Erik Duhaime, Co-founder and CEO of Centaur Labs, discusses the potential of generative AI in healthcare and the importance of quality control in AI models. He explores the evolving role of humans in AI and how data labeling is becoming increasingly important. The impact of new technologies and the importance of human feedback in healthcare are also explored.
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Quick takeaways
Generative AI models like chat GPT provide new opportunities in healthcare by allowing AI developers to build models quickly and interact with them like humans.
To ensure accuracy in AI model development for healthcare, building large-scale training datasets, using experts' preference data sets for feedback and fine-tuning, and ongoing model monitoring and quality control are crucial.
Deep dives
Opportunities and Challenges of Generative AI in Healthcare
Generative AI models like chat GPT provide new opportunities in the healthcare space. With large foundation models, AI developers can build models quickly and interact with them like humans. For instance, a model can generate complete descriptive radiology reports. However, the challenge lies in quality control. Human-like responses create infinite potential outputs, making it difficult to maintain quality. Issues like hallucinations can be harmful, especially in healthcare. Ensuring model quality is crucial, and experts are needed in data labeling and ongoing monitoring to prevent mistakes and ensure accuracy.
Ensuring Quality in AI Models for Healthcare
To ensure accuracy, three things are crucial in AI model development. First, building large-scale training datasets is important in specialized domains like healthcare. Unique datasets lead to improved models. Second, experts' preference data sets should be used to provide feedback and fine-tune models. Reinforcement learning with expert feedback is necessary for healthcare tasks. Third, ongoing model monitoring and quality control are essential. Skilled experts should review model outputs, especially in tasks with high stakes like healthcare. Ongoing testing and monitoring ensure continuous improvement and accuracy in AI models.
The Importance of Experts in AI Development for Healthcare
Experts play a crucial role in AI development for healthcare. Bringing experts into the loop may slow down AI development compared to using unskilled workers. High-quality work from experts is ensured by measuring performance continually and combining the votes of skilled workers. Expertise in domains like healthcare is crucial in building accurate models. The role of experts will change and evolve as AI and humans work together. AI will not replace doctors, but tasks will be assigned differently, allowing doctors to focus more on tasks that add value. AI models will enhance healthcare by automating certain tasks and improving overall care.
Today’s guest is Erik Duhaime, Co-founder and CEO of Centaur Labs. Centaur Labs helps AI developers and data scientists label medical and scientific datasets at scale so that they can build and improve their models more quickly and easily. He joins us on the program today to talk about generative AI in the healthcare space today and the increasingly important role human experts will play in the development of the AI of tomorrow. This episode is sponsored by Centaur Labs. Learn how brands work with Emerj and other Emerj Media options at emerj.com/ad1.
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