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Ha, if it's any condolence I did delete the account myself three-ish years ago.
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.
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?
I'm probably underweighing more conservative assessments like this, so I appreciate it.
motivation and self-delusion
I have not collected evidence the directly contradicts statistical assessments regarding the conscientiousness trait. Instead I'm making an inference based off a collection of evidence that I can name. I don't think I've given much consideration to evidence strength yet so working through this will be a good exercise.
For example:
Historically my conscientiousness has been quite low in part due to depression. I've been coming out of that depression recently, and have improved in my ability to keep on task even when I'm discouraged. Oftentimes psyching myself out was the reason why I haven't instigated behavioral change, because when I fall off the bandwagon I don't get back on. This change towards optimism makes me feel comparatively more competent and willing to explore my alternatives for support and skills.
Though, as a counterpoint: I am not experiencing mania, but the fact that I've recently acquired and optimistic temperament that has not been subject to calibration by the new action-space means that I might still be overestimating my abilities instead of underestimating them.
But given that I am strongly interested in doing things that successful people do that I couldn't before:
Nick Winter's assessments in his book "The Motivation Hacker" make me believe that there exists low hanging fruit when it comes to motivation that I have not yet picked. I would guess the same for typically surveyed people due to the recency of prescriptive motivation literature like "The Procrastination Equation".
Successful students and learners follow regular patterns of behavior that can be turned into habits. The particular examples would be the writings of Cal Newport, Scott H Young, in addition to consulting my academic advisors and the successful students themselves. Needless to say I probably haven't been using those patterns, which include precommtiments, oicking a good study environment and using it regularly, processing textbooks in a way that produces reviewable notes, and using office hours.
Twin and developmental studies might make me eat my dust on this if I'm directly challenging claims about a personality trait. I'm feeling a bit of resistance to looking them up but I should probably push through it and get it over with.
There are other conditions by which the amount of work and stress that someone can take on goes up, like joining the military; yes, I'm considering it. But there are also less extreme options like just having good health and being more organized, taking up a martial art or doing a sport. Not all of these are going to take off and most certainly I won't be doing all of them at once. So one obstacle I need to consider is the timeframe towards orienting myself properly for success in biomedical and whether the value is greater or lower than lost wages or other measures of opportunity cost.
I have also experimented with nootropics, which I know believe are overrated but still a useful tool in the toolkit. Finally I am beginning to use Anki, which might be a good way of managing larger volumes of knowledge.
At this point I would like to get answers to my questions on actual working conditions, hiring practices, and future work opportunities. Grabbing all of the experiences with the largest decision-relevant information:cost ratio possible could help me resolve whether this plan will work out. This is unless all of the evidence from current models is substantial enough to outweigh the potential evidence from empiricism.
computer science and self-study; old people
There are at least two components here: the actual studying and skill acquisition, and the judgement made by the hiring practitioner.
I read on Less Wrong in this popular PSA that a handful of people have managed to get programming jobs through self-study. Although it seems reckless - would it be possible to define a satisficing case for the amount of practice that I would do towards the profile of skills of what a hiring person would want from their employee? This would help resolve the following:
- whether or not the idea of studying is even feasible for the target skill level and time constraints
- if you control for skill level, and add the condition of whether I have a compsci major or don't have a compsci major, what do the probabilities of being hired look like? If for a person with a major at the expected skill level I will have has a largely dominating probability, then yeah, I would want to reconsider.
I could talk to HR people or other software engineers at developer meetups, or at career fairs, to get a clearer picture on this. But if like you claim this is a political factor, then maybe I won't be getting the evidence I need.
You need to find a job you can be satisfied first, and one that's doing the right thing second; you won't be productive if you're unhappy.
I'll keep this in mind. It does seem safer.
Note that I still have a timeline of 2-5 months before this plan can fully propogate to my actions. So that's the amount of time I have to research decision-relevant information and be able to pull through towards making my choice.
How do we more reliably ask ourselves the questions in the Useful Questions Repository?
I would love to identify more questions with the theme of "getting your concepts and beliefs closer to tacit reality as possible". I can't think of a better way to say it.
"Who is already occupying the kind of world that I want to be in such that I should go out and interview them?"
Agreed. Or Oxford for that matter.
Not to conflate my opinion's with shminux's, but I feel like a set of these maps from different hotspots of activity could help provide greater balance to the more implicit parts of Less Wrong's ethos. Consider the problem where those who visit Less Wrong for the first time conflate the above memes as what we consider a "rational" course of action; or consider how derivations of what's rational might depend on a background knowledge in ways that are easy to miss (the kind of biases that "softer" sciences may attempt to track). It's only possible to think what we have basis for in our memories, as per the availability heuristic. This could lead Less Wrong members to confuse the instrumental with the rational, similarly with the optimum and the rational.
It could also be possible to identify other potential "hotspots" for rationality communities if their culture follows a similar pattern. I imagine Minneapolis could be a city with such potential, for example, due to its youth population and tech firm presence.
Bagging Soylent: 40min work time, 60min elapsed (first time doing task, setting up. Optimization of manufacturing occurred while I was bagging.)
Doing Laundry: 70 mins total - 40mins washing with two rinse cycles and 30mins drying
Folding Large Laundry Load After Drying: 10 mins, 15 elapsed.
The world is a lot simpler than the human mind can comprehend. The mind endlessly manufactures meanings and reflects with other minds, ignoring reality. Or maybe it enhances it. Not very clear on that part, I'm human as well.
Spaced Repetition is only the beginning. http://bigthink.com/neurobonkers/assessing-the-evidence-for-the-one-thing-you-never-get-taught-in-school-how-to-learn
Here's How to Read - on page 2 there's a table that lists all of what this guy recommends, use that to evaluate if the rest of the document is worth your time. http://pne.people.si.umich.edu/PDF/howtoread.pdf
Also, if you know anyone who has gone to CFAR, start PMing them for the material on Propogating Urges. http://rationality.org/schedule/
Use some of the best-tested principles in experimental psychology to reinforce the behaviors you want to want, and avoid punishing yourself for doing things you want to do again. Pay attention to the immediate rewards and punishments you’re already doling out to yourself without noticing. If you always feel anxious when you think of a slow-moving project, you may be training yourself not to think about it at all. Connect the intermediate steps toward your goal to your natural enthusiasm for the result.
What you're doing to make reading papers fun is apparently something that Andrew Critch is very very good at, so keep it up, Critch Jr.
You just became stronger.
If someone takes notes they would be helpful to upload as well.
Adding Carrot - a search engine which takes your query and creates dynamic clusters of websites that form around related concepts. It's like a form of Google's related searches that does the sorting for you. There are also visualizations that it can generate for you that allow proportionality comparisons.
This is an example query for 'rationality' and this one is Explore vs Exploit with a visualization on the side.
Thank you! I like this one.
I haven't read the article so I could be full of shit, but essentially:
If you have the list of desired things ready, there should be an ETA on the work time necessary for each desired thing as well as confidence on that estimate. Confidence varies with past data and expected competence, e.g. how easily you believe you can debug the feature if you begin to draft it. Or such. Then you have a set of estimates for each implementable feature.
Then you put in time on that feature over the day tracked by some passive monitoring program like ManictTime or something like it.
The ratio of time spent on work that counted towards your features over the work that didn't is your productivity metric. As time goes on your confidence is calibrated in your feature-implementation work time estimates.
From Jacques Vallee, Messengers of Deception...
'Then he posed a question that, obvious as it seems, had not really occurred to me: “What makes you think that UFOs are a scientific problem?”
I replied with something to the effect that a problem was only scientific in the way it was approached, but he would have none of that, and he began lecturing me. First, he said, science had certain rules. For example, it has to assume that the phenomena it is observing is natural in origin rather than artificial and possibly biased. Now the UFO phenomenon could be controlled by alien beings. “If it is,” added the Major, “then the study of it doesn’t belong to science. It belongs to Intelligence.” Meaning counterespionage. And that, he pointed out, was his domain. *
“Now, in the field of counterespionage, the rules are completely different.” He drew a simple diagram in my notebook. “You are a scientist. In science there is no concept of the ‘price’ of information. Suppose I gave you 95 per cent of the data concerning a phenomenon. You’re happy because you know 95 per cent of the phenomenon. Not so in intelligence. If I get 95 per cent of the data, I know that this is the ‘cheap’ part of the information. I still need the other 5 percent, but I will have to pay a much higher price to get it. You see, Hitler had 95 per cent of the information about the landing in Normandy. But he had the wrong 95 percent!”
“Are you saying that the UFO data we us to compile statistics and to find patterns with computers are useless?” I asked. “Might we be spinning our magnetic tapes endlessly discovering spurious laws?”
“It all depends on how the team on the other side thinks. If they know what they’re doing, there will be so many cutouts between you and them that you won’t have the slightest chance of tracing your way to the truth. Not by following up sightings and throwing them into a computer. They will keep feeding you the information they want you to process. What is the only source of data about the UFO phenomenon? It is the UFOs themselves!”
Some things were beginning to make a lot of sense. “If you’re right, what can I do? It seems that research on the phenomenon is hopeless, then. I might as well dump my computer into a river.”
“Not necessarily, but you should try a different approach. First you should work entirely outside of the organized UFO groups; they are infiltrated by the same official agencies they are trying to influence, and they propagate any rumour anyone wants to have circulated. In Intelligence circles, people like that are historical necessities. We call them ‘useful idiots’. When you’ve worked long enough for Uncle Sam, you know he is involved in a lot of strange things. The data these groups get is biased at the source, but they play a useful role.
“Second, you should look for the irrational, the bizarre, the elements that do not fit...Have you ever felt that you were getting close to something that didn’t seem to fit any rational pattern yet gave you a strong impression that it was significant?”'
I'll say that I'm interested in what you have to offer just from the standpoint of novelty and exploration. However, your style doesn't lend itself to brevity and even though thinking out loud is valuable, getting seven pages out has made me lose track of the point.
I'm glad to see that on certain issues we are in intellectual agreement, but your writing style combined with the sheer amount of academic context you are bringing to the field makes any specific understanding very difficult. Although I am cursorily familiar with maybe a fourth of the authors you mentioned, I feel like in order to do justice for all of them I would need to read primary texts and get to know the literature better. This is something I currently don't have the time or patience for.
If there are any particular comments that you want to make to me, please do so in my private message box. I am open to picking your brain further and hearing what you have to say. Otherwise I would say that libertarian reform through quantum computers and courthouse bugs is outside the scope of this particular thread.
Anyway, much appreciated. Namaste.
I wanted to save time on doing time estimates of tasks when blocking them into a calendar.
Added GoogleGuide - http://www.googleguide.com/ (with practice and tutorials)
I would recommend editing the post.
It would be great to have a repository of task-time estimates, as well as "time until habitual." Setting estimates of how long one needs to practice before a "maintenance event horizon" occurs could aide in my motivation, at least.
I was mainly pointing out that the reliance on information that is accessible by most anybody is a benefit that levels the playing field, so to speak.
This is more of a request than a review. My current akrasia problems have to deal with filtering and prioritization. I have a lot of simultaneous "projects" going on. This is to say that I want to do all of them, but usually get trapped in doing busy-work like planning and budgeting and research, instead of building and execution. I switch often which makes switching costs very high.
All of my projects feel very urgent to me. But none of them get done. Thoughts?
Going down to the bottom of the post for the TL;DR, I was pleasantly surprised to having the need to go back up again.
Does he?
How could you demonstrate that status is adequate or inadequate as an explanation, in this case? Or any case?
Beware of universal explanations everywhere!
It's times like this where I wish there was a consistently updated dump of meetup summaries available for global use to all meetup organizers at the very least.
preference inference based on the structure of [your] goals
It's nothing too formal - wisdom gleaned from an article here and a blog post there.
Most of us readily have a list of goals that come to mind, but it's likely that they are subgoals and we are unaware of why exactly we do them. So, you keep on asking "What will this goal do for me?" instead of "What will do this goal for me?", creating downwind nodes in your graph until you presumably hit your preferences. In which case you (a) could check your preferences for consistency and overlap (see Nozick), and (b) investigate if your current subgoals are the best way to maximize your preferences, or find new ones.
Apparently this can be prescribed from the Connection Theory framework, but I haven't found it necessary to study Connection Theory. They make some interesting guesses about what happens when our stated goals conflict, amongst other things.
One day we're going to have to unpack "aesthetic" a bit. I think it's more than just 'oh it feels really nice and fun', but after we used it as applied to HPMOR and Atlas Shrugged - or parable fiction in general - I've been giving it a similar meaning as 'mindset' or 'way of viewing'. It's becoming less clear to me as to how to use the term.
I've been using it in justifications of reading (certain) fiction now, but I want to be careful that I'm not talking about something else, or something that doesn't exist, so my rationality can aim true.
Has anyone indexed the set of Five-Second Skill posts on Less Wrong? E.g. Get Curious, the Algorithm for Beating Procrastination, Value of Information etc.
Hearing some clear thinking will be a nice refreshment from the being processed in the bowels of cultural academia.
I'd love to cover how to find the exchange rate between opportunities, willingness to pay, and Making your explicit reasoning trustworthy., in that particular order. The latter I wanted to present but it features some pretty masterful rationality, so it might be beyond my capability.
I could lead a small talk on Job-hunt-hacking, but it could wait for next week if my plate is full.