雙語： 陳馮富珍總幹事人工智慧惠及人類全球峰會開幕致辭

Opening Remarks at the Artificial Intelligence for Good Global Summit

「人工智慧惠及人類全球峰會」開幕致辭

Dr. Margaret Chan, Director-General of the World Health Organization

世界衛生組織總幹事 陳馮富珍博士

Geneva, Switzerland

瑞士 日內瓦

7 June 2017

2017年6月7日

Fellow UN agencies, experts in artificial intelligence, representatives of industry, ladies and gentlemen,

聯合國機構的同事們、人工智慧領域的專家們、業界代表們、女士們、先生們，

I welcome this opportunity to learn from the vast amount of technical expertise assembled in this room.

今天這裡彙集了大量技術專長，我很高興能有此機會從中學習。

Market analysts predict that intelligent machines, programmed to think and reason like the human mind, will revolutionize health care in the very near future. In fact, proponents of the transformative power of artificial intelligence usually give two examples: self-driving cars and the delivery of health care.

市場分析師們預言，在不久的將來，經過編程能夠像人腦一樣思考和推理的智能機器將在衛生保健領域引起突破性變革。確切說，人工智慧變革力量的支持者們常常會舉兩個例子：自駕車和衛生保健服務的提供。

This year』s influential Internet Trends Report, released last week in the USA, covers the effects of new technology on health care for the first time, again predicting a huge transformative impact.

上周在美國發布了今年的《互聯網趨勢報告》，很有影響力，首次論及了新技術對衛生保健的影響，再次預言了巨大的變革性衝擊。

Artificial intelligence is a new frontier for the health sector. As so often happens, the speed of technological advances has outpaced our ability to reflect these advances in sound public policies and address a number of ethical dilemmas.

人工智慧是衛生部門的新前沿。然而正如經常發生的情況一樣，技術進步的速度超過了我們的能力，我們難以及時在合理的公共政策中反映這些進步，並解決一系列倫理難題。

Many questions do not yet have answers and we are not yet sure we know all the questions that need to be asked.

許多問題尚未找到答案，而且我們對所有需要問的問題也尚不確定。

Much of the enthusiasm for the use of smart machines to improve health care reflects the perspectives of wealthy countries and well-resourced private companies. We need a broader perspective.

目前熱衷於使用智能機器來改善衛生保健服務的多是富裕國家和資源豐富的私營公司。我們需要聽取更廣泛的意見。

I find it wise to look at potential benefits, risks, and ethical dilemmas in the context of several worldwide trends that shape priority health needs.

我認為明智的做法是，結合決定重點衛生需求的若干全球趨勢來審視潛在的利益、風險和倫理難題。

Over the past decade, I have visited many countries where the majority of health facilities lack such basics as electricity and running water. I would be hard-pressed to sell these countries on the advantages of artificial intelligence when even standard machines for analysing patient samples or sterilizing equipment cannot run for want of electrical supplies.

在過去十年中，我訪問過許多國家，它們的大多數衛生機構都缺乏電力和自來水等基本要素。在這些國家，因為缺乏電力供應連用於分析患者樣本或消毒設備的標準機器也不能運轉，我實在很難向它們宣傳人工智慧的優勢。

Any discussion of the potential of smart machines to revolutionize the delivery of health care must be alert to these huge gaps in basic capacities.

關於智能機器革新衛生保健服務的潛力的任何討論都必須注意基本能力方面的這些巨大差距。

At the same time, I have also observed the ubiquitous presence of smartphone even in the most resource-constrained settings. Schools may not have toilets or latrines. Children may not have shoes. But smart phones are ready to hand.

同時，我也看到智能手機無處不在，即使在資源最有限的環境中也是如此。學校可能沒有廁所，孩子可能沒有鞋子，但智能手機卻便捷可得。

The traditional dichotomy between health conditions in rich and poor countries no longer holds. Health everywhere is being shaped by the same dominant forces, namely population ageing, rapid unplanned urbanization, and the globalized marketing of unhealthy products.

窮國與富國衛生狀況之間的傳統二分法已不再成立。決定世界各地衛生狀況的是相同的主導力量，即人口老齡化，迅速無計劃的城市化，以及不健康產品的全球化營銷。

Under the pressure of these forces, chronic noncommunicable diseases have overtaken infectious diseases as the leading killers worldwide.

在這些力量的壓力下，慢性非傳染性疾病已經超過了傳染病，成為全世界的主要殺手。

Diseases like heart disease, cancer, diabetes, and chronic respiratory diseases are profoundly shaped by human behaviours and the environments in which people make their lifestyle choices.

心臟病、癌症、糖尿病和慢性呼吸道疾病等疾病深受人類行為和促成人們生活方式選擇的環境的影響。

These are among the most democratic of all diseases, affecting all income groups in all places. They are also the most costly.

這些屬於最普遍的疾病，影響到世界各地各種收入層次的人群。同時也是代價最高的。

Could artificial intelligence help improve lifestyle choices? Could smart machines help consumers understand the meaning of food labels or interpret restaurant menu options? Could a smartphone app help people with diabetes maintain good metabolic control between visits to a doctor?

人工智慧可以幫助改善生活方式的選擇嗎？智能機器能幫助消費者了解食品標籤的含義或解釋餐廳菜單中的選項嗎？智能手機應用程序能幫助糖尿病患者在兩次就診之間保持良好的代謝控制嗎？

Moreover, the demands of long-term if not life-long treatment for chronic conditions have placed unsustainable pressure on an overloaded health workforce. The high-level Commission on health employment and economic growth estimates that the management of NCDs and conditions like dementia will require 40 million new health workers by 2030 in wealthy countries. In contrast, the developing world is expected to experience a shortfall of 18 million health workers.

此外，慢性病的長期（如果說不是終生）治療需求對負擔已過重的衛生人力施加了無法承受的壓力。據衛生領域就業和經濟增長高級別委員會估計，到2030年，富裕國家為管理非傳染性疾病和痴呆症等病症將需要新增4000萬衛生工作者。相比之下，發展家預計會短缺1800萬衛生工作者。

The waves of populism and anti-globalization sentiment that are sweeping through some parts of the world are driven, in part, by technological advances that have eliminated many jobs, especially for the middle class.

在世界一些地區蔓延的民粹主義和反全球化情緒，部分上是因為技術進步淘汰了許多工作，尤其是對於中產階級而言。

Given the significant shortage of health workers, the application of artificial intelligence to health care could potentially reduce some of the burden on overloaded health staff. This is one advantage: revolutionary new technologies will certainly meet some resistance from the medical profession, but not, for the time being, because they threaten jobs.

鑒於衛生工作者嚴重短缺，將人工智慧應用於衛生保健可能會減少已超負荷的衛生人員的部分負擔。這是一個優勢。革命性的新技術將必定會遇到來自醫學界的一些阻力，但這不是（至少目前不是）因為會威脅到就業。

Given the power of super computers and superchips to mine and organize huge amounts of data, it is easy to envision a number of applications in the health sector.

鑒於超級計算機和超級晶元具有挖掘和組織大量數據的能力，因此很容易為衛生部門設想一些應用程序。

As we all know, health information is often messy and poorly structured. In many cases, it is systematically collected but not systematically analysed and used. Artificial intelligence can give that data a structure, and by detecting patterns, guide some medical decisions.

眾所周知，衛生信息往往凌亂且結構欠佳。在許多情況下，能夠系統地收集卻不能系統地進行分析和使用。人工智慧可以為數據提供一個結構，並通過檢測模式來指導一些醫療決策。

Supercomputers can accelerate the screening of novel molecules in the search for new drugs. They can speed up the reading and interpretation of results from radiographs, electrocardiograms, ultrasound and CT scans, and even the analysis of blood samples.

超級計算機可以在尋找新藥方面加速對新分子的篩選。它們可以加快對X光片，心電圖，超聲和CT掃描結果的讀取和闡釋，甚至可加快對血液樣本的分析。

By reducing the likelihood of human errors, they can contribute to more precise diagnoses and predictions of patient prognoses, and to enhanced patient safety.

通過減少人為錯誤的可能性，它們可以有助於更精確地判斷和預測患者預后情況，並增強患者安全。

Other applications currently under development include personal use of smartphones to communicate symptoms and obtain a diagnosis from the cloud. Enthusiastic developers see this as a way to cut down health care costs by keeping the worried well from flooding clinics and emergency rooms.

目前開發中的其它應用程序包括個人使用智能手機來通報癥狀並從雲端獲得診斷。滿腔熱情的開發人員認為這是減少衛生保健費用的一條途徑，可避免憂慮者洪水般涌到診所和急診室。

For patients recovering from a stroke or an accident, developers have already introduced a system, involving sensor technology and the latest advances in cloud computing, that provides tailor-made physiotherapy that can be performed in homes. Immediate feedback scores the number of right and wrong movements. The cost of the system is estimated at one tenth of that for facility-based physiotherapy.

對於正在從中風或事故中恢復的患者，開發人員已經採用了一個系統，涉及感測器技術和雲計算的最新進展，提供可在家中進行的量身定製的物理治療，並可立即提供反饋標出正確與錯誤的動作數量。該系統的成本估計為基於設施的物理治療的十分之一。

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，醫療決定是複雜的。它們取決於環境和價值觀，如關愛和同情等。我不認為機器有一天真能模模擬正的人類同情心。

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，但人工智慧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，或者藥物的價格對於患者和衛生系統都不可負擔，那麼對皮膚癌或乳腺癌進行早期診斷又有什麼意義？

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，會發生什麼？你能起訴一台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。如何對一台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.

在新的人工智慧技術進入市場之前，必須解決監管問題。用於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.

最後，我們要記住，許多發展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，人工智慧在衛生保健領域的潛力是巨大的，但採取某些預防措施的需要也是巨大的。

Thank you.

謝謝大家。