評論
打印
Ladies and gentlemen,
女士們，先生們，
In the midst of all this exciting potential, I see several reasons for caution.
所有這些潛力都令人興奮，但我認為有若干理由需要我們謹慎行事。
First, medical decisions are complex. They depend on context and values such as care and compassion. I doubt that a machine will ever be able to imitate genuine human compassion.
首先，醫療決定是復雜的。它們取決于環境和價值觀，如關愛和同情等。我不認為機器有一天真能模仿真正的人類同情心。
Second, machines can aid the work of doctors, organize, rationalize, and streamline the processes leading to a diagnosis or other medical decision, but artificial intelligence cannot replace doctors and nurses in their interactions with patients.
第二，機器可以協助醫生工作，幫助組織、理順和簡化診斷程序或其它醫療決策過程，但人工智能不能取代醫生和護士與患者之間的相互作用。
Third, we must consider the context and what it means for the lives of people. What good does it do to get an early diagnosis of skin or breast cancer if a country offers no opportunity for treatment, has no specialists or specialized facilities and equipment, or if the price of medicines is unaffordable for both patients and the health system?
第三，我們必須考慮環境及其對人們生活的意義。如果一個國家不提供治療機會，沒有專家或專門的設施和設備，或者藥物的價格對于患者和衛生系統都不可負擔，那么對皮膚癌或乳腺癌進行早期診斷又有什么意義？
What happens if a diagnosis by smartphone app misses a symptom that signals a severe underlying disease? Can you sue a machine for medical malpractice?
如果智能手機應用程序的診斷忽視了表明某種嚴重基礎病的癥狀，會發生什么？你能起訴一臺機器造成了醫療事故嗎？
Medicines and medical devices are heavily regulated, and with good reason. Medical schools are accredited. Doctors and nurses are licensed to practice and are often required to undergo continuing education. How do you regulate a machine programmed to think like a human?
藥品和醫療裝置受到嚴格管制，這樣做有充分的理由。醫學院校須得到資格認證。醫生和護士須獲得許可方能從業，且需要經常接受持續教育。如何對一臺經過編程能夠像人一樣思考的機器進行管制？
Regulatory issues must be solved before a new AI technology reaches the market. The reliability of wearable devices for monitoring cardiovascular performance is already being questioned. Medical history is replete with examples of technologies that were eventually rejected because they created a false sense of safety and security.
在新的人工智能技術進入市場之前，必須解決監管問題。用于監測心血管性能的穿戴式裝置的可靠性已經受到質疑。醫學史上因為造成虛假的安全保障感而最終被拒絕的技術比比皆是。
The mining of huge amounts of data raises serious issues of patient privacy and the sacrosanct confidentiality of medical records. This is another set of issues that must be addressed in advance.
數據的大量挖掘會給病人隱私和病歷不可侵犯的保密性造成嚴重問題。這是另一組必須提前解決的問題。
Finally, we need to keep in mind that many developing countries do not have a great deal of health data to mine. These are countries that still do not have functioning information systems for civil registration and vital cause-of-death statistics.
最后，我們要記住，許多發展中國家沒有可挖掘的大量衛生數據。這些國家仍然不具備能運作的民事登記信息系統和重要的死因統計數據。
In short, the potential of AI in health care is huge, but so is the need to take some precautions.
總之，人工智能在衛生保健領域的潛力是巨大的，但采取某些預防措施的需要也是巨大的。
Thank you.
謝謝大家。
