[findateamfirst]

When on Earth did anti science trolls take such a prominent role in HN? It's not hard for me to imagine a misinformation campaign run against HN, because I can't really understand how someone technical could countenance anti climate change ideas.

[Analemma_]

You can come up with reasons to justify anything, once you're motivated by ideology. Being "more technical" sadly really only means that the justifications you come up with are more technical-sounding.

[js2]

mikeash was being sarcastic.

[davesque]

I'm fairly certain he was being sarcastic.

[exclusiv]

If you've done any sort of computer modeling, it's pretty easy to understand why technical people would have doubts. It's pretty easy to do it wrong and it's pretty easy to make it look right. Anyway, questioning is science and the debate is more about whether the sky is falling, whether man is primarily responsible, and if so what the next steps should be. So you can acknowledge that deforestation contributes to global warming as an example while being skeptical of the claims and modeling the environmentalists make.

[exclusiv]

This also doesn't help ease concerns with those that are skeptical of many reports and models:

http://www.washingtontimes.com/news/2017/feb/5/climate-chang...

> “Gradually, in the months after [the report] came out, the evidence kept mounting that Tom Karl constantly had his ‘thumb on the scale’ — in the documentation, scientific choices, and release of datasets — in an effort to discredit the notion of a global warming hiatus and rush to time the publication of the paper to influence national and international deliberations on climate policy,” Mr. Bates said Saturday on Climate Etc.

> “What John Bates has done is to expose this culture based not on robust science, but on promoting an agenda,” Mr. Pielke said in a comment on Climate Etc. “Regardless of one’s views on policies, the scientific method should not be hijacked as they have done.”

[digitalzombie]

It's an allegation base on evidence and report with no source.

The news article if you can call that, sources the Daily UK Mail as a source.

> Possible artifacts of data biases in the recent global surface warming hiatus,

There is no smoking gun. It's a hear say from one person or two.

[exclusiv]

Bates is an insider source as is Roger Pielke. We'll find out more as the investigation unfolds. There's more to this lack of discipline to scientific methods as they push for policy changes and their own agenda.

> Another prominent climate scientist, the University of Colorado’s Roger A. Pielke Sr., said Mr. Bates‘ experience was “consistent with my experiences” with Mr. Karl on the Climate Change Science Program in 2005.

[digitalzombie]

These modeling are base statistic which takes into account random errors.

Just cause you did computer modeling doesn't grant you magic power to understand machine learning or the vast swarth of area in statistic, mathematical modeling, etc...

And it certainly doesn't give you power over the dozen of experts in different fields that spend their whole lives in it and saying global warming is a thing.

If you're so skeptic about "computer modeling", then why google, apple, and many other are banking on Machine Learnin such as Neural Network?

The foundation of data science, some argue, is computational statistic. Which falls under this so call computer modeling you're bringing up.

[exclusiv]

I never said it grants you magic power to understand machine learning. You're putting that in my mouth.

What I was putting forth was an understanding on why some techies may be skeptical of the computer modeling which is the evidence of AGW and the near immediate doom and gloom. Machine learning is not infallible. We're very much in the infancy. And all of a sudden scientists are experts at modeling the sun, earth, moon, currents, etc? This is not social network / ad network / ecommerce optimization we are talking about.

Of course the models account for random errors but they also include a lot of assumptions. You can doctor any model to fit your agenda.

Computer models and neural networks have incredible potential and application, but to suggest that everyone should accept these models of the universe from scientists as if they are infallible makes no sense.