Hi all!
My name is Itamar Menuhin-Gruman, and I feel like a long-time newcomer to the community :)
On the EA front, I have been lately volunteering intensely in my local chapter (EA Israel), including leading the career fellowship program (loosely based on HIP's workbook), supporting the management in various capacities (such as helping in various operations behind our upcoming conference), and I have several ideas that I think would help the global community that I want to promote :)
On my career front, I took a meandring route. I started from ~3 years R&D in radiation propagation analysis (both in antennas design, mutual interference, and human safety fronts). I then did an undergrad in physics and applied math. Afterwards, I started a career in data science, first focusing on agriculture (~1 year), then cyber security (~2 years), followed by predicting high-risk population for various diseases, based on health records (~3 years).
In tandem, I completed an M.Sc. in mathematical theory of deep learning, and also was team leader of an iGEM team (studential synthetic biology competition) in creating algorithms for mutationally robust genetic designs. Today, I am studying for a Ph.D. in the field, on the same topic.
On a personal level, I have a lovely partner that taught me a lot about altruism, and two beautiful black cats that I'm fairly sure are not altruistic. I practice aerial acrobatics and japanese group drumming (taiko), and I have a particular fondness for going into new fields, especially when I have both a lot to learn and to contribute from the start.
Excellent post - I enjoyed reading it, and find the mental framework useful!
Two comments:
This work is an important piece of the puzzle, but I would love to see a deeper syntesis with other components of the puzzle - decision-making under high-intensity pain, system-wide mechanisms (e.g., hormones), cellular biology connections. For example, I could give a different explanation regarding high-intensity pain - it does not give evolutionary value, but rather the cellular mechanism leading to pain is (for reasons of energy efficiency) linear with the input, leading to strong signals when there are strong inputs. This, coupled with the fact that many organisms die under such circumstances, would lead to negligible evolutionary cost of this high-affective pain.
To be clear, I tend to agree with your explanation, but I think the framework would be stronger by either dealing with these counter-arguments in future work, or acknowledging these alternatives.
Definitely, thanks for putting it out there! It has been immensely useful :)
I absolutely agree!
I also appreciate this addition, I didn't think this would be of value to the community.
Hi Wladimir, impressive work!
I am working on designing and creating an agent for impact analysis - it seems like I could draw a lot on your experience, while our goals are complementary. I'll reach out to you via private chat :)