding process, which is when the user is familiarized…

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The automated system educates users on the appropriate times to partner with an AI assistant.

Algorithms, Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Data, Electrical Engineering & Computer Science (eecs), Health care, Human-computer interaction, IDSS, Institute for Medical Engineering and Science (IMES), Machine learning, MIT Schwarzman College of Computing, Research, School of Engineering, UncategorizedApril 6, 202436Views0Likes0Comments
Researchers from MIT and the MIT-IBM Watson AI Lab have developed a system that instructs users when to trust an AI system’s decision-making. In medicine, there might be instances like a radiologist using an AI model for reading X-rays where human intervention can make a difference. However, clinicians are uncertain whether to lean on the…

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The automated system instructs users on the appropriate time to work together with an AI assistant.

Algorithms, Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Data, Electrical Engineering & Computer Science (eecs), Health care, Human-computer interaction, IDSS, Institute for Medical Engineering and Science (IMES), Machine learning, MIT Schwarzman College of Computing, Research, School of Engineering, UncategorizedApril 5, 202432Views0Likes0Comments
Researchers from MIT and the MIT-IBM Watson AI Lab have developed an onboarding process which teaches users how to effectively collaborate with artificial intelligence (AI) assistants. The system was designed to provide guidance to users and to improve collaboration between humans and AI. The automated system learns how to create the onboarding process by gathering…

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The automated system provides guidance on when to engage with an AI assistant for collaboration.

Algorithms, Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Data, Electrical Engineering & Computer Science (eecs), Health care, Human-computer interaction, IDSS, Institute for Medical Engineering and Science (IMES), Machine learning, MIT Schwarzman College of Computing, Research, School of Engineering, UncategorizedApril 5, 202434Views0Likes0Comments
Researchers from MIT and the MIT-IBM Watson AI Lab have developed an automated system that trains users on when to collaborate with an AI assistant. In medical fields such as radiology, this system could guide a practitioner on when to trust an AI model’s diagnostic advice. The researchers claim that their onboarding procedure led to…

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The automated system instructs users on the appropriate times to engage with an AI assistant.

Algorithms, Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Data, Electrical Engineering & Computer Science (eecs), Health care, Human-computer interaction, IDSS, Institute for Medical Engineering and Science (IMES), Machine learning, MIT Schwarzman College of Computing, Research, School of Engineering, UncategorizedApril 4, 202434Views0Likes0Comments
Researchers at MIT and the MIT-IBM Watson AI Lab have developed a system that trains users on when to trust an AI model's advice. This automated system essentially creates an onboarding process based on a specific task performed by a human and an AI model. It then uses this data to develop training exercises, helping…

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An automated platform instructs users on the appropriate timing for partnership with an AI assistant.

Algorithms, Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Data, Electrical Engineering & Computer Science (eecs), Health care, Human-computer interaction, IDSS, Institute for Medical Engineering and Science (IMES), Machine learning, MIT Schwarzman College of Computing, Research, School of Engineering, UncategorizedApril 4, 202441Views0Likes0Comments
Researchers at MIT and the MIT-IBM Watson AI Lab have outlined an onboarding process, which includes training for users of artificial intelligence (AI) tools to better comprehend and utilise them. With a 5% accuracy improvement, the system setup enables a user to discern when to collaborate with AI by providing a personalised training programme. The AI…

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