Yea, thanks. But is this true that these technical challenges really are more straightforward and only a matter of money poured in?
Regarding deference, I think that it's important to make clear that this holds mostly for the EA community, rather than the EA network.
When someone who is not actively involved in the EA community but is nevertheless working on a specific recommended cause, especially a more established cause, it may well be the case that their view on the matter has less impact than their career success.
This is relevant to movement building. Work that aims at outreach can involve more deferential point of view when seeking to inform people who might be interested in paths in the EA network, or more inquisitive activities aimed at people who might consider themselves as part of the EA community.
Cochrane had a team set up in 2011 to investigate better Priority Setting Methods.
Jaime Sevilla gave a detailed advice on how to generate research proposals, which might also be useful.
I was a bit surprised to read what you wrote about Cultivated Meat. I am not an expert, but I've looked into this topic and my understanding is that there are fundamental technical challenges to be solved at least in cell expansion, the rate and specificity of cell growth, and the creation of thick cuts of any tissue. I'm sure that these can be solved in the end, but they seem very difficult (considering that cell expansion is needed for making blood cells and other non-tissue type of cells in the much more heavily funded biomedical field which is also less bottlenecked by medium cost).
I understand that today we may be possible to make some hybrid products, but that these won't really be similar to the real thing. Is this similar to your view?
Regarding the possibility of Extinction level agents, there has been at least 2 species extinction cases that likely resulted from pathogens (here or in sci-hub).
Also, the Taino people were pretty much extinct and that may be mostly the result of disease, though it seems contended:
In thirty years, between 80% and 90% of the Taíno population died. Because of the increased number of people (Spanish) on the island, there was a higher demand for food. Taíno cultivation was converted to Spanish methods. In hopes of frustrating the Spanish, some Taínos refused to plant or harvest their crops. The supply of food became so low in 1495 and 1496, that some 50,000 died from the severity of the famine. Historians have determined that the massive decline was due more to infectious disease outbreaks than any warfare or direct attacks. By 1507, their numbers had shrunk to 60,000. Scholars believe that epidemic disease (smallpox, influenza, measles, and typhus) was an overwhelming cause of the population decline of the indigenous people, and also attributed a "large number of Taíno deaths...to the continuing bondage systems" that existed. Academics, such as historian Andrés Reséndez of the University of California, Davis, assert that disease alone does not explain the total destruction of indigenous populations of Hispaniola.
These two cases actually lower my fear of naturally accruing pandemics, because I'd expect to find more evidence. This in turn also lowers slightly my credence in the plausibility of engineered pandemics. I'm sure that other people here are much more knowledgeable than myself, and this brief analysis might be misleading.
Yes, thank you
Are the grants decided by taking the top applications or by passing some bar?
This reminded me of the Birds and Frogs distinction of mathematicians.
In a very shallow literature search, I found this review of the cognitive diversity literature. The closest thing there is a diversity in problem solving style which only has the Adaptors-Innovators distinction which may be slightly correlated but is a different thing.
I've written this interactive notebook in Foretold prediction platform. It is meant to be completely beginner friendly and takes about 2 hours to go through. I've used it as the basis for a workshop, and the accompanying slides can be found at the bottom of the notebook.
From the notebook:
In this interactive notebook, our goal is to actively try out forecasting and learn several basic tools. After this, you will be able to more easily use forecasts in your daily life and decision making, understand broadly how forecasters go about predicting stuff, and you should know if this is something you want to dive into deeper and how to go about that. We have 5 sections:We will start immediately with several examples.Then go on to understand how probabilities feel like, and how to be more calibrated.Work on the technique of outside view and inside view reasoning.Briefly discuss several interesting techniques - research, combining models and changing scope.Try out some actual forecasts from start to finish!
In this interactive notebook, our goal is to actively try out forecasting and learn several basic tools. After this, you will be able to more easily use forecasts in your daily life and decision making, understand broadly how forecasters go about predicting stuff, and you should know if this is something you want to dive into deeper and how to go about that. We have 5 sections: