Ep 38: Oscar Co-Founder Mario Schlosser on Lessons from Implementing LLMs and How AI Will Impact Healthcare
Feb 13, 2024
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Mario Schlosser, Co-Founder of Oscar Health, discusses the impact of AI in healthcare, limitations of GPT-4, and why we can't have robot doctors. They also talk about sharing AI knowledge, developing healthcare-specific models, and the need for a safety layer in LLMs. Other topics include commercial opportunities in healthcare, the possibility of AI doctors, and overhyped/underhyped aspects of AI. Oscar Health's unique approach and their interest in exploring AI use cases in gaming are also highlighted.
AI can greatly impact healthcare by improving outcomes, reducing costs, and assisting in decision-making.
Oscar Health leverages AI to enhance customer experience and personalize messaging, improving member retention and engagement.
Implementing AI in healthcare requires proper alignment with regulations, addressing complex workflows, and balancing interpretability and performance.
Deep dives
The Impact of AI in Healthcare
AI in healthcare has the potential to greatly impact the industry. Healthcare is a unique field with a mix of formal and informal language, making it a suitable domain for AI algorithms. The use of AI in healthcare has been limited in the past, but advancements in language models like GPT-4 have opened up possibilities. AI can be utilized in administrative tasks like claims processing, where it can summarize complex rules and provide clearer explanations to both experts and laypeople. AI can also help improve healthcare outcomes by reducing costs, enhancing transparency, and assisting in clinical decision-making. However, challenges remain, such as the need for interpretability, addressing biases, and bridging the gap between formal and informal language.
Personalized Messaging and Improved Customer Experience
Oscar, an insurance company, has leveraged AI to enhance customer experience and personalize messaging. Through outbound campaigns, personalized reminders, and targeted messaging, Oscar has been able to improve member retention and engagement. By understanding different member personas and tailoring communications accordingly, Oscar has achieved better results. AI has helped in analyzing ethnic background, language, and health conditions to deliver more relevant and impactful messages. The use of AI in customer service, claims processing, and care teams has allowed Oscar to provide better healthcare experiences to its members.
Addressing Complexity and Challenges in AI Implementation
Implementing AI in healthcare poses unique challenges due to industry regulations and complex workflows. AI applications need to comply with regulations like HIPAA, and it requires efforts to establish trust with healthcare providers and organizations. AI models often struggle with complex rule-based systems and maintaining alignment with instructions. Proper prompting strategies are crucial to navigate model limitations and maintain accuracy. While healthcare-specific models have been developed, they still lag behind general-purpose models like GPT-4 in alignment and customization. Balancing interpretability, performance, and the ability to follow instructions remains an ongoing challenge in AI implementation.
Structuring AI at Oscar
Oscar has adopted a successful model for structuring its AI teams. They have a dedicated hackathon where employees can work on AI-related projects. This approach encourages participation and innovation across the company. AI expertise is embedded within individual product teams, allowing for specialization and deep domain knowledge. By combining the strengths of AI professionals with domain experts, Oscar has been able to develop tailored AI solutions for various healthcare aspects, such as claims processing and customer experience. This structure promotes collaboration and ensures that AI technologies are effectively integrated into different areas of the company.
The Potential of Clinical Chatbots and Virtual Doctors
The podcast discusses the potential of clinical chatbots and the evolution of virtual doctors in healthcare AI. The speaker acknowledges that clinical chatbots are currently overhyped, but believes that there is a future in which doctors can be replaced by AI. However, there are challenges to overcome, such as safety concerns, the need for physical interactions in certain cases, and the resistance of health systems to switch to lower-cost care delivery methods. Overall, the speaker is optimistic about the future of AI in healthcare, but emphasizes the importance of addressing these challenges to fully realize its potential.
The Growing Influence of the Individual Market and the Accelerated Market Opportunity
The podcast highlights the significant growth and influence of the individual market in healthcare. The speaker notes that the individual market has expanded rapidly, with the number of individuals covered increasing over the years. Additionally, the introduction of Individual Coverage HRAs (Accra) has the potential to shift the employer market towards the individual market on a larger scale. This presents an opportunity for startups and businesses to enter the healthcare AI space, as the individual market continues to expand and evolve. The speaker encourages entrepreneurs to explore specific API access points, such as fraud-waste-and-abuse detection, and emphasizes the need to find niche areas where healthcare AI can provide valuable solutions.
Oscar Health is a $4B public healthcare company, providing healthcare insurance to nearly 1 million members. Oscar is at the forefront of AI adoption, continuously developing new AI use cases in healthcare. On this week’s episode, we sat down with Oscar Health Co-Founder, former CEO, and now President of Technology Mario Schlosser to talk about where AI will have the biggest impact in healthcare, limitations of GPT-4 in healthcare, and why can't we have robot doctors today.
(0:00) intro
(1:06) how will AI change healthcare in the next decade
(9:09) how Oscar uses AI
(18:40) how to build around healthcare requirements
(25:46) when would GPT-4 fail "miserably" and fundamental limitations of LLMs
(36:28) we shouldn’t piss off our smartest robots
(38:15) sharing AI knowledge between companies
(41:50) developing healthcare-specific models
(44:35) hackathons and karaoke nights at Oscar
(49:07) the need for a safety layer in LLMs
(51:33) best commercial opportunities in healthcare
(55:19) will their be AI doctors this decade?
(59:18) over-hyped/under-hyped
(1:00:49) most exciting AI company?
(1:08:46) over-hyped/under-hyped
Out-Of-Pocket: https://www.outofpocket.health/
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