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Let's just say a combination of a few essentially computational factors--memory, conscientiousness, and scholarship and/or expertise through experience over a s

Let's just say a combination of a few essentially computational factors--memory, conscientiousness, and scholarship and/or expertise through experience over a significant period of time in varied contexts. But really it's just my intuition, and I'm not the most intelligent person in the world so maybe I'm wrong. I don't really mean intelligence in the technical or usual sense, just in the sense that it applies to a climatologist that makes good predictions in this context. Anyways, I'm just here to deliver the message, I don't really pretend to know either way--but I do tend to agree with certain experts over others because their arguments are much more robust, given my math background it appeals to my reasonable side. edit: I thought about it some more. I think I can boil it down to one thing--high information entropy in their written work.

onion2k 6y ago
But really it's just my intuition So you're really just using "intelligent" as a proxy for "says things I agree with", with no real basis for the claim. That's not a good look.
- solinent 6y ago
  Yes, it's my opinion, and I've presented it as such, but it's entirely based on his point of view. I think the opinions of non-experts are very valuable due to the effects of group-think. The basis for my claim I could lay down, but this is not the ground for that battle. Do you have any reason to disbelieve certain experts over others? When they are the foremost in their field, consistently? No one is denying climate change. In any case, I don't claim its truth, just its existence. It's obviously important to any scientific process to consider alternative theories which have better predictive power, and to criticize our existing ones, however close to reality they ultimately are. In any case, if reasonable discussion is not permitted here maybe it's not the place for me. edit: > That's not a good look. Maybe I'm just in the wrong neighborhood. Okay maybe I'll stay, seems like there's a mixed response.
  - roelschroeven 6y ago
    > Do you have any reason to disbelieve certain experts over others? What is important, I think, is that we shouldn't believe anyone just because they're an expert. What we believe or not should not be based on who says it, but ultimately on the data that supports it (or not). So find the studies that (are supposed to) support a given opinion, have a look them, and have a look at how other studies in the field react to it. That last point is very important: it often reveals flaws in the study that a layman could never spot. > In any case, I don't claim its truth, just its existence. It's obviously important to any scientific process to consider alternative theories which have better predictive power, and to criticize our existing ones, however close to reality they ultimately are. If you go look at the climate science literature, you'll find that all different kinds of models and explanations have been proposed and studied. Those alternatives have been looked at in detail by people in the field, just like any other study. None of them have been found to better match the data.
    - solinent 6y ago
      >If you go look at the climate science literature, you'll find that all different kinds of models and explanations have been proposed and studied. Those alternatives have been looked at in detail by people in the field, just like any other study. None of them have been found to better match the data. Because the system is chaotic and we can't predict it beyond a week. Maybe a day at best. Once you can predict hurricanes, volcanoes, and tropical storms, then let me know. You can over-fit any data. I guess ML still has to learn this basic concept from statistics 101. Anyways, I appreciate the discussion, thank you. I'm a bit irate this week. You can harness chaos in space because things are really far apart. It doesn't work on Earth, or our stock market would be linear.
      - solinent 6y ago
        To summarize. The existing models just scratch the surface.
      - onion2k 6y ago
        Because the system is chaotic and we can't predict it beyond a week. Maybe a day at best. Once you can predict hurricanes, volcanoes, and tropical storms, then let me know. You're confusing weather and climate. We can't model the weather very well. It's hard. We can model the climate reasonably well (our models fit historical data really well), but the models turn out to be bad at predicting the future because we underestimate how much of an impact we're having (the article is a good example).

onion2k 6y ago

But really it's just my intuition So you're really just using "intelligent" as a proxy for "says things I agree with", with no real basis for the claim. That's not a good look.

solinent 6y ago
Yes, it's my opinion, and I've presented it as such, but it's entirely based on his point of view. I think the opinions of non-experts are very valuable due to the effects of group-think. The basis for my claim I could lay down, but this is not the ground for that battle. Do you have any reason to disbelieve certain experts over others? When they are the foremost in their field, consistently? No one is denying climate change. In any case, I don't claim its truth, just its existence. It's obviously important to any scientific process to consider alternative theories which have better predictive power, and to criticize our existing ones, however close to reality they ultimately are. In any case, if reasonable discussion is not permitted here maybe it's not the place for me. edit: > That's not a good look. Maybe I'm just in the wrong neighborhood. Okay maybe I'll stay, seems like there's a mixed response.
- roelschroeven 6y ago
  > Do you have any reason to disbelieve certain experts over others? What is important, I think, is that we shouldn't believe anyone just because they're an expert. What we believe or not should not be based on who says it, but ultimately on the data that supports it (or not). So find the studies that (are supposed to) support a given opinion, have a look them, and have a look at how other studies in the field react to it. That last point is very important: it often reveals flaws in the study that a layman could never spot. > In any case, I don't claim its truth, just its existence. It's obviously important to any scientific process to consider alternative theories which have better predictive power, and to criticize our existing ones, however close to reality they ultimately are. If you go look at the climate science literature, you'll find that all different kinds of models and explanations have been proposed and studied. Those alternatives have been looked at in detail by people in the field, just like any other study. None of them have been found to better match the data.
  - solinent 6y ago
    >If you go look at the climate science literature, you'll find that all different kinds of models and explanations have been proposed and studied. Those alternatives have been looked at in detail by people in the field, just like any other study. None of them have been found to better match the data. Because the system is chaotic and we can't predict it beyond a week. Maybe a day at best. Once you can predict hurricanes, volcanoes, and tropical storms, then let me know. You can over-fit any data. I guess ML still has to learn this basic concept from statistics 101. Anyways, I appreciate the discussion, thank you. I'm a bit irate this week. You can harness chaos in space because things are really far apart. It doesn't work on Earth, or our stock market would be linear.
    - solinent 6y ago
      To summarize. The existing models just scratch the surface.
    - onion2k 6y ago
      Because the system is chaotic and we can't predict it beyond a week. Maybe a day at best. Once you can predict hurricanes, volcanoes, and tropical storms, then let me know. You're confusing weather and climate. We can't model the weather very well. It's hard. We can model the climate reasonably well (our models fit historical data really well), but the models turn out to be bad at predicting the future because we underestimate how much of an impact we're having (the article is a good example).