人工智能外文翻译文献.docx

人工智能外文翻译文献.docx

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文献信息：

文献标题：

ResearchPrioritiesforRobustandBeneficialArtificial

Intelligence（稳健和有益的人工智能的研究重点）

国外作者：

StuartRussell,DanielDewey,MaxTegmark

文献出处：

《Association for the Advancement of Artificial

Intelligence》,2015,36（4）:

105-114

字数统计：

英文2887单词，16400字符；中文5430汉字

外文文献：

Research Priorities for Robust and BeneficialArtificial Intelligence Abstract  Success inthequestfor artificialintelligencehasthe potentialto bring unprecedented benefits to humanity, and it is thereforeworthwhile to investigate 

howtomaximizethesebenefitswhileavoidingpotentialpitfalls.Thisarticlegives numerous examples （which should by no means be construed as an exhaustive list） of suchworthwhile research aimed at ensuring thatAI remains robust and beneficial.

Keywords:

 artificial intelligence, superintelligence, robust, beneficial, safety, 

society 

Artificialintelligence （AI） researchhas explored avariety ofproblems and approaches since its inception, but for the last 20 years or so has been focused on the problemssurroundingtheconstructionofintelligentagents–systemsthatperceive and act in some environment. In this context, the criterion for intelligence is related to statistical and economic notions of rationali–tycolloquially, the ability to make good decisions,plans,or inferences.Theadoption of probabilisticrepresentations and statistical learningmethods has led to a largedegree ofintegrationand 

cross-fertilization between AI, machine learning, statistics, control theory, neuroscience, and other fields. The establishment of shared theoretical frameworks, combined with the availability of data and processing power, has yielded remarkable 

successes in various component tasks such as speech recognition, image classification, autonomous  vehicles, machine translation, legged locomotion, and question-answering systems.

As capabilitiesin theseareasand otherscross thethreshold fromlaboratory research to economically valuable technologies, a virtuous cycle takes hold whereby even small improvements in performance are worth large sums of money, prompting greater investments in research. There is now a broad consensus that AI research is progressing steadily, and that its impact on society is likely to increase. The potential benefits are huge, since everything that civilization has to offer is a product of human intelligence;we cannot predictwhatwe mightachievewhen this intelligence is magnified by the tools AI may provide, but the eradication of disease and poverty are notunfathomable.Becauseof thegreatpotentialof AI, it isvaluable to investigate how to reap its benefitswhile avoiding potential pitfalls.

Short-termResearch Priorities OptimizingAI’s Economic Impact

The successesof industrialapplicationsof AI,from manufacturingto informationservices, demonstrate a growing impact on the economy, although there is disagreement about the exact nature of this impact and on how to distinguish between the effects of AI and those of other information technologies.Many economists and computerscientistsagree thatthere isvaluable researchto bedoneon howto maximize the economic benefits of AIwhile mitigating adverse effects, which could includeincreasedinequalityandunemployment（Mokyr2014;Brynjolfssonand McAfee2014;FreyandOsborne 2013; Glaeser 2014; Shanahan 2015; Nilsson 1984; Manyikaetal.2013）.Suchconsiderationsmotivatearangeofresearchdirections,spanning areas from economics to psychology. Below are a few examples that should by no means be interpreted as an exhaustive list. 

Labormarketforecasting:

Whenandinwhatordershouldweexpectvarious jobs to become automated （Frey and Osborne 2013）?

 Howwill this affect the wages oflessskilledworkers,thecreativeprofessions,anddifferentkindsofinformation

workers?

Somehavehavearguedthat AIis likelytogreatlyincreasetheoverallwealth of humanity as a whole （Brynjolfsson and McAfee 2014）. However, increased automation may push income distribution further towards a power law （Brynjolfsson, McAfee,andSpence2014）,andtheresultingdisparitymayfalldisproportionately along lines of race, class, and gender; research anticipating the economic and societal impact of such disparity could be useful. 

Other market disruptions:

Significant parts of the economy, including finance, insurance, actuarial, and many consumer markets, could be susceptible to disruption throughtheuseof AItechniquestolearn,model,andpredicthumanandmarket behaviors.Thesemarketsmightbeidentifiedbyacombinationofhighcomplexity and high rewards for navigating that complexity （Manyika et al. 2013）. 

Policy for managingadverse effects:

 What policies