本文由小咖机器人翻译整理

期刊来源：JAMA

原文链接：https://doi.org/10.1001/jama.2023.25057

摘要内容如下：

重要性

人们对人工智能（AI）的兴趣达到了前所未有的高度，整个生态系统的医疗保健领导者都面临着关于在何处、何时和如何部署人工智能以及如何理解其风险、问题和可能性的问题。

观察

虽然人工智能作为一个概念自20世纪50年代就已经存在，但所有的人工智能都是不一样的。各种人工智能的能力和风险明显不同，在检查中出现了三个人工智能时代。人工智能1.0包括符号人工智能，它试图将人类知识编码成计算规则，以及概率模型。人工智能2.0时代始于深度学习，在深度学习中，模型从贴有地面事实标签的例子中学习。这个时代在人们的日常生活和医疗保健方面都带来了许多进步。深度学习模型是特定于任务的，这意味着它们一次只做一件事，并且它们主要专注于分类和预测。人工智能3.0是基础模型和生成式人工智能的时代。人工智能3.0中的模型具有全新的（和潜在的变革性）能力，以及新的风险类型，如幻觉。这些模型可以完成许多不同类型的任务，而无需在新的数据集上重新训练。例如，一个简单的文本指令将改变模型的行为。诸如“为专家顾问写这张便条”和“为患者的母亲写这张便条”这样的提示会产生明显不同的内容。

结论和相关性

基础模型和生成人工智能代表了人工智能能力的一次重大革命，为改善护理提供了巨大的潜力。如今，医疗保健领导者正在就人工智能做出决策。虽然任何启发式方法都会忽略细节并失去细微差别，但AI 1.0、2.0和3.0的框架可能对决策者有帮助，因为每个时代都有根本不同的能力和风险。

英文原文如下：

Abstracts

Importance  Interest in artificial intelligence (AI) has reached an all-time high, and health care leaders across the ecosystem are faced with questions about where, when, and how to deploy AI and how to understand its risks, problems, and possibilities.

Observations  While AI as a concept has existed since the 1950s, all AI is not the same. Capabilities and risks of various kinds of AI differ markedly, and on examination 3 epochs of AI emerge. AI 1.0 includes symbolic AI, which attempts to encode human knowledge into computational rules, as well as probabilistic models. The era of AI 2.0 began with deep learning, in which models learn from examples labeled with ground truth. This era brought about many advances both in people's daily lives and in health care. Deep learning models are task-specific, meaning they do one thing at a time, and they primarily focus on classification and prediction. AI 3.0 is the era of foundation models and generative AI. Models in AI 3.0 have fundamentally new (and potentially transformative) capabilities, as well as new kinds of risks, such as hallucinations. These models can do many different kinds of tasks without being retrained on a new dataset. For example, a simple text instruction will change the model's behavior. Prompts such as "Write this note for a specialist consultant" and "Write this note for the patient's mother" will produce markedly different content.

Conclusions and Relevance  Foundation models and generative AI represent a major revolution in AI's capabilities, ffering tremendous potential to improve care. Health care leaders are making decisions about AI today. While any heuristic omits details and loses nuance, the framework of AI 1.0, 2.0, and 3.0 may be helpful to decision-makers because each epoch has fundamentally different capabilities and risks.

-----------分割线---------

点击链接：https://www.mediecogroup.com/community/user/vip/categories/ ，成为医咖会员，获取12项专属权益。

现在购买可享受最大优惠（买一年送三个月，买两年送一年），2024年2月10日起将不再享有该优惠。