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. /?ɡr?pl/ 1.~ (with sb/sth) 扭打；搏斗??Passers-by grappled with the man after the attack. 襲擊之后過路人便與這男人扭打起來。2.~ (with sth) 努力設(shè)法解決??I was grappling to find an answer to his question. 我正在努力解決他的問題。

Alleviate??v./??li?vie?t/減輕；緩和；緩解?? to alleviate suffering 減輕苦難

into the red：負債；財政情況欠佳

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. /?pleθ?r?/ 過多；過量；過剩

"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 逃脫懲罰? The criminals know how to play the system and get away with it. 那些罪犯知道怎樣鉆制度的空子并逃脫懲罰。

Inference：n. /??nf?r?ns/ ?

1. 推斷的結(jié)果；結(jié)論 ?to draw/make inferences from the data 根據(jù)資料推論出結(jié)果

2.推斷；推理；推論 ?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，那么由此可以推斷他的妻子也同樣有罪。

Spillover：影響，事物傳播、影響到其他情形或者地方帶來的影響

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 /pi?k/ n 怨恨；憤恨；惱怒?When he realized nobody was listening to him, he left in a fit of pique . 他發(fā)覺無人理睬他的話，就憤然離去。凸紋堅挺布料；珠地布；凹凸織物；v. 使憤恨；使惱怒? ?2.??pique sb's ?interest, curi?osity, etc.使…興趣盎然；引起…的好奇

Go：圍棋的意思，是英語引進日語的發(fā)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. /si?d/ ?~ sth (to sb) ( formal ) to give sb control of sth or give them power, a right, etc., especially unwillingly 割讓；讓給；轉(zhuǎn)讓

?Toolkits：工具箱，工具包

譯文

The World in 2021--Intelligent design（智能設(shè)計）

Conventional economic models do not capture the complexity of human behaviour

? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? 傳統(tǒng)經(jīng)濟學(xué)模型不能夠捕捉人類行為的復(fù)雜性。

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.

深陷新冠疫情的債務(wù)，各國政府紛紛準(zhǔn)備抓住2021年讓財政回歸正軌。經(jīng)歷2007-2009年的金融危機，發(fā)達國家財政皮帶勒得太緊，阻礙了經(jīng)濟復(fù)蘇。這次他們想做的聰明一些。有一些政府會很有野心，尋找重新設(shè)計其國家的福利系統(tǒng)：疫情讓公眾更愿意加強支持更強力的社會安全網(wǎng)。窮國政策決策者想要緩和貧窮問題和推動經(jīng)濟可持續(xù)發(fā)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.

如何平衡這些目標(biāo)？一個實驗可能會告訴你一個特定的工具是否有效，一些關(guān)于基本收入的研究項目的發(fā)現(xiàn)，比如肯尼亞的慈善機構(gòu)“直接捐贈”(Give direct)，將會影響政府的想法。但是，要幫助政府制定每年過多的稅收和補貼率，實驗的范圍既不夠廣泛，也不夠及時。傳統(tǒng)經(jīng)濟模型不能夠覆蓋人類行為的復(fù)雜性：當(dāng)稅率升高的時候，人民會改變自己的行為，或者一些官員會腐敗貪污公款。所以2021年，政府想要嘗試應(yīng)用計算機的力量來做政策決策，利用AI模擬經(jīng)濟及其新政策產(chǎn)生的影響。

"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.

“基于參與主體的”模型模擬了經(jīng)濟中不同類型參與者的行為，允許他們在一段時間內(nèi)對彼此做出反應(yīng)：如果一個公務(wù)員可以逃脫貪污的懲罰，或者一位納稅人可以少納稅，他們會選擇這樣做。一些公司通過使用大量數(shù)據(jù)，使用機器學(xué)習(xí)“訓(xùn)練”模型，模擬出令人驚訝的真實行為。其中一種方法是政策優(yōu)先推理，它由英國和墨西哥的研究人員開發(fā)，由聯(lián)合國開發(fā)計劃署贊助。該方法已經(jīng)在墨西哥使用過，它將政府的支出計劃分類，并根據(jù)其對腐敗、低效和溢出效應(yīng)的模擬得出政府是否有可能達到其發(fā)展目標(biāo)，以及應(yīng)該在哪里花更多(或更少)的錢。更多的貧窮國家可以看到這種方法的吸引力。

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?

富國也可能對該應(yīng)用充滿興趣。Salesforce（軟件公司名）研究員和哈佛大學(xué)采用模擬得出--電腦不僅可以學(xué)習(xí)和下圍棋，能開發(fā)出人類想不到的圍棋策略，也可能會弄出官僚想不到的最大優(yōu)化經(jīng)濟效應(yīng)的稅收支出混合策略。因此，為什么不嘗試一下新的點子呢？

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.

這并不意味著經(jīng)濟學(xué)家或官僚們會在2021年失業(yè)。解釋模型結(jié)果需要專業(yè)知識。政客們不會放棄提高和降低稅率的權(quán)力。但是熱衷于檢測疫情余波的決策者和研究人員將有機會擴大他們的工具包。

經(jīng)濟學(xué)人--2020年12月刊