This is interesting as it runs counter to what many people think about current AI. Its performance seems directly linked to the quality of the training data it has. Here the opposite is happening; it has poor training data and still outperforms humans. It's not surprising the humans would do badly in this situation too; it's hard to keep up to date on things that you may only encounter once or twice in your entire career. It's interesting to extrapolate from this observation as it applies to many other fields.
One of the authors of the paper goes into more detail on Twitter.
What concerns me is that a lot of these efforts seem to be political in nature and are tied to mitigating the inevitable decline in the fossil fuel industry. More often it makes more sense to speed up the use of renewables and dropping the use of fossil fuels. Fossil fuel use still hasn't peaked. That is mainly driven by China, who are still building new coal and gas electricity plants. However the peak year of fossil fuel use is very near, there is some speculation it may even be this year for oil use. From then on it will be in steady decline, so of course that industry is going to do everything they can to delay.