The World in 2021--Intelligent design

Conventional economic models do not capture the complexity of human behaviour

HAVING GONE deep into the red during the covid-19 pandemic, governments will grapple in 2021 with getting their finances back in order. After the global financial crisis of 2007-09, those in rich countries tightened their belts too much, choking the economic recovery.This time they will want to be cleverer about it. Some will be more ambitious, seeking to redesign their welfare systems: the pandemic will strengthen public support for stronger social safety-nets. And policymakers in poor countries will want to alleviate poverty and sustain economic development.

Grapple  v. /ˈɡræpl/ 1.~ (with sb/sth) 扭打；搏斗 •Passers-by grappled with the man after the attack. 袭击之后过路人便与这男人扭打起来。2.~ (with sth) 努力设法解决 •I was grappling to find an answer to his question. 我正在努力解决他的问题。

Alleviate  v./əˈliːvieɪt/减轻；缓和；缓解 • to alleviate suffering 减轻苦难

into the red：负债；财政情况欠佳

How to balance all these aims? An experiment might tell you if a particular tool works, and findings from projects on basic income, such as that run in Kenya by Give Directly, a charity, will influence governments’ thinking. But experiments can be neither broad nor timely enough to help governments set a plethora of tax and subsidy rates every year. Conventional economic models do not capture the complexity of human behaviour: that people change what they do as tax rates rise, or that corrupt officials might pocket some public funds. So in 2021 governments will be tempted to throw computational power at their policymaking, using artificial intelligence (AI) to simulate the economy, and the effects of new policies.

Plethora  n. /ˈpleθərə/ 过多；过量；过剩

"Agent-based"models simulate the behaviour of different types of participants in the economy by allowing them to respond to each other over time: if a public servant can get away with pocketing more money, or a taxpayer with payingless tax, then they will do so. Some simulate surprisingly realistic behaviour by using machine learning to "train" the model using vast sets of data. One such approach is Policy Priority Inference, developed by researchers in Britain and Mexico and sponsored by the UN's development programme. Already used in Mexico, it takes governments' spending plans across a range of categories and works out, based on its simulation of corruption, inefficiencies and spillovers, whether a government is likely to hit its development goals, and where more (or less) money should be spent. More poor countries could see the appeal of such an approach.

get away with 逃脱惩罚• The criminals know how to play the system and get away with it. 那些罪犯知道怎样钻制度的空子并逃脱惩罚。

Inference：n. /ˈɪnfərəns/  

1. 推断的结果；结论 •to draw/make inferences from the data 根据资料推论出结果

2.推断；推理；推论 •If he is guilty then, by inference , so is his wife (= it is logical to think so, from the same evidence) . 如果他有罪，那么由此可以推断他的妻子也同样有罪。

Spillover：影响，事物传播、影响到其他情形或者地方带来的影响

Interest in rich countries could be piqued, too. Researchers at Salesforce, a software company, and Harvard University have used simulations to show that, much as computers can learn to play Go and develop strategies that might not occur to humans, they can also suggest combinations of tax and spending that maximise economic performance, and which bureaucrats might not have dreamed up. So why not turn to AI for fresh ideas?

pique /piːk/ n 怨恨；愤恨；恼怒•When he realized nobody was listening to him, he left in a fit of pique . 他发觉无人理睬他的话，就愤然离去。凸纹坚挺布料；珠地布；凹凸织物；v. 使愤恨；使恼怒   2. ˌpique sb's ˈinterest, curiˈosity, etc.使…兴趣盎然；引起…的好奇

Go：围棋的意思，是英语引进日语的发音

None of this means that economists or bureaucrats will find themselves out of work in 2O21. Interpreting the models' results requires expertise. Politicians will not cede their power to raise and lower tax rates. But policymakers and researchers keen to experiment in the aftermath of the pandemic will have an opportunity to expand their toolkits.

Cede  v. /siːd/  ~ sth (to sb) ( formal ) to give sb control of sth or give them power, a right, etc., especially unwillingly 割让；让给；转让

 Toolkits：工具箱，工具包

译文

The World in 2021--Intelligent design（智能设计）

Conventional economic models do not capture the complexity of human behaviour

                                传统经济学模型不能够捕捉人类行为的复杂性。

HAVING GONE deep into the red during the covid-19 pandemic, governments will grapple in 2021 with getting their finances back in order. After the global financial crisis of 2007-09, those in rich countries tightened their belts too much, choking the economic recovery.This time they will want to be cleverer about it. Some will be more ambitious, seeking to redesign their welfare systems: the pandemic will strengthen public support for stronger social safety-nets. And policymakers in poor countries will want to alleviate poverty and sustain economic development.

深陷新冠疫情的债务，各国政府纷纷准备抓住2021年让财政回归正轨。经历2007-2009年的金融危机，发达国家财政皮带勒得太紧，阻碍了经济复苏。这次他们想做的聪明一些。有一些政府会很有野心，寻找重新设计其国家的福利系统：疫情让公众更愿意加强支持更强力的社会安全网。穷国政策决策者想要缓和贫穷问题和推动经济可持续发展。

How to balance all these aims? An experiment might tell you if a particular tool works, and findings from projects on basic income, such as that run in Kenya by Give Directly, a charity, will influence governments’ thinking. But experiments can be neither broad nor timely enough to help governments set a plethora of tax and subsidy rates every year. Conventional economic models do not capture the complexity of human behaviour: that people change what they do as tax rates rise, or that corrupt officials might pocket some public funds. So in 2021 governments will be tempted to throw computational power at their policymaking, using artificial intelligence (AI) to simulate the economy, and the effects of new policies.

如何平衡这些目标？一个实验可能会告诉你一个特定的工具是否有效，一些关于基本收入的研究项目的发现，比如肯尼亚的慈善机构“直接捐赠”(Give direct)，将会影响政府的想法。但是，要帮助政府制定每年过多的税收和补贴率，实验的范围既不够广泛，也不够及时。传统经济模型不能够覆盖人类行为的复杂性：当税率升高的时候，人民会改变自己的行为，或者一些官员会腐败贪污公款。所以2021年，政府想要尝试应用计算机的力量来做政策决策，利用AI模拟经济及其新政策产生的影响。

"Agent-based"models simulate the behaviour of different types of participants in the economy by allowing them to respond to each other over time: if a public servant can get away with pocketing more money, or a taxpayer with payingless tax, then they will do so. Some simulate surprisingly realistic behaviour by using machine learning to "train" the model using vast sets of data. One such approach is Policy Priority Inference, developed by researchers in Britain and Mexico and sponsored by the UN's development programme. Already used in Mexico, it takes governments' spending plans across a range of categories and works out, based on its simulation of corruption, inefficiencies and spillovers, whether a government is likely to hit its development goals, and where more (or less) money should be spent. More poor countries could see the appeal of such an approach.

“基于参与主体的”模型模拟了经济中不同类型参与者的行为，允许他们在一段时间内对彼此做出反应：如果一个公务员可以逃脱贪污的惩罚，或者一位纳税人可以少纳税，他们会选择这样做。一些公司通过使用大量数据，使用机器学习“训练”模型，模拟出令人惊讶的真实行为。其中一种方法是政策优先推理，它由英国和墨西哥的研究人员开发，由联合国开发计划署赞助。该方法已经在墨西哥使用过，它将政府的支出计划分类，并根据其对腐败、低效和溢出效应的模拟得出政府是否有可能达到其发展目标，以及应该在哪里花更多(或更少)的钱。更多的贫穷国家可以看到这种方法的吸引力。

Interest in rich countries could be piqued, too. Researchers at Salesforce, a software company, and Harvard University have used simulations to show that, much as computers can learn to play Go and develop strategies that might not occur to humans, they can also suggest combinations of tax and spending that maximise economic performance, and which bureaucrats might not have dreamed up. So why not turn to AI for fresh ideas?

富国也可能对该应用充满兴趣。Salesforce（软件公司名）研究员和哈佛大学采用模拟得出--电脑不仅可以学习和下围棋，能开发出人类想不到的围棋策略，也可能会弄出官僚想不到的最大优化经济效应的税收支出混合策略。因此，为什么不尝试一下新的点子呢？

None of this means that economists or bureaucrats will find themselves out of work in 2O21. Interpreting the models' results requires expertise. Politicians will not cede their power to raise and lower tax rates. But policymakers and researchers keen to experiment in the aftermath of the pandemic will have an opportunity to expand their toolkits.

这并不意味着经济学家或官僚们会在2021年失业。解释模型结果需要专业知识。政客们不会放弃提高和降低税率的权力。但是热衷于检测疫情余波的决策者和研究人员将有机会扩大他们的工具包。

经济学人--2020年12月刊