{
  "id": 17804467,
  "title": "AI Chief: Treating Medical AI as New Is a ‘Real Danger’",
  "url": "https://urgent.news/2026/11/02/ai-chief-treating-medical-ai-as-new-is-a-real-danger",
  "topic": "ai",
  "section": "AI",
  "published": "2026-11-02T13:44:00.000Z",
  "source": {
    "name": "Newsweek",
    "slug": "newsweek",
    "url": "https://www.newsweek.com/ai-chief-treating-medical-ai-as-new-is-a-real-danger-12532653"
  },
  "original_language": "en",
  "account": "Philip Payne, chief health AI officer at BJC HealthCare and WashU Medicine, cautioned against treating artificial intelligence as a newly emerging field during the AI Health Summit in New York City. Payne, a PhD-trained informatician, argued that AI is not in its infancy, despite the technology's rapid rise in healthcare. He emphasized that decades of research dating back to the 1950s and 1960s have established valuable lessons about using AI in medicine, which many health systems may overlook in their rush to adopt contemporary AI.\n\nPayne warned of the \"real danger\" of overlooking this historical research as health systems prioritize deploying newer AI technologies. He stressed the need for thoughtful consideration when treating AI as new, noting that the field has evolved significantly over the decades due to advancements in computing power, data availability, and technical infrastructure.\n\nOne example Payne cited was computerized identification of abnormal heart rhythms, a simple form of AI currently in use in clinics. He noted that he had been discussing AI applications in clinical practice years before the generative AI boom, which began in late 2022.\n\nRohit Chandra, executive vice president and chief digital officer at Cleveland Clinic, pointed out that today's AI technology is \"probably the most immature version that we're going to see,\" highlighting the rapid pace of its evolution. This rapid development means organizations must be prepared to experiment and accept that some efforts may fail, as they navigate this journey of AI adoption.\n\nChandra emphasized that health systems must learn from both decades of AI research in medicine and the capabilities offered by increasingly advanced technology. The panelists discussed the importance of infrastructure that can support these AI applications, particularly the need for continuous, real-time data to power increasingly predictive AI systems. Without reliable data, health systems risk failing to harness the full potential of AI.\n\nContinuous vital-sign monitoring, for example, has enabled Houston Methodist Hospital to identify potential problems earlier and alert bedside nurses, according to Michelle Stansbury, associate chief innovation officer. This example demonstrates how expanding technical capabilities can improve patient care when AI has access to timely information.\n\nPayne stressed that health systems should measure AI outcomes rather than relying solely on process measures, which are readily available. He advised health system leaders to work with informatics, clinical, and operational teams to ensure responsible innovation. By leveraging existing \"champions\" in these areas, organizations can build upon previous AI efforts and avoid reinventing the wheel. Payne concluded that AI is not merely a technological play but a tool that, when used responsibly, can deliver significant value to healthcare.",
  "summary": "As health systems work towards an AI-enabled future, BJC HealthCare's Philip Payne suggests consulting the past.",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}