I'm a meteorologist by degree, I have a bachelor's, master's and PhD in physical meteorology, so I'm a meteorologist, card carrying. And so with that comes four questions, always. This is one prediction I will always get right.
從學位上來看,我是氣象學家, 我有物理氣象學的 學士、碩士、博士學位, 所以我是氣象學家,有認證的。 這總是會伴隨著四個問題。 我的這項預測是最準的。
(Laughter)
(笑聲)
And those questions are, "Marshall, what channel are you on?"
那幾個問題是: 「馬歇爾,你在哪一台播氣象?」
(Laughter)
(笑聲)
"Dr. Shepherd, what's the weather going to be tomorrow?"
「薛佛博士,明天的天氣如何?」
(Laughter)
(笑聲)
And oh, I love this one: "My daughter is getting married next September, it's an outdoor wedding. Is it going to rain?"
喔,我很愛這一個: 「我女兒明年九月要結婚, 是戶外婚禮。到時會下雨嗎?」
(Laughter)
(笑聲)
Not kidding, I get those, and I don't know the answer to that, the science isn't there. But the one I get a lot these days is, "Dr. Shepherd, do you believe in climate change?" "Do you believe in global warming?" Now, I have to gather myself every time I get that question. Because it's an ill-posed question -- science isn't a belief system. My son, he's 10 -- he believes in the tooth fairy. And he needs to get over that, because I'm losing dollars, fast.
不是開玩笑的,我會被問 這些問題,但我沒有答案, 那沒有科學。 但最近我最常被問的是這個: 「薛佛博士,你相信 氣候變遷嗎?」 「你相信全球暖化嗎?」 每當我被問那個問題時, 我就得打起精神。 因為這是個不適定的問題—— 科學並不是個信念系統。 我的兒子十歲——他相信 有牙仙(會把牙齒換成金幣)。 他最好快點度過這段時期, 因為我虧錢虧得很快。
(Laughter)
(笑聲)
But he believes in the tooth fairy. But consider this. Bank of America building, there, in Atlanta. 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?" You never hear that, because gravity is a thing. So why don't we hear the question, "Do you believe in gravity?" But of course, we hear the question, "Do you believe in global warming?"
但他相信有牙仙。 但,想想這一點。 美國銀行大樓,位在亞特蘭大。 你從來不會聽到有人說: 「你信不信,如果到 那棟大樓的樓頂, 把一顆球丟出去, 它就會向下落?」 你從來沒有聽過, 因為重力是客觀存在。 所以我們不會聽到這個問題: 「你相信重力嗎?」 但,當然,我們會聽到這個問題: 「你相信全球暖化嗎?」
Well, consider these facts. The American Association for the Advancement of Science, AAAS, one of the leading organizations in science, queried scientists and the public on different science topics. Here are some of them: genetically modified food, animal research, human evolution. And look at what the scientists say about those, the people that actually study those topics, in red, versus the gray, what the public thinks. How did we get there? How did we get there? That scientists and the public are so far apart on these science issues.
想想看這些事實。 美國科學促進會, 縮寫 AAAS, 是科學界最重要的組織之一, 詢問科學家和大眾 各種不同的科學主題。 以下是其中一些:基因改造食物、 動物研究、人類演化。 看看科學家們對這些主題的說法, 真正在研究那些 主題的人是紅色的, 相對的,灰色是大眾的想法。 我們是怎麼走到這一步的? 我們是怎麼走到這一步的? 在這些科學議題上, 科學家和大眾的認知差好多。
Well, I'll come a little bit closer to home for me, climate change. Eighty-seven percent of scientists believe that humans are contributing to climate change. But only 50 percent of the public? How did we get there? So it begs the question, what shapes perceptions about science? It's an interesting question and one that I've been thinking about quite a bit. I think that one thing that shapes perceptions in the public, about science, is belief systems and biases. Belief systems and biases. Go with me for a moment. Because I want to talk about three elements of that: confirmation bias, Dunning-Kruger effect and cognitive dissonance. Now, these sound like big, fancy, academic terms, and they are. But when I describe them, you're going to be like, "Oh! I recognize that; I even know somebody that does that."
我挑個我比較熟悉的主題來談: 氣候變遷。 87% 的科學家 相信人類造成了氣候變遷。 但只有 50% 的民眾這麼想? 我們是怎麼走到這一步的? 這就帶出了一個問題: 關於科學的認知,是怎麼來的? 這是個很有意思的問題, 我花了不少時間在思考它。 我認為,大眾對於科學的認知, 是由信念系統和偏見所形塑的。 信念系統和偏見。 耐心聽我說一下。 因為我想要談它的三項元素: 確認偏誤、 達克效應, 以及認知失調。 這些聽起來是很博大、 很炫的學術名詞,的確是的。 但當我描述它們時, 你們會說類似:「喔! 我知道,我甚至認識 有這種狀況的人。」
Confirmation bias. Finding evidence that supports what we already believe. Now, we're probably all a little bit guilty of that at times. Take a look at this. I'm on Twitter. And often, when it snows, I'll get this tweet back to me.
確認偏誤。 找證據來支持我們已經相信的事。 我們可能難免有時 都會有一點確認偏誤。 看看這個。 我在推特上。 通常,下雪時, 我會收到這樣的回覆。
(Laughter)
(笑聲)
"Hey, Dr. Shepherd, I have 20 inches of global warming in my yard, what are you guys talking about, climate change?" I get that tweet a lot, actually. It's a cute tweet, it makes me chuckle as well. But it's oh, so fundamentally scientifically flawed. Because it illustrates that the person tweeting doesn't understand the difference between weather and climate. I often say, weather is your mood and climate is your personality. Think about that. Weather is your mood, climate is your personality. Your mood today doesn't necessarily tell me anything about your personality, nor does a cold day tell me anything about climate change, or a hot day, for that matter.
「嘿,薛佛博士,我的院子裡 有二十英吋的全球暖化, 你們在說的是什麼?氣候變遷?」 其實,我常收到這種推特訊息。 這種訊息很可愛,會讓我咯咯笑。 但,它在根本上, 有很大的科學瑕疵。 因為它說明了寫這則 推特訊息的人並不了解 天氣和氣候之間的差別。 我常說,天氣是你的心情, 氣候是你的個性。 想想看。天氣是你的心情, 氣候是你的個性。 你今天的心情不見得 能代表你的個性, 有一天很冷,並不表示 就有氣候變遷, 有一天很熱也是一樣的。
Dunning-Kruger. Two scholars from Cornell came up with the Dunning-Kruger effect. If you go look up the peer-reviewed paper for this, you will see all kinds of fancy terminology: it's an illusory superiority complex, thinking we know things. In other words, people think they know more than they do. Or they underestimate what they don't know.
達克效應。 康乃爾大學的兩位學者 提出了達克效應。 若你去找相關的同儕審查論文, 你會看到各式各樣 很炫的專有名詞: 它是一種虛幻的優越情節, 認為我們什麼都知道。 換言之,「認為自己知道的」 比「真正知道的」多。 或是說低估了自己不知道的。
And then, there's cognitive dissonance. Cognitive dissonance is interesting. We just recently had Groundhog Day, right? Now, there's no better definition of cognitive dissonance than intelligent people asking me if a rodent's forecast is accurate.
接著,還有認知失調。 認知失調很有趣。 我們才剛過了土撥鼠節,對吧? 認知失調最好的定義就是 有智慧的人問我齧齒目 動物的預測是否正確。
(Laughter)
(笑聲)
But I get that, all of the time.
但常常會有人問我這個問題。
(Laughter)
(笑聲)
But I also hear about the Farmer's Almanac. We grew up on the Farmer's Almanac, people are familiar with it. The problem is, it's only about 37 percent accurate, according to studies at Penn State University. But we're in an era of science where we actually can forecast the weather. And believe it or not, and I know some of you are like, "Yeah, right," we're about 90 percent accurate, or more, with weather forecast. You just tend to remember the occasional miss, you do.
但我也聽過農民曆。 我們是看農民曆長大的, 大家很熟悉它。 問題是, 它只有 37% 的正確率, 這是賓夕法尼亞州立大學 研究出來的數據。 但我們所處的科學時代, 是可以正確預測天氣的。 信不信由你,我知道 有人在想「最好是啦」。 在天氣預測上,我們可以 達到 90% 以上的正確率。 你們只是傾向會記得偶爾 才發生的錯誤預測,真的。
(Laughter)
(笑聲)
So confirmation bias, Dunning-Kruger and cognitive dissonance. I think those shape biases and perceptions that people have about science. But then, there's literacy and misinformation that keep us boxed in, as well. During the hurricane season of 2017, media outlets had to actually assign reporters to dismiss fake information about the weather forecast. That's the era that we're in. I deal with this all the time in social media. Someone will tweet a forecast -- that's a forecast for Hurricane Irma, but here's the problem: it didn't come from the Hurricane Center. But people were tweeting and sharing this; it went viral. It didn't come from the National Hurricane Center at all.
所以,確認偏誤、 達克效應,和認知失調。 我認為這些元素造成了 對於科學的偏見和認知。 但,還有識字能力和錯誤訊息, 會讓我們的所知受限。 在 2017 年的颶風季, 媒體管道真的有指派記者 去排除關於天氣預測的假資訊。 那就是我們所處的時代。 我總是要在社交媒體上 處理這種事。 有人會在推特上發佈預測—— 那是颶風艾瑪的預測, 但有個問題:這個預測 並非來自國家颶風中心。 但大家就不斷轉推和分享 這個預測;它被瘋傳。 它完全不是來自國家颶風中心的。
So I spent 12 years of my career at NASA before coming to the University of Georgia, and I chair their Earth Science Advisory Committee, I was just up there last week in DC. And I saw some really interesting things. Here's a NASA model and science data from satellite showing the 2017 hurricane season. You see Hurricane Harvey there? Look at all the dust coming off of Africa. Look at the wildfires up in northwest US and in western Canada. There comes Hurricane Irma. This is fascinating to me. But admittedly, I'm a weather geek. But more importantly, it illustrates that we have the technology to not only observe the weather and climate system, but predict it. There's scientific understanding, so there's no need for some of those perceptions and biases that we've been talking about. We have knowledge.
我的職涯中,有十二年 是在太空總署, 後來才到喬治亞大學, 我在他們的地球科學 諮詢委員會當主席, 我上週才到華盛頓特區。 我看到了一些很有趣的事。 這是太空總署的模型, 以及來自衛星的資料, 呈現出來的 是 2017 年的颶風季。 有看到那裡的颶風哈維嗎? 看看所有從非洲來的塵土。 看看美國西北部 和加拿大西部的野火。 颶風艾瑪來了。 這對我來說很迷人。 但,必須要承認, 我是個天氣怪咖。 但,更重要的是, 它說明了我們不僅有 可以觀察天氣和氣候系統的 科技,也能做預測。 這裡有科學上的了解, 所以就不需要我們先前談的 那些認知和偏見。 我們有知識。但,想想看……
But think about this ... This is Houston, Texas, after Hurricane Harvey. Now, I write a contribution for "Forbes" magazine periodically, and I wrote an article a week before Hurricane Harvey made landfall, saying, "There's probably going to be 40 to 50 inches of rainfall." I wrote that a week before it happened. But yet, when you talk to people in Houston, people are saying, "We had no idea it was going to be this bad." I'm just...
這是颶風哈維過後的德州休士頓。 我定期會為《富比士》雜誌寫稿, 在颶風哈維登陸前一週, 我寫了一篇文章,說: 「可能會有四十 到五十英吋的降雨。」 這是在發生前一週寫的。 但,當你和休士頓的人談話時, 他們會說:「我們完全 不知道這次會這麼糟。」 我只是……
(Sigh)
(嘆氣)
(Laughter)
(笑聲)
A week before. But -- I know, it's amusing, but the reality is, we all struggle with perceiving something outside of our experience level. People in Houston get rain all of the time, they flood all of the time. But they've never experienced that. Houston gets about 34 inches of rainfall for the entire year. They got 50 inches in three days. That's an anomaly event, that's outside of the normal.
一週前。 但—— 我知道,這很有趣,但現實是, 我們都很難認知 在我們經驗層級以外的東西。 休士頓的人常常遇到下雨, 常常有水災。 但他們從來沒有經驗過那種災難。 休士頓整年的降雨量 大約是三十四英吋。 三天內,降雨共五十英吋。 那是件異常事件,並非正常的。
So belief systems and biases, literacy and misinformation. How do we step out of the boxes that are cornering our perceptions? Well we don't even have to go to Houston, we can come very close to home.
所以,信念系統和偏見, 識字能力和錯誤資訊。 要如何爬出限制我們認知的井底? 我們甚至不用到休士頓, 我們可以到離家很近的地方。
(Laughter)
(笑聲)
Remember "Snowpocalypse?"
記得「雪界末日 (改自世界末日)嗎」?
(Laughter)
(笑聲)
Snowmageddon? Snowzilla? Whatever you want to call it. All two inches of it.
末日暴雪(改自末日大戰)? 雪吉拉(改自哥吉拉)? 不論你怎麼稱呼它。 積雪總共有兩英吋。
(Laughter)
(笑聲)
Two inches of snow shut the city of Atlanta down.
兩英吋的積雪, 讓亞特蘭大市關閉。
(Laughter)
(笑聲)
But the reality is, we were in a winter storm watch, we went to a winter weather advisory, and a lot of people perceived that as being a downgrade, "Oh, it's not going to be as bad." When in fact, the perception was that it was not going to be as bad, but it was actually an upgrade. Things were getting worse as the models were coming in. So that's an example of how we get boxed in by our perceptions.
但現實是當時我們 正處於冬季風暴中。 我們發布寒冬天氣預報。 很多人認為說得太嚴重了: 「喔,不會那麼糟的。」 當他們的認知是「不會那麼糟」, 事實卻是狀況更新成「更為嚴峻」。 隨著新到的模型,一切都在惡化。 那就是我們被認知 困在井底的一個例子。
So, the question becomes, how do we expand our radius? The area of a circle is "pi r squared". We increase the radius, we increase the area. How do we expand our radius of understanding about science? Here are my thoughts. You take inventory of your own biases. And I'm challenging you all to do that. Take an inventory of your own biases. Where do they come from? Your upbringing, your political perspective, your faith -- what shapes your own biases? Then, evaluate your sources -- where do you get your information on science? What do you read, what do you listen to, to consume your information on science? And then, it's important to speak out. Talk about how you evaluated your biases and evaluated your sources. I want you to listen to this little 40-second clip from one of the top TV meteorologists in the US, Greg Fishel, in the Raleigh, Durham area. He's revered in that region. But he was a climate skeptic. But listen to what he says about speaking out.
所以,問題變成了: 我們要如何擴展我們的半徑? 圓的面積是「π r 平方」。 我們若能增加半徑, 就能增加面積。 我們要如何擴展我們 在了解科學方面的半徑? 以下是我的想法。 你把你自己的偏見盤點一下。 我挑戰各位去做這件事。 把你自己的偏見盤點一下。 它們是從哪裡來的? 你的養育過程、 你的政治觀點、你的信仰—— 你自己的偏見是由什麼形成的? 接著,評估你的資訊來源—— 你從哪裡取得 那些關於科學的資訊? 你會讀什麼、你會聽什麼, 來取得關於科學的資訊? 接著,很重要的是要說出來。 談談你如何評估 你的偏見以及你的來源。 我想請各位聽聽 這一小段影片,只有四十秒, 美國最頂尖的電視氣象學家之一, 北卡羅萊納州,羅利達拉姆 三角區的格雷格費雪爾。 他在那個地區倍受推崇。 但他是個氣候懷疑論者。 但聽聽他對於「說出來」怎麼說。
Greg Fishel: The mistake I was making and didn't realize until very recently, was that I was only looking for information to support what I already thought, and was not interested in listening to anything contrary. And so I woke up one morning, and there was this question in my mind, "Greg, are you engaging in confirmation bias? Are you only looking for information to support what you already think?" And if I was honest with myself, and I tried to be, I admitted that was going on. And so the more I talked to scientists and read peer-reviewed literature and tried to conduct myself the way I'd been taught to conduct myself at Penn State when I was a student, it became very difficult for me to make the argument that we weren't at least having some effect. Maybe there was still a doubt as to how much, but to say "nothing" was not a responsible thing for me to do as a scientist or a person.
格雷格費雪爾:我所犯下的錯誤, 且一直到最近才發現, 就是我只有針對我既有的想法 來尋找支持的資訊, 且我沒興趣傾聽任何相反資訊。 所以,有天早上我醒來時, 腦中有一個問題: 「格雷格,你是否有確認偏誤? 你是否只在尋找 支持你想法的資訊?」 若我對自己很誠實, 且我有試著這麼做, 我會承認我的確有這個狀況。 所以,我和越多科學家談話, 閱讀越多同儕審查論文, 並照我學生時期 在賓夕法尼亞州立大學 被教導的方式來做人做事, 我就越難主張說 我們沒有受到絲毫影響。 也許還無法確定影響有多少, 但對我來說,說「沒有」 是很不負責的, 不論以一個科學家 或一個人的身分都一樣。
JMS: Greg Fishel just talked about expanding his radius of understanding of science. And when we expand our radius, it's not about making a better future, but it's about preserving life as we know it.
講者:格雷格費雪爾在說的, 就是擴展他了解科學的半徑。 當我們能擴展我們的半徑時, 重點並不在於讓未來更好, 而在於保存生命現有的狀態。
So as we think about expanding our own radius in understanding science, it's critical for Athens, Georgia, for Atlanta, Georgia, for the state of Georgia, and for the world. So expand your radius.
所以,當我們想著要擴展 我們了解科學的半徑時, 這對於喬治亞州的雅典、 喬治亞州的亞特蘭大、 整個喬治亞州,及全世界,都很重要。 所以,擴展你們的半徑吧。
Thank you.
謝謝。
(Applause)
(掌聲)