Seven years have passed since world leaders met in New York and agreed on17可持续发展目标(SDGs) to resolve major challenges including poverty, hunger, inequality, climate change and health.
在过去的几年中，大流行无疑从其中一些问题转移了关注。但是甚至在Covid-19之前，联合国正在警告that progress to meet the SDGs was not advancing at the speed or on the scale needed. Meeting them by 2030 will be tough.
但是我仍然乐观。大流行一无所有，为了社会的利益而在边界上进行协作的力量。它集中精力，资金和政策，以加快对病毒检测，疾病治疗，疫苗和制造平台的研究。
人工智能在加速可持续发展目标中的作用
这是全球社区的一项巨大努力，在首次检测到病毒后的一年内开发有效的疫苗，这些和其他治疗已大大降低了病毒的死亡率。这可以归因于世界各地科学家的才华，毅力和创造力。但是他们并不是一个人工作：人工智能（AI）也发挥了关键作用。
这U.S. company Moderna was among the first to release an effective COVID-19 vaccine. One reason it was able to make this breakthrough so quickly was the use of AI to speed up development. Moderna Chief Data and Artificial Intelligence Officer Dave Johnson解释that AI algorithms and robotic automation helped them move from manually producing around 30 mRNAs (a molecule fundamental to the vaccine) each month to being able to produce around 1,000 a month.
Moderna还使用人工智能来帮助其mRNA序列设计。它的联合创始人Noubar Afeyan最近预测during a visit to ImperialCollege London that immune medicine will see "large advances" in the coming years, and we can look forward to a future where medicine is more preemptive than reactionary.
这re are numerous examples of how advances in AI could support our understanding of climate change (SDG13), enable our transition to sustainable transport systems (SDG11) and accelerate agri-tech ...
他说：“如果我们能尽早发现疾病并延迟疾病，至少会以更低的成本产生更大的影响。”这是一个很好的例子，说明了AI如何为科学家腾出时间加速发现并致力于解决重大挑战的努力。
我们还看到了其他医疗保健其他领域（例如癌症和疟疾疾病筛查）改进AI技术的例子。Google Health，DeepMind，NHS，NHS，西北大学和帝国同事的研究人员已经设计和训练了AI模型从X射线图像中发现乳腺癌。
这computer algorithm, which was trained using mammography images from almost 29,000 women, was shown to be as effective as human radiologists in spotting cancer. At a time when世界各地的卫生服务已伸展当他们处理大流行后的长期积压患者时，这种技术可以帮助缓解瓶颈并改善治疗。
对于疟疾而言，使用AI开发的手持式实验室分子诊断系统可能会彻底改变非洲偏远地区的疾病如何检测到这种疾病。在非洲网络的数字诊断领导下，该项目汇集了合作者，例如加纳的Minohealth AI实验室和伦敦帝国学院的全球发展中心。这项技术可以为普遍的健康覆盖范围铺平道路，并促使我们迈向实现SDG3。
还有许多其他例子说明AI的进步如何支持我们对气候变化的理解（SDG13），使我们能够过渡到可持续运输系统（SDG11）（SDG11）并加速农业技术，以帮助农民最终的食品贫困和营养不良（SDG2），包括许多好处也是其他可持续发展目标。
例如，英国国家数据科学与人工智能中心艾伦·图灵研究所（Alan Turing Institute）正在使用机器学习来更好地了解复杂的互动between climate and Arctic sea ice.
With an expanding global population,我们面临食物需求和生产的挑战- 不仅如何减少营养不良，而且对地球的影响，例如森林砍伐，排放和生物多样性损失。为了满足这些需求，人工智能在农业中的使用正在迅速增长，并使农民能够增强作物生产，直接机械能够自动执行任务并在发生之前识别害虫侵扰。
Smart sensing technology is also helping farmers use fertilizer more effectively and reduce environmental damage.一个激动人心的研究项目, funded by the EPSRC, Innovate UK and Cytiva, will help growers optimize timing and amount of fertilizer to use on their crops, taking into account factors such as the weather and soil condition. This will reduce the expense and damaging effects of overfertilizing soil.
发展可持续和智能运输系统也将至关重要，因为城市和国家希望减少空气污染的影响并改善基础设施。在过去的十年中，AI为运输和机动性的革命提供了动力，从自动驾驶汽车到乘车共享应用程序和路线规划器。AI还被用来使公共交通系统更有效，减少交通拥堵和污染并提高安全性。
Despite its benefits to research and medicine, integrating AI into society and innovation is not always smooth sailing. Recent controversies on facial recognition, automated decision-making and COVID-related tracking, have led to some caution and suspicion. We need to ensure that AI is employed in ways that are trusted, transparent and inclusive. We need to make sure that there is an internationally coordinated, collaborative approach, just as there was in the pandemic.
这世界经济论坛的全球AI行动联盟brings together more than 100 leading companies, governments, international organizations, non-profits and academics united in a commitment to maximize AI's societal benefits while minimizing its risks.
我们必须采用良好的流程和实践来确保以积极和道德的方式开发AI，以使其被公民和政府充分地采用并充分利用它。
We must now work together to ensure that artificial intelligence can accelerate progress of the Sustainable Development Goals and help us get back on track to reaching them by 2030.
