I'm a meteorologist by degree, I have a bachelor's, master's and PhD in physical meteorology,
从学位上来看，我是气象学家，我有物理气象学的学士、硕士、博士学位，
so I'm a meteorologist, card carrying. And so with that comes four questions, always.
所以我是气象学家，有认证的。这总是会伴随着四个问题。
This is one prediction I will always get right.
我的这项预测是最准的。
And those questions are, "Marshall, what channel are you on?"
那几个问题是：“马歇尔，你在哪一台播气象？”
"Dr. Shepherd, what's the weather going to be tomorrow?"
“谢博德博士，明天的天气如何？”
And oh, I love this one: "My daughter is getting married next September, it's an outdoor wedding. Is it going to rain?"
喔，我很爱这一个：“我女儿明年九月要结婚，是户外婚礼。到时会下雨吗？”
Not kidding, I get those, and I don't know the answer to that, the science isn't there.
不是开玩笑的，我会被问这些问题，但我没有答案，那没有科学。
But the one I get a lot these days is,
但最近我最常被问的是这个：
"Dr. Shepherd, do you believe in climate change?" "Do you believe in global warming?"
“谢博德博士，你相信气候变迁吗？”“你相信全球变暖吗？”
Now, I have to gather myself every time I get that question.
每当我被问那个问题时，我就得打起精神。
Because it's an ill-posed question -- science isn't a belief system.
因为这是个不适定的问题--科学并不是个信念系统。
My son, he's 10 -- he believes in the tooth fairy.
我的儿子十岁--他相信有牙仙。
And he needs to get over that, because I'm losing dollars, fast.
他最好快点度过这段时期，因为我亏钱亏得很快。
But he believes in the tooth fairy. But consider this. Bank of America building, there, in Atlanta.
但他相信有牙仙。但想想这一点。美国银行大楼，位于亚特兰大。
You never hear anyone say, "Do you believe, if you go to the top of that building and throw a ball off, it's going to fall?"
你从来不会听到有人说：“你信不信，如果到那栋大楼的楼顶，把一颗球丢出去，它就会向下落？”
You never hear that, because gravity is a thing.
你从来没有听过，因为重力是客观存在。
So why don't we hear the question, "Do you believe in gravity?"
所以我们不会听到这个问题：“你相信重力吗？”
But of course, we hear the question, "Do you believe in global warming?"
但当然，我们会听到这个问题：“你相信全球变暖吗？”
Well, consider these facts. The American Association for the Advancement of Science, AAAS,
想想看这些事实。美国科学促进会，缩写AAAS，
one of the leading organizations in science, queried scientists and the public on different science topics.
是科学界最重要的组织之一，询问科学家和大众各种不同的科学主题。
Here are some of them: genetically modified food, animal research, human evolution.
以下是其中一些：基因改造食物、动物研究、人类演化。
And look at what the scientists say about those,
看看科学家们对这些主题的说法，
the people that actually study those topics, in red, versus the gray, what the public thinks.
真正在研究那些主题的人是红色的，相对的，灰色是大众的想法。
How did we get there? How did we get there?
我们是怎么走到这一步的？我们是怎么走到这一步的？
That scientists and the public are so far apart on these science issues.
在这些科学议题上，科学家和大众的认知差好多。
Well, I'll come a little bit closer to home for me, climate change.
我挑个我比较熟悉的主题来谈：气候变迁。
Eighty-seven percent of scientists believe that humans are contributing to climate change.
87%的科学家相信人类造成了气候变迁。
But only 50 percent of the public? How did we get there?
但只有50%的民众这么想？我们是怎么走到这一步的？
So it begs the question, what shapes perceptions about science?
这就带出了一个问题：关于科学的认知，是怎么来的？
It's an interesting question and one that I've been thinking about quite a bit.
这是个很有意思的问题，我花了不少时间在思考它。
I think that one thing that shapes perceptions in the public, about science, is belief systems and biases.
我认为，大众对于科学的认知，是由信念系统和偏见所形塑的。
Belief systems and biases. Go with me for a moment.
信念系统和偏见。耐心听我说一下。
Because I want to talk about three elements of that: confirmation bias, Dunning-Kruger effect and cognitive dissonance.
因为我想要谈它的三项元素：确认偏误、达克效应以及认知失调。
Now, these sound like big, fancy, academic terms, and they are.
这些听起来是很博大、很炫的学术名词，的确是的。
But when I describe them, you're going to be like, "Oh! I recognize that; I even know somebody that does that."
但当我描述它们时，你们会说类似：“喔！我知道，我甚至认识有这种状况的人。”
Confirmation bias. Finding evidence that supports what we already believe.
确认偏误。找证据来支持我们已经相信的事。
Now, we're probably all a little bit guilty of that at times.
我们可能难免有时都会有一点确认偏误。
Take a look at this. I'm on Twitter. And often, when it snows, I'll get this tweet back to me.
看看这个。我在推特上。通常，下雪时，我会收到这样的回复。
"Hey, Dr. Shepherd, I have 20 inches of global warming in my yard, what are you guys talking about, climate change?"
“嘿，谢博德博士，我的院子里有二十英寸的全球变暖，你们在说的是什么？气候变迁？”
I get that tweet a lot, actually. It's a cute tweet, it makes me chuckle as well.
其实，我常收到这种推特信息。这种信息很可爱，会让我咯咯笑。
But it's oh, so fundamentally scientifically flawed.
但，它在根本上，有很大的科学瑕疵。
Because it illustrates that the person tweeting doesn't understand the difference between weather and climate.
因为它说明了写这则推特信息的人并不了解天气和气候之间的差别。
I often say, weather is your mood and climate is your personality.
我常说，天气是你的心情，气候是你的个性。
Think about that. Weather is your mood, climate is your personality.
想想看。天气是你的心情，气候是你的个性。
Your mood today doesn't necessarily tell me anything about your personality,
你今天的心情不见得能代表你的个性，
nor does a cold day tell me anything about climate change, or a hot day, for that matter.
有一天很冷，并不表示就有气候变迁，有一天很热也是一样的。
Dunning-Kruger. Two scholars from Cornell came up with the Dunning-Kruger effect.
达克效应。康乃尔大学的两位学者提出了达克效应。
If you go look up the peer-reviewed paper for this, you will see all kinds of fancy terminology:
若你去找相关的同侪审查论文，你会看到各式各样很炫的专有名词：
it's an illusory superiority complex, thinking we know things.
它是一种虚幻的优越情节，认为我们什么都知道。
In other words, people think they know more than they do. Or they underestimate what they don't know.
换言之，“认为自己知道的”比“真正知道的”多。或是说低估了自己不知道的。
And then, there's cognitive dissonance. Cognitive dissonance is interesting.
接着，还有认知失调。认知失调很有趣。
We just recently had Groundhog Day, right?
我们才刚过了土拨鼠节，对吧？
Now, there's no better definition of cognitive dissonance than intelligent people asking me if a rodent's forecast is accurate.
认知失调最好的定义就是有智慧的人问我啮齿目动物的预测是否正确。
But I get that, all of the time.
但常常会有人问我这个问题。
But I also hear about the Farmer's Almanac.
但我也听过农民年鉴。
We grew up on the Farmer's Almanac, people are familiar with it.
我们是看农民年鉴长大的，大家很熟悉它。
The problem is, it's only about 37 percent accurate, according to studies at Penn State University.
问题是，它只有37%的正确率，这是宾夕法尼亚州立大学研究出来的数据。
But we're in an era of science where we actually can forecast the weather.
但我们所处的科学时代，是可以正确预测天气的。
And believe it or not, and I know some of you are like, "Yeah, right,"
信不信由你，我知道有人在想“最好是啦”，
we're about 90 percent accurate, or more, with weather forecast.
在天气预测上，我们可以达到90%以上的正确率。
You just tend to remember the occasional miss, you do.
你们只是倾向会记得偶尔才发生的错误预测，真的。
So confirmation bias, Dunning-Kruger and cognitive dissonance.
所以，确认偏误、达克效应和认知失调。
I think those shape biases and perceptions that people have about science.
我认为这些元素造成了对于科学的偏见和认知。
But then, there's literacy and misinformation that keep us boxed in, as well.
但还有识字能力和错误信息，会让我们的所知受限。
During the hurricane season of 2017,
在2017年的飓风季，
media outlets had to actually assign reporters to dismiss fake information about the weather forecast.
媒体管道真的有指派记者去排除关于天气预测的假信息。

That's the era that we're in. I deal with this all the time in social media.
那就是我们所处的时代。我总是要在社交媒体上处理这种事。
Someone will tweet a forecast -- that's a forecast for Hurricane Irma,
有人会在推特上发布预测--那是飓风埃玛的预测，
but here's the problem: it didn't come from the Hurricane Center.
但有个问题：这个预测并非来自国家飓风中心。
But people were tweeting and sharing this; it went viral.
但大家就不断转推和分享这个预测；它被疯传。
It didn't come from the National Hurricane Center at all.
它完全不是来自国家飓风中心的。
So I spent 12 years of my career at NASA before coming to the University of Georgia,
我的职业生涯中，有十二年是在美国国家航空航天局，后来才到乔治亚大学，
and I chair their Earth Science Advisory Committee, I was just up there last week in DC.
我在他们的地球科学咨询委员会当主席，我上周才到华盛顿特区。
And I saw some really interesting things.
我看到了一些很有趣的事。
Here's a NASA model and science data from satellite showing the 2017 hurricane season.
这是美国国家航空航天局的模型，以及来自卫星的数据，呈现出来的是2017年的飓风季。
You see Hurricane Harvey there? Look at all the dust coming off of Africa.
有看到那里的飓风哈维吗？看看所有从非洲来的尘土。
Look at the wildfires up in northwest US and in western Canada.
看看美国西北部和加拿大西部的野火。
There comes Hurricane Irma. This is fascinating to me. But admittedly, I'm a weather geek.
飓风埃玛来了。这对我来说很迷人。但必须要承认，我是个天气怪咖。
But more importantly, it illustrates that we have the technology to not only observe the weather and climate system, but predict it.
但更重要的是，它说明了我们不仅有可以观察天气和气候系统的科技，也能做预测。
There's scientific understanding,
这里有科学上的了解，
so there's no need for some of those perceptions and biases that we've been talking about. We have knowledge.
所以就不需要我们先前谈的那些认知和偏见。我们有知识。
But think about this ... This is Houston, Texas, after Hurricane Harvey.
但，想想看...这是飓风哈维过后的德州休斯敦。
Now, I write a contribution for "Forbes" magazine periodically,
我定期会为《富比士》杂志写稿，
and I wrote an article a week before Hurricane Harvey made landfall,
在飓风哈维登陆前一周，我写了一篇文章，
saying, "There's probably going to be 40 to 50 inches of rainfall."
说：“可能会有四十到五十英寸的降雨。”
I wrote that a week before it happened. But yet, when you talk to people in Houston,
这是在发生前一周写的。 但当你和休斯敦的人谈话时，
people are saying, "We had no idea it was going to be this bad." I'm just...
他们会说：“我们完全不知道这次会这么糟。”我只是...
A week before. But -- I know, it's amusing, but the reality is,
一周前。但...我知道，这很有趣，但现实是，
we all struggle with perceiving something outside of our experience level.
我们都很难认知在我们经验层级以外的东西。
People in Houston get rain all of the time, they flood all of the time.
休斯敦的人常常遇到下雨，常常有水灾。
But they've never experienced that.
但他们从来没有经验过那种灾难。
Houston gets about 34 inches of rainfall for the entire year.
休斯敦整年的降雨量大约是三十四英寸。
They got 50 inches in three days. That's an anomaly event, that's outside of the normal.
三天内，降雨共五十英寸。那是件异常事件，并非正常的。
So belief systems and biases, literacy and misinformation.
所以，信念系统和偏见，识字能力和错误信息。
How do we step out of the boxes that are cornering our perceptions?
要如何爬出限制我们认知的井底？
Well we don't even have to go to Houston, we can come very close to home.
我们甚至不用到休斯敦，我们可以到离家很近的地方。
Remember "Snowpocalypse?" Snowmageddon? Snowzilla? Whatever you want to call it. All two inches of it.
记得“雪界末日吗”？末日暴雪？雪吉拉？不论你怎么称呼它。积雪总共有两英寸。
Two inches of snow shut the city of Atlanta down.
两英寸的积雪，让亚特兰大市关闭。
But the reality is, we were in a winter storm watch, we went to a winter weather advisory,
但现实是当时我们正处于冬季风暴中，我们发布寒冬天气预报，
and a lot of people perceived that as being a downgrade, "Oh, it's not going to be as bad."
很多人认为说得太严重了：“喔，不会那么糟的。”
When in fact, the perception was that it was not going to be as bad, but it was actually an upgrade.
当他们的认知是“不会那么糟”，事实却是状况更新成“更为严峻”。
Things were getting worse as the models were coming in.
随着新到的模型，一切都在恶化。
So that's an example of how we get boxed in by our perceptions.
那就是我们被认知困在井底的一个例子。
So, the question becomes, how do we expand our radius? The area of a circle is "pi r squared".
所以，问题变成了：我们要如何扩展我们的半径？圆的面积是“πr平方”。
We increase the radius, we increase the area.
我们若能增加半径，就能增加面积。
How do we expand our radius of understanding about science? Here are my thoughts.
我们要如何扩展我们在了解科学方面的半径？以下是我的想法。
You take inventory of your own biases. And I'm challenging you all to do that.
你把你自己的偏见盘点一下。我挑战各位去做这件事。
Take an inventory of your own biases. Where do they come from?
把你自己的偏见盘点一下。它们是从哪里来的？
Your upbringing, your political perspective, your faith -- what shapes your own biases?
你的养育过程、你的政治观点、你的信仰--你自己的偏见是由什么形成的？
Then, evaluate your sources -- where do you get your information on science?
接着，评估你的信息来源--你从哪里取得那些关于科学的信息？
What do you read, what do you listen to, to consume your information on science?
你会读什么、你会听什么，来取得关于科学的信息？
And then, it's important to speak out. Talk about how you evaluated your biases and evaluated your sources.
接着，很重要的是要说出来。谈谈你如何评估你的偏见以及你的来源。
I want you to listen to this little 40-second clip
我想请各位听听这一小段影片，只有四十秒，
from one of the top TV meteorologists in the US, Greg Fishel, in the Raleigh, Durham area.
是关于美国最顶尖的电视气象学家之一，北卡罗莱纳州罗利达拉姆三角区的格雷格·费雪尔。
He's revered in that region. But he was a climate skeptic.
他在那个地区倍受推崇。但他是个气候怀疑论者。
But listen to what he says about speaking out.
但听听他对于“说出来”怎么说。
The mistake I was making and didn't realize until very recently,
我所犯下的错误，并且一直到最近才发现，
was that I was only looking for information to support what I already thought,
就是我只有针对我既有的想法来寻找支持的信息，
and was not interested in listening to anything contrary.
并且我没兴趣倾听任何相反信息。
And so I woke up one morning, and there was this question in my mind,
所以，有天早上我醒来时，脑中有一个问题：
"Greg, are you engaging in confirmation bias? Are you only looking for information to support what you already think?"
“格雷格，你是否有确认偏误？你是否只在寻找支持你想法的信息？”
And if I was honest with myself, and I tried to be, I admitted that was going on.
若我对自己很诚实，并且我有试着这么做，我会承认我的确有这个状况。
And so the more I talked to scientists and read peer-reviewed literature
所以，我和越多科学家谈话，阅读越多同侪审查论文，
and tried to conduct myself the way I'd been taught to conduct myself at Penn State when I was a student,
并照我学生时期在宾夕法尼亚州立大学被教导的方式来做人做事，
it became very difficult for me to make the argument that we weren't at least having some effect.
我就越难主张说我们没有受到丝毫影响。
Maybe there was still a doubt as to how much,
也许还无法确定影响有多少，
but to say "nothing" was not a responsible thing for me to do as a scientist or a person.
但对我来说，说“没有”是很不负责的，不论以一个科学家或一个人的身分都一样。
Greg Fishel just talked about expanding his radius of understanding of science.
格雷格·费雪尔在说的，就是扩展他了解科学的半径。
And when we expand our radius, it's not about making a better future, but it's about preserving life as we know it.
当我们能扩展我们的半径时，重点并不在于让未来更好，而在于保存生命现有的状态。
So as we think about expanding our own radius in understanding science,
所以，当我们想着要扩展我们了解科学的半径时，
it's critical for Athens, Georgia, for Atlanta, Georgia, for the state of Georgia, and for the world.
这对于乔治亚州的雅典、乔治亚州的亚特兰大、整个乔治亚州及全世界都很重要。
So expand your radius. Thank you.
所以，扩展你们的半径吧。谢谢。