题目
A)abandonedB)adjustedC)driftsD)fruitfulE)identifiedF)installG)intellectualH) internetI)originatesJ)perspectiveK)posiiveL)retainM)sakeN)stroveO)tackleThese days everyone is talking about the fascinating things artificial intelligence can do ike the human brain.Nevertheless,t might be wise to put府into 29)True it can deal with data more quickly and accurately thanhumans, but it can also 30) our biases (偏见). For the 31)of learning, it needs large quantities of data,and the easiest way to find that data is to feed t with text from the 32)But these data contain some extremelybiased language. A Stanford study found that web-based Al connected white names with 33)words like "love,and black names with negative words like "failure" and "cancer "Luminoso Chief Science Officer Rob Speer is in charge of the data set ConceptNet Numberbatch, which is used as aknowledge base for Al systems. He tested one of Numberbatch's data sources and found obvious problems with their wordconnections. When fed the question "Man is to woman as shopkeeper is to.." the system filled in "housewife." So Speer34)for the clearing up of the biases in Concept Net. He 35)inappropriate connections and 36)them to zero, while maintaining appropriate connections like "man/uncle" and "woman/aunt." He did the samewith words related to race and religionBias 37)in human thinking. To fight human bias, it takes a human. So Al developers have a hugeresponsibiity tofind the problems in their Al and 38)them.
A)abandonedB)adjustedC)driftsD)fruitfulE)identifiedF)installG)intellectualH) internetI)originatesJ)perspectiveK)posiiveL)retainM)sakeN)stroveO)tackleThese days everyone is talking about the fascinating things artificial intelligence can do ike the human brain.Nevertheless,t might be wise to put府into 29)True it can deal with data more quickly and accurately thanhumans, but it can also 30) our biases (偏见). For the 31)of learning, it needs large quantities of data,and the easiest way to find that data is to feed t with text from the 32)But these data contain some extremelybiased language. A Stanford study found that web-based Al connected white names with 33)words like "love,and black names with negative words like "failure" and "cancer "Luminoso Chief Science Officer Rob Speer is in charge of the data set ConceptNet Numberbatch, which is used as aknowledge base for Al systems. He tested one of Numberbatch's data sources and found obvious problems with their wordconnections. When fed the question "Man is to woman as shopkeeper is to.." the system filled in "housewife." So Speer34)for the clearing up of the biases in Concept Net. He 35)inappropriate connections and 36)them to zero, while maintaining appropriate connections like "man/uncle" and "woman/aunt." He did the samewith words related to race and religionBias 37)in human thinking. To fight human bias, it takes a human. So Al developers have a hugeresponsibiity tofind the problems in their Al and 38)them.
题目解答
答案
29Cdrifts激流，说明现在AI快速发展30Lretain保留，确实它可以比人类更快，更准确地处理数据，但也可以保留我们的偏见31Jperspectiv在ai学习的意见来看，它需要大量数据32HInternet来自于互联网的文本数据33Kpositive基于网络的Al将白色名称与积极单词（如“爱”）和黑色名称与否定单词（如“失败”和“癌症”）联系起来35Aabandoned科学家放弃不适当的连接，36Badjusted将它们设置为零37Ioriginates偏见起源于人类，要克服人类的偏见，需要人类38Otackle解决，发现问题并解决他们
解析
步骤 1：理解背景信息
- 人工智能（AI）可以像人类大脑一样处理数据，但也会保留人类的偏见。
- AI需要大量数据来学习，而这些数据通常来自互联网，其中包含有偏见的语言。
- 一个斯坦福大学的研究发现，基于网络的AI将白人名字与积极词汇（如“爱”）联系起来，而将黑人名字与消极词汇（如“失败”和“癌症”）联系起来。
- Luminoso首席科学官Rob Speer负责一个名为ConceptNet Numberbatch的数据集，该数据集被用作AI系统的知识库。
- Speer发现数据集中的词汇连接存在问题，例如“男人是女人，就像店主是……”系统回答“家庭主妇”。
- Speer努力清除ConceptNet中的偏见，他放弃不适当的连接，并将它们调整为零，同时保持适当的连接，如“男人/叔叔”和“女人/阿姨”。
- 偏见起源于人类思维，要克服人类的偏见，需要人类。
- 因此，AI开发者有责任发现并解决他们AI中的问题。
步骤 2：选择合适的单词
- 29. C)drifts：说明现在AI快速发展。
- 30. L)retain：确实它可以比人类更快，更准确地处理数据，但也可以保留我们的偏见。
- 31. J)perspective：在AI学习的意见来看，它需要大量数据。
- 32. H)Internet：来自于互联网的文本数据。
- 33. K)positive：基于网络的AI将白色名称与积极单词（如“爱”）和黑色名称与否定单词（如“失败”和“癌症”）联系起来。
- 34. N)strove：科学家努力清除偏见。
- 35. A)abandoned：科学家放弃不适当的连接。
- 36. B)adjusted：将它们设置为零。
- 37. I)originates：偏见起源于人类。
- 38. O)tackle：解决问题。
- 人工智能（AI）可以像人类大脑一样处理数据，但也会保留人类的偏见。
- AI需要大量数据来学习，而这些数据通常来自互联网，其中包含有偏见的语言。
- 一个斯坦福大学的研究发现，基于网络的AI将白人名字与积极词汇（如“爱”）联系起来，而将黑人名字与消极词汇（如“失败”和“癌症”）联系起来。
- Luminoso首席科学官Rob Speer负责一个名为ConceptNet Numberbatch的数据集，该数据集被用作AI系统的知识库。
- Speer发现数据集中的词汇连接存在问题，例如“男人是女人，就像店主是……”系统回答“家庭主妇”。
- Speer努力清除ConceptNet中的偏见，他放弃不适当的连接，并将它们调整为零，同时保持适当的连接，如“男人/叔叔”和“女人/阿姨”。
- 偏见起源于人类思维，要克服人类的偏见，需要人类。
- 因此，AI开发者有责任发现并解决他们AI中的问题。
步骤 2：选择合适的单词
- 29. C)drifts：说明现在AI快速发展。
- 30. L)retain：确实它可以比人类更快，更准确地处理数据，但也可以保留我们的偏见。
- 31. J)perspective：在AI学习的意见来看，它需要大量数据。
- 32. H)Internet：来自于互联网的文本数据。
- 33. K)positive：基于网络的AI将白色名称与积极单词（如“爱”）和黑色名称与否定单词（如“失败”和“癌症”）联系起来。
- 34. N)strove：科学家努力清除偏见。
- 35. A)abandoned：科学家放弃不适当的连接。
- 36. B)adjusted：将它们设置为零。
- 37. I)originates：偏见起源于人类。
- 38. O)tackle：解决问题。