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Home » Failing Upwards: Science Learns by Making Mistakes by Phil Plait (Transcript)

Failing Upwards: Science Learns by Making Mistakes by Phil Plait (Transcript)

Phil Plait

Phil Plait is an astronomer and science communicator. He is the author of three books, as well as the blog “Bad Astronomy” where he evangelizes science with joy and passion.

Here is the full text of Phil’s talk titled “Failing Upwards: Science Learns by Making Mistakes” at TEDxBoulder conference.


Have you ever made a really dumb mistake?

Now I don’t mean like going to the store and coming home and then realizing you forgot to buy something. I mean something big, something consequential, something that affected other people, something that was embarrassing.

Well did you admit it? And did you apologize? And most importantly, did you change your way of thinking so you wouldn’t make that same mistake again?

Well I have a secret for you that really shouldn’t be a secret. Science does this all the time. It is the very essence of science.

Now, people have a lot of misconceptions about science — about how it works and what it is. A big one is that science is just a big old pile of facts. But that’s not true — that’s not even the goal of science.

Science is a process. It’s a way of thinking. Gathering facts is just a piece of it, but it’s not the goal. The ultimate goal of science is to understand objective reality the best way we know how, and that’s based on evidence.

The problem here is that people are flawed. We can be fooled — we’re really good at fooling ourselves. And so baked into this process is a way of minimizing our own bias. So sort of boiled down more than is probably useful, here’s how this works.

If you want to do some science, what you want to do is you want to observe something … say, “The sky is blue. Hey, I wonder why?” You question it.

The next thing you do is you come up with an idea that may explain it: a hypothesis. Well, you know what? Oceans are blue. Maybe the sky is reflecting the colors from the ocean. Great, but now you have to test it so you predict what that might mean.

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Your prediction would be, “Well, if the sky is reflecting the ocean color, it will be bluer on the coasts than it will be in the middle of the country.” OK, that’s fair enough, but you’ve got to test that prediction so you get on a plane, you leave Denver on a nice gray day, you fly to LA, you look up and the sky is gloriously blue. Hooray, your thesis is proven.

But is it really? No. You’ve made one observation. You need to think about your hypothesis, think about how to test it and do more than just one. Maybe you could go to a different part of the country or a different part of the year and see what the weather’s like then.

Another good idea is to talk to other people. They have different ideas, different perspectives, and they can help you. This is what we call peer review. And in fact, that will probably also save you a lot of money and a lot of time, flying coast-to-coast just to check the weather.

Now, what happens if your hypothesis does a decent job but not a perfect job? Well, that’s OK, because what you can do is you can modify it a little bit and then go through this whole process again — make predictions, test them and do that — and as you do that over and over again, you will hone this idea. And if it gets good enough, it may be accepted by the scientific community, at least provisionally, as a good explanation of what’s going on, at least until a better idea or some contradictory evidence comes along.

Now, part of this process is admitting when you’re wrong. And that can be really, really hard.

Science has its strengths and weaknesses and they depend on this. One of the strengths of science is that it’s done by people, and it’s proven itself to do a really good job. We understand the universe pretty well because of science.

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One of science’s weaknesses is that it’s done by people, and we bring a lot of baggage along with us when we investigate things. We are egotistical, we are stubborn, we’re superstitious, we’re tribal, we’re humans — these are all human traits and scientists are humans. And so we have to be aware of that when we’re studying science and when we’re trying to develop our theses.

But part of this whole thing, part of this scientific process, part of the scientific method, is admitting when you’re wrong. And the thing is scientists are human; we have all those same traits as every other human. And when you have a cool idea, giving it up is really, really hard. I know, I’ve been there.

Many years ago, I was working on Hubble Space Telescope, and a scientist I worked with came to me with some data, and he said, “I think there may be a picture of a planet orbiting another star in this data.” We had not had any pictures taken of planets orbiting other stars yet, so if this were true, then this would be the first one and we would be the ones who found it. That’s a big deal.

I was very excited, so I just dug right into this data. I spent a long time trying to figure out if this thing were a planet or not. The problem is planets are faint and stars are bright, so trying to get the signal out of this data was like trying to hear a whisper in a heavy metal concert — it was really hard. I tried everything I could, but after a month of working on this, I came to a realization … couldn’t do it. I had to give up.

And I had to tell this other scientist, “The data’s too messy. We can’t say whether this is a planet or not.” And that was hard.

Then later on we got follow-up observations with Hubble, and it showed that it wasn’t a planet. It was a background star or galaxy, something like that.

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