I have spent much of the last years trying to understand why it is that academics fail to understand the nature of the global temperature signal, whereas most engineers and those of a pragmatic nature who have studied the subject find themselves … let’s just say sceptical of the academic viewpoint.
In the past I’ve tried to explain this difference through a mechanistic approach: that academics do not encounter the same real world problems with the same real world knowledge, so when presented with a real world problem with real world noise & “natural variation”, they have no relevant skills or experience to draw on and so fail to recognise the true complexity of the situation. But I’m beginning to suspect a psychosurgical deficiency in the way academia behaves which is akin to autism.
Last night after watching a film on AI, I was discussing possible alternative strategies for developing AI with my wife in which I asserted that perhaps the biggest block to AI, was that academic researchers are trying to mimic their own “intelligence”. In other words, they may be basing their views on the false premise that what they perceive as “themselves” is “intelligent”. And the reason they cannot see beyond the idea of an “intelligent self” – is that they are falsely arrogant of their own abilities. (Without going into details, it would be like a kid using a calculator. Is the kid with the calculator “intelligent” – just because they come up with the right answers. Therefore is the academic who merely draws from the accumulated knowledge to answer a question really “intelligent”?)
Then afterwards I started researching Maasai group marriage traditions, and reading the academic papers I found the same kinds of “holier than thou” attitude in which those papers were trying to explain why the Maasai were not monogamous “like us”. I was just trying to understand – without allowing my own prejudices to get in the way – why group-marriage was the preferred system of the Maasai. But the academics appeared to want to explain why the Maasai “weren’t like us”.
My question: “what do the Maasai themselves think about group marriage versus monogamy”
Academic question: “why do the Maasai practice group marriage (with the implication they should be monogamous)”?
And, I am finding this more and more: academics are not asking the questions that I want to have answered. They simply either are not interested, or perhaps more accurately, do not understand the types of questions I ask. What is going on here? Continue reading
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Therefore if I had responded I would have taken a simple average gradient (LR) and picked those with the highest absolute gradient and depending if +ve or -ve have said they were +1 or -1C respectively. But unfortunately, I was missing one vital piece of information: how many had been adjusted.
Therefore, a bit of stats is required. We know the gradients fall into three buckets: those with no addition, those with +1/century and those with -1/century. Within each bucket the gradients should be a normal distribution (if the time series were random), and we know where each should be centred. So it should be possible to estimate the number that were in each bucket. That is just a question of putting each gradient into the most likely bucket. There’s probably some statistical trick for that, and I could have found it, but as Doug would have known this was the likely approach and have checked to ensure a 90% accuracy was impossible using this approach, so I knew it was pointless.
Instead, in order to win the $100,000 prize, it would have been necessary to “move away” from the optimum which would have been checked to ensure the prize could not be claimed, toward a sub-optimum solution which was sufficiently different that there was a small chance that it might have by accident picked the right ones (but most likely would be wrong).
But what if I did win?
It would then put me in a moral dilemma – since I could very well do with the money, I’m very happy Doug ran the competition – but he clearly never intended it to be won – and certainly not by a sceptic.
However, I would still be interesting to see a graph based on the scale of gradient chosen as the cut-off (above which it is assumed +1 or -1C/century added) and what percentage would be right using this very simple approach for each cut-off. I assume the graph would rise steadily as the threshold was increased because at first each increase would identify more right ones than wrong. But eventually the scale would be too large and it would start identifying more wrong than right.
The Top Graph
It’s just natural variation – it’s just as meaningless as the “global temperature” graph.