There is a AI x-risk documentary currently being filmed. An Inconvenient Doom. https://www.documentary-campus.com/training/masterschool/2024/inconvenient-doom It covers some aspects on AI safety, but doesn't focus on it exactly.

I also agree 5 is the main crux.

In the description of point 5, the OP says "Proving this assertion is beyond the scope of this post,", I presume that the proof of the assertion is made elsewhere. Can someone post a link to it?

I'm thirty-something. This was about 7 years ago. From the inhibitors? Nah. From the lab: probably.

We still smell plenty of things in a university chemistry lab, but I wouldn't bother with that kind of test for an unknown compound. Just go straight to NMR and mass spec, maybe IR depending on what you guess you are looking for. 

As a general rule don't go sniffing strongly, start with carefully wafting. Or maybe don't, if you truly have no idea what it is.

Most of us aren't dead. Just busy somewhere else.

I used to work in a chemistry research lab. For part of that I made Acetylcholinesterase inhibitors for potential treatment of Parkinson's Alzhiemer's. These are neurotoxins. As a general rule I didn't handle more than 10 lethal doses at once, however on one occasion I inhaled a small amount of the aerosolized powder and started salivating and I pissed my pants a little. 

As for tasting things, we made an effort to not let that happen. However as mentioned above, some sweeteners are very potent, a few micrograms being spilt on your hands, followed by washing, could leave many hundred nanograms behind. I could see how someone would notice this if they ate lunch afterwards. 

While tasting isn't common, smelling is. Many new chemicals would be carefully smelt as this often gave a quick indication if something novel had happened. Some chemical reactions can be tracked via smell. While not very precise, it is much faster than running an NMR. 

I think this distinction between "control" and "alignment" is important and not talked about enough.

Meta question: is the above picture too big?

Ok so the support score is influenced non-linearly by donor score. Is there a particular donor that has donated to the highest ranked 22 projects, that did not donate to the 23 or lower ranked projects? 

I have graphed donor score vs rank for the top GiveWiki donors. Does this include all donors in the calculation or are there hidden donors?

We see a massive drop in score from the 22nd to the 23rd project. Can you explain why this is occurring?