3 ms·
The problem with presenting data is that you have to be an expert (e.g. a climate scientist in this case) to thoroughly understand the techniques and assumption
by greydius 10y ago
The problem with presenting data is that you have to be an expert (e.g. a climate scientist in this case) to thoroughly understand the techniques and assumptions used in the models. The average citizen, who is no doubt quite intelligent, isn't going to understand that stuff and certainly isn't going to put their life on hold to learn it. We need to look at the big picture here: society needs to trust science to get this stuff right. Or at the very least, we should all be asking ourselves "who benefits from the policy that this person is advocating?". The answer that we should accept for that question is "everyone", not "energy company shareholders".
- wolfgke 10y ago> We need to look at the big picture here: society needs to trust science to get this stuff right. Why do we trust in mathematical proofs? Answer: because one (theoretically) doesn't have to trust authorities, but can check the proof oneself. The same holds for results from empirical sciences: They can be falsified and lots of experiments have been done with the intention to falsify the theories and failed. By the way: This is also a strong argument for open access (because parking scientific results behind paywalls makes this really hard). Thus science is not about trusting authorities, but about being to verify yourself (structural sciences) and all. In other words: Science is about distrusting authorities and verifying/falsifying yourself.
- beevai142 10y agoThat's beside the point --- the argument above is that most people do not have time to obtain the expertise and check it yourself. So the next best thing is to trust someone who has done that, where you can't do much better than to trust consensus.
- wolfgke 10y agoIf you don't have the time to obtain the expertise one can still do good checks (only not in the details). For example if we are willing to accept the correctness (in some formalized sense) of a statistical test, we can still check whether it was applied correctly (or alternatively you can accept that it was applied correctly and try to understand the proof details behind the statistical methods). This way you will surely not get a complete understanding, but neverthess can check parts of the chain of conclusions and falsification attempts.
- greydius 10y agoI agree for the most part. The problem is that the science that needs to be done to verify/falsify results requires a lot of knowledge. We cannot reasonably expect every citizen to have that knowledge. If they did, we wouldn't have this problem. (We'd have other problems, like who's doing all the other jobs now that everyone is a climate scientist?) Your point about open access is very much on the mark, though. The society I want to live in is one that trusts science, and making all research freely available would, I think, greatly improve the general public's attitude even if they themselves cannot understand that research.