终有一天，给你看病的是人工智能医生

Artificial intelligence holds huge promise in health care. But it also faces massive barriers which are better diagnoses， personalized support for patients， faster drug discovery， and greater efficiency. Artificial intelligence （AI） is generating excitement and hyperbole （夸张） everywhere， but in the field of health care it has the potential to be transformational. In Europe， analysts predict that deploying AI could save hundreds of thousands of lives each year. From smart stethoscopes （听诊器） and robot surgeons to the analysis of large data sets or the ability to chat to a medical AI with a human face， opportunities abound.

There is already evidence that AI systems can enhance diagnostic accuracy and disease tracking， improve the prediction of patients’ outcomes and suggest better treatments. It can also boost efficiency in hospitals and surgeries by taking on tasks such as medical transcription and monitoring patients， and by streamlining administration. It may already be speeding the time it takes for new drugs to reach clinical trials. New tools， including generative AI， could supercharge these abilities. Yet as our Technology Quarterly this week shows， although AI has been used in health care for many years， integration has been slow and the results have often been mediocre.

There are good and bad reasons for this. The good reasons are that health care demands high evidentiary barriers when introducing new tools， to protect patients’ safety. The bad reasons involve data， regulation and incentives. Overcoming them could hold lessons for AI in other fields.

AI systems learn by processing huge volumes of data， something health-care providers have in abundance. But health data is highly fragmented; strict rules control its use. Governments recognize that patients want their medical privacy protected. But patients also want better and more personalized care. Each year roughly 800，000 Americans suffer from poor medical decision-making.

Improving accuracy and reducing bias in AI tools requires them to be trained on large data sets that reflect patients’ full diversity. Finding secure ways to allow health data to move more freely would help. But it could benefit patients， too： they should be given the right to access their own records in a portable， digital format. Consumer-health firms are already making use of data from wearables， with varying success.

Another problem is managing and regulating these innovations. In many countries， the governance of AI in health， as in other areas， is struggling to keep up with the rapid pace of innovation. Regulatory authorities may be slow to approve new AI tools or may lack capacity and expertise. Governments need to equip regulators to assess new AI tools. They also need to fill regulatory gaps in the surveillance of adverse events，and in the continuous monitoring of algorithms （算法） to ensure they remain accurate， safe， effective and transparent.

（材料来自The Economist，有删改）

1.What is the main topic of the passage？

A. The limitations of AI in healthcare.

B. The potential of AI in healthcare.

C. The challenges of deploying AI in healthcare.

D. The economic impact of AI on healthcare.

2. In the context of the passage， what does the underlined word “mediocre” in the second paragraph mean？

A. Average or slightly below average.

B. Extremely good.

C. Innovative.

D. Cost-effective.

3. What is suggested as a way to improve the accuracy and reduce bias in AI tools？

A. Training AI on smaller and more focused data sets.

B. Allowing health data to move more freely in secure ways.

C. Limiting access to patient records to protect privacy.

D. Relying on AI for all medical decisions.

4. What is the author’s writing purpose of the last paragraph？

A. To discourage the use of AI in healthcare.

B. To argue that AI has no place in healthcare.

C. To highlight the challenges and suggest areas for improvement.

D. To compare healthcare AI to AI in other industries.

1. B。解析：主旨大意题。材料主要讨论了人工智能在医疗保健领域的变革潜力，以及实现这一潜力所需克服的巨大障碍。B选项“人工智能在医疗保健中的潜力”与材料内容相符，故选B。

2. A。解析：词义理解题。材料第二段的最后一句提到“尽管人工智能已在医疗保健中应用多年，但集成速度缓慢，结果往往是平庸的”，根据其转折关系可以判断出“mediocre”指的是平均或略低于平均的结果，故选A。

3. B。解析：推理判断题。材料第五段的第一、二句提到“提高人工智能工具的准确性和减少偏见需要……找到允许健康数据更自由移动的安全方法将有所帮助”，B选项“允许健康数据以安全的方式更自由地移动”与材料内容相符，故选B。

4. C。解析：观点态度题。材料最后一段提到了“另一个问题是管理和规范这些创新。在许多国家，人工智能……正在努力跟上快速的创新步伐……政府需要为……填补不良事件监测和算法持续监测方面的监管空白……”。C选项“强调挑战并提出改进领域”与材料内容相符，故选C。