I think it’s best to restore it, I would have just used my throwaway otherwise and I discovered that I could still log in by a fluke. Although I was enjoying being anonymous while it lasted. Why aren’t deleted accounts just taken off of the database entirely? That seems like a holdover from using Reddit as the forum engine.
Arkanj3l
Karma: 261
Meetup hasn’t happened yet. Should the refutations be given on your time frame?
Your historian friends agreed with the global claim which I believe was fairly well established. From what I’ve heard talking to the interlocutor hosting this meetup (I am not he), it was *how* you extrapolated to that global claim from a local one that is being taken issue with. Notice that the historian on your blog also believes it is difficult to say to what degree Europe declined during the Dark Ages, although there are many possible markers. Notice that the reddit historian backing you is apologizing for your background rather than providing corroborative concrete evidence related to the structure of your argument. The Dominican Friar thing is nice and it’s understandable why you wouldn’t quote a private email, but it’s of course possible that they would make a similar mistake and taken without detail, it definitely seems like a pithy authority appeal.
As far as this meetup goes, from my discussions with the interlocutor, I’d expect mainly methodological criticisms, and criticisms of the rhetorical moves used to waive the limitations of the methodology. These are not the same as criticisms of the goals of SSC, or even the goals of a particular post. The substitutes recommended will be deeper reading of primary and secondary sources instead of *only* using SSC as a source (being that it’s tertiary and pop-sci), at the very least.
Maybe these criticisms once brought to light won’t be enough to brand you as a “pseudo-intellectual”, but people who do not take these kinds of criticisms into account will read your disclaimers against your expertise, yet would still be left with the inability to understand how these affect the soundness of your claims, because supposedly, they too, are not domain experts. I think such refutations, if valid and pondered, could be educational and sanity-raising for everyone in the SSC blogosphere.
Any LW-concept-specific critiques applicable to everyone else?
Do you know what it’s like to be stupid?
Similar in theme is “Vehicles: Experiments in Synthetic Psychology” by Valentino Braitenberg, in that creating simple systems that aren’t goal driven can nonetheless produce behavior that we characterize as emotional or thoughtful, somehow. It’s more exploratory and illustrative than principled or conceptual, but should be a good read.
Potential tool leveraging relative pragmatism and honesty of the LW community: “Hot or Not?” or attractiveness-rating app for members, done by the opposite gender, focused on physical attractiveness and specific criticism on what works and what doesn’t.
Routes around anxiety/weirdness of doing this IRL, specifically the honest commentary part.
I vouch for Ozzie Estimate.
I take shminux’s point to be primarily one of ease, or maybe portability. The need to understand sensitivity in heuristical estimation is a real one, and I also believe that your tools here may be the right approach for a different level of scale than was originally conceived by Fermi. It might be worth clarifying the kinds of decisions that require the level of analysis involved with your method to prevent confusion.
Have you seen the work of Sanjoy Mahajan? Street-Fighting Mathematics, or The Art of Insight in Science and Engineering?
Weirdness is a scarce resource with respect to ourselves? Great! Does that mean that we’d benefit from cooperating such that we all take on different facets of the weirder whole, like different faces of a PR operation?
Man, get out of my brain! I’m basically in all of those.
Just found this lecture dump for a course on algorithmic game theory and mechanism design for computer scientists: https://www.cs.duke.edu/courses/fall06/cps296.2/
If you scan the domain with google (i.e. with the ‘site:’ operator) some important PDFs come up.
If I could change anything, it would be seeking out problem-oriented instead of method-oriented mentors. Scientists and engineers can often be divided into two categories: those who are experts at a given method and look for problems to apply it to, and those who are experts at a given problem and look for tools to attack it with. Both can be productive strategies. I have a problem-oriented perspective, but most of my mentors have been method-oriented and don’t understand my unwavering focus on specific seemingly intractable problems.
I definitely get what you mean and I’ve been blessed with a problem-oriented mentor. However, I don’t really have a strategy to seek out some similar mentors and worry that in engineering it’s a lot more likely to find method-oriented persons. I’m wondering if you have any advice on this.
(My supposition: Non-applied mathematicians are dominantly problem oriented, but for problems that usually don’t matter. Programmers and applied mathematicians (like Operational Research guys) will probably experience a more even distribution between the two modes, however I would guess that it would lean towards problem-oriented as the underlying ontology of phenomena are necessarily modeled from scratch (in physics and chem most of our ontology is mapped, but not so in social problems except maybe with economics).)
Lately I’ve been less motivated to engage because of the intractability of the problems that grabbed my attention in the first place (intelligence amplification/cognition), even though it would be the more satisfying field from a curiosity standpoint (I like science and BME is highly integrated between all scientific disciplines).
What kind of paradigm shifts do you think will occur for biology in the future? Where are the current controversies for biology right now?
I voiced interest in making a career switch into BME. Would you still be doing biomedical engineering now if you knew what you now know about it? What would you change and why?
I’m having trouble knowing how well I understand a concept, while learning the concept. I tend to be good at making up consistent verbalizations of why something is, or how something works. However these verbalizations aren’t always accurate.
The first strategy against this trend is to simply do more problem sets with better feedback. I’m wondering if we can come up with a supplementary strategy where I can check if I really understand a concept or not.
What great timing! I’ve just started investigating the occult and chaos magick (with a ‘k’) just to see if it works.
just ask
It’s difficult when the creators are dead, or otherwise unaccessible (like busy hedge fundies). The next best thing are students who were mentored under the creator of the paradigm and are considered experts, but then the same check has to be applied to them on whether or not the ideas can be discussed. Overall I like the approach, it might still be possible to find journals, biographies or interviews with the originator of the viewpoint, as these are likely to contain some form of inquiry.
I have first-degree friends who have worked with 80K and they’ve said it’s unlikely that they would prioritize interviewing me, due to me not directly optimizing for earning-to-give (something which I made clear). I think it’s still worth a shot to try and be put in their candidate pool, and I could see if I could get an off-the-record conversation with some of the staff. So we’ll see.
That’s a good point. How mutually exclusive is the optimization path for being highly employable versus self-employing or bootstrapping? Is it just a question of efficiency of time spent or is there more to it?
How much computer science knowledge is necessary for startups, do you think? I can program and have worked on software modules and have written my own utilities, but I still have a lot to learn conceptually and I still need to survey a wider range of technologies, especially related to databases and web development in the front and back end. That’s even excluding some of the trendier hotspots like semantic web, NLP and machine learning.
I’m guessing that computer science majors can often pursue these biomedical-ish sorts of careers, but the reverse is not true (Biomedical Engineers typically don’t pursue computer science-ish careers).
I am strongly interested in figuring out if this is true. Do you have any thoughts on how I would do this?
Ha, if it’s any condolence I did delete the account myself three-ish years ago.