NYU Langone Health is leveraging agentic AI to support medical students by processing anonymized diagnostic data from multiple hospitals and outpatient locations. This AI system autonomously matches diagnostic codes with relevant research, delivering tailored information to students each morning. For successful implementation, CIOs need to consider five key questions: What specific problem is the AI solving? Is there appropriate data available? How secure is this data? How does the AI fit into the overall tech strategy? And how will the AI be monitored? NYU’s proactive approach ensures that the AI remains effective and continues to provide valuable insights for students.
AI Revolutionizes Learning at NYU Grossman School of Medicine
In today’s fast-paced world, integrating artificial intelligence (AI) into education is becoming a game changer. At NYU Grossman School of Medicine and the NYU Grossman Long Island School of Medicine, an innovative AI application is helping medical students enhance their learning experience while they sleep. This technology operates at night, analyzing anonymized diagnostic codes from a wide network of hospitals and outpatient facilities within the NYU Langone Health system.
The AI matches these codes with relevant research and diagnoses, sending tailored findings directly to students just in time for their morning coffee. By doing so, it not only saves time but also enriches the educational journey of future healthcare professionals.
This type of AI is known as agentic AI, which refers to systems capable of making decisions and taking actions autonomously. As David Brauchler, a technical director at NCC Group, points out, improving the surrounding components is essential for AI to make relevant decisions. However, deploying such technology requires careful consideration.
Five Key Questions for CIOs Considering Agentic AI
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What Problem Will Agentic AI Solve?
Organizations must have a strategic plan to ensure that AI addresses the correct use case. Nader Mherabi from NYU Langone Health emphasizes that integrating AI into existing workflows is crucial to maximize its utility. -
Do We Have the Data to Make It Work?
For AI to be effective, the right data must be in place. Tom Coshow from Gartner notes that data preparation is vital to ensure the AI system pulls accurate and relevant information. Organizations need data experts who can maintain quality data tailored for AI applications. -
Will Data Be Secure?
As organizations introduce AI, they must consider the security implications. Brauchler warns that adding AI components could create vulnerabilities if not properly governed. Conducting security testing is crucial to prevent potential risks. -
Where Does Agentic AI Fit into the Company’s Tech Strategy?
CIOs should evaluate how agentic AI fits into their broader tech strategy. Understanding whether to build capabilities in-house or partner with specialized startups is essential for success. - How Will Agentic AI Be Monitored?
Continuous monitoring is necessary to ensure that agentic AI delivers accurate and beneficial results. Mherabi highlights the importance of ongoing oversight to maintain the effectiveness of these applications.
Thanks to this innovative approach, NYU Langone Health has successfully deployed its agentic AI, enhancing the learning experience for medical students. This technology encourages students to engage with relevant materials daily, adding a modern twist to medical education. As Mherabi aptly puts it, "Who wouldn’t like that?"
This integration of AI in education signifies a broader trend in using advanced technologies to improve learning outcomes, making it an exciting prospect for educational institutions worldwide.
Tags: AI in education, agentic AI, NYU Langone Health, medical education, technology in learning
What is agentic AI?
Agentic AI refers to artificial intelligence systems that can make decisions and take actions on their own. These systems can learn from experiences and adapt to new situations without much human input.
What are the risks of deploying agentic AI?
There are some risks to consider, like potential bias in decision-making, lack of control, and unintended consequences. It is important to assess and manage these risks before deployment.
How can we ensure the safety of agentic AI?
To ensure safety, you should implement strict controls, regularly monitor the AI’s decisions, and establish clear guidelines. Testing the AI in controlled environments before full deployment can also help.
What industries can benefit from agentic AI?
Many industries can benefit, including healthcare, finance, manufacturing, and customer service. Agentic AI can improve efficiency, decision-making, and customer experience in these fields.
How do we monitor agentic AI after deployment?
Monitoring can involve tracking performance metrics, analyzing outcomes, and gathering feedback from users. Regular audits and evaluations help ensure the AI operates ethically and effectively.
